amazon case study for xl dynamics

Hacking the Case Interview

If you’re interviewing for a business role at Amazon, there is a good chance that you’ll receive at least one case study interview, also known as an Amazon case interview. Amazon roles that include case study interviews as part of the interview process include:

• Business Analyst : Candidates are often given mini case interviews
• Business Development : Candidates are often given M&A case interviews
• Corporate Strategy : Candidates are often given strategy case interviews
• Product Manager : All candidates are given product manager case study interviews
• P roduct Marketing : Candidates are often often given product manager case study interviews
• Marketing : Candidates are often given marketing case interviews

To land an Amazon job offer, you’ll need to crush every single one of your case interviews. While Amazon case study interviews may seem ambiguous and challenging, know that they can be mastered with proper preparation.

If you are preparing for an upcoming Amazon case interview, we have you covered. In this comprehensive Amazon case interview guide, we’ll cover:

• What is an Amazon case study interview
• Why Amazon uses case study interviews
• The 6 steps to ace any Amazon case interview
• Amazon case interview tips
• Recommended Amazon case study interview resources

If you’re looking for a step-by-step shortcut to learn case interviews quickly, enroll in our case interview course . These insider strategies from a former Bain interviewer helped 30,000+ land tech and consulting offers while saving hundreds of hours of prep time.

What is an Amazon Case Study Interview?

Amazon case study interviews, also known as Amazon case interviews, are 20- to 30-minute exercises in which you are placed in a hypothetical business situation and are asked to find a solution or make a recommendation.

First, you’ll create a framework that shows the approach you would take to solve the case. Then, you’ll collaborate with the interviewer, answering a mix of quantitative and qualitative questions that will give you the information and data needed to develop an answer. Finally, you’ll deliver your recommendation at the end of the case.

Case interviews have traditionally been used by consulting firms to assess a candidate’s potential to become a successful consultant. However, now a days, many companies with ex-consultants use case studies to assess a candidate’s capabilities. Since Amazon has so many former consultants in its business roles, you’ll likely encounter at least one case study interview.

The business problems that you’ll be given in an Amazon case study interview will likely be real challenges that Amazon faces today:

• How can Amazon improve customer retention for their Amazon Prime subscription service?
• How can Amazon improve its digital streaming service?
• How can Amazon increase ad revenues from merchant sellers?
• How should Amazon deal with fake products among its product listings?
• How can Amazon Web Services outcompete Microsoft Azure?

Depending on what team at Amazon you are interviewing for, you may be given a business problem that is relevant to that specific team.

Although there is a wide range of business problems you could possibly be given in your Amazon case interview, the fundamental case interview strategies to solve each problem is the same. If you learn the right strategies and get enough practice, you’ll be able to solve any Amazon case study interview.

Why does Amazon Use Case Study Interviews?

Amazon uses case study interviews because your performance in a case study interview is a measure of how well you would do on the job. Amazon case interviews assess a variety of different capabilities and qualities needed to successfully complete job duties and responsibilities.

Amazon’s case study interviews primarily assess five things:

• Logical, structured thinking : Can you structure complex problems in a clear, simple way?
• Analytical problem solving : Can you read, interpret, and analyze data well?
• Business acumen : Do you have sound business judgment and intuition?
• Communication skills : Can you communicate clearly, concisely, and articulately?
• Personality and cultural fit : Are you coachable and easy to work with?

Since all of these qualities can be assessed in just a 20- to 30-minute case, Amazon case study interviews are an effective way to assess a candidate’s capabilities.

In order to do well on the personality and cultural fit portion, you should familiarize yourself with  Amazon’s Leadership Principles before your interview. At a high level, these principles include:

• Customer obsession : Leaders start with the customer and work backwards
• Ownership : Leaders are owners and act on behalf of the entire company
• Invent and simplify : Leaders expect and require innovation and invention from their teams and always find ways to simplify
• Learn and be curious : Leaders are never done learning and always seek to improve themselves
• Insist on the highest standards : Leaders have relentlessly high standards
• Think big : Leaders create and communicate a bold direction that inspires results
• Frugality : Accomplish more with less
• Earn trust : Leaders listen attentively, speak candidly, and treat others respectfully
• Dive deep : Leaders operate at all levels and stay connected to the details
• Deliver results : Leaders focus on key inputs for their business and deliver them with the right quality and in a timely fashion

The 6 Steps to Solve Any Amazon Case Interview

In general, there are six steps to solve any Amazon case study interview.

1. Understand the case

Your Amazon case interview will begin with the interviewer giving you the case background information. While the interviewer is speaking, make sure that you are taking meticulous notes on the most important pieces of information. Focus on understanding the context of the situation and the objective of the case.

Don’t be afraid to ask clarifying questions if you do not understand something. You may want to summarize the case background information back to the interviewer to confirm your understanding of the case.

The most important part of this step is to verify the objective of the case. Not answering the right business question is the quickest way to fail a case interview.

2. Structure the problem

The next step is to develop a framework to help you solve the case. A framework is a tool that helps you structure and break down complex problems into smaller, more manageable components. Another way to think about frameworks is brainstorming different ideas and organizing them into different categories.

For a complete guide on how to create tailored and unique frameworks for each case, check out our article on case interview frameworks .

Before you start developing your framework, it is completely acceptable to ask the interviewer for a few minutes so that you can collect your thoughts and think about the problem.

Once you have identified the major issues or areas that you need to explore, walk the interviewer through your framework. They may ask a few questions or provide some feedback.

3. Kick off the case

Once you have finished presenting your framework, you’ll start diving into different areas of your framework to begin solving the case. How this process will start depends on whether the case interview is candidate-led or interviewer-led.

If the case interview is a candidate-led case, you’ll be expected to propose what area of your framework to start investigating. So, propose an area and provide a reason for why you want to start with that area. There is generally no right or wrong area of your framework to pick first.

If the case interview is interviewer-led, the interviewer will tell you what area of the framework to start in or directly give you a question to answer.

4. Solve quantitative problems

Amazon case study interviews may have some quantitative aspect to them. For example, you may be asked to calculate a certain profitability or financial metric. You could also be asked to estimate the size of a particular market or to estimate a particular figure.

The key to solving quantitative problems is to lay out a structure or approach upfront with the interviewer before doing any math calculations. If you lay out and present your structure to solve the quantitative problem and the interviewer approves of it, the rest of the problem is just simple execution of math.

5. Answer qualitative questions

Amazon case study interviews may also have qualitative aspects to them. You may be asked to brainstorm a list of potential ideas. You could also be asked to provide your opinion on a business issue or situation.

The key to answering qualitative questions is to structure your answer. When brainstorming a list of ideas, develop a structure to help you neatly categorize all of your ideas. When giving your opinion on a business issue or situation, provide a summary of your stance or position and then enumerate the reasons that support it.

6. Deliver a recommendation

In the last step of the Amazon case interview, you’ll present your recommendation and provide the major reasons that support it. You do not need to recap everything that you have done in the case, so focus on only summarizing the facts that are most important.

It is also good practice to include potential next steps that you would take if you had more time or data. These can be areas of your framework that you did not have time to explore or lingering questions that you do not have great answers for.

Amazon Case Interview Tips

Below are eight of our best tips to help you perform your best during your Amazon case study interview.

1. Familiarize yourself with Amazon’s business model

If you don’t understand Amazon’s business model, it will be challenging for you to do well in their case interviews. If you are interviewing for the Amazon Web Services team, you should know how Amazon makes money as a cloud service provider. If you are interviewing for the Amazon Prime team, you should be familiar with how their subscription service works.

2. Read recent news articles on Amazon

A lot of the times, the cases you’ll see in an Amazon case study interview are real business issues that the company faces. Reading up on the latest Amazon news will give you a sense of what Amazon’s biggest challenges are and what major business decisions they face today. There is a good chance that your case study interview will be similar to something that you have read in the news.

3. Verify the objective of the case 

Answering the wrong business problem will waste a lot of time during your Amazon case study interview. Therefore, the most critical step of the case interview is to verify the objective of the case with the interviewer. Make sure that you understand what the primary business issue is and what overall question you are expected to answer at the end of the case.

4. Ask clarifying questions

Do not be afraid to ask questions. You will not be penalized for asking questions that are important and relevant to the case. 

Great questions to ask include asking for the definition of an unfamiliar term, asking questions that clarify the objective of the case, and asking questions to strengthen your understanding of the business situation.

5. Do not use memorized frameworks

Interviewers can tell when you are using memorized frameworks from popular case interview prep books. Amazon values creativity and intellect. Therefore, make every effort to create a custom, tailored framework for each case that you get.

6. Always connect your answers to the case objective

Throughout the case, make sure you are connecting each of your answers back to the overall business problem or question. What implications does your answer have on the overall business problem?

Many candidates make the mistake of answering case questions correctly, but they don’t take the initiative to tie their answer back to the case objective.

7. Communicate clearly and concisely

In an Amazon case study interview, it can be tempting to answer the interviewer’s question and then continue talking about related topics or ideas. However, you have a limited amount of time to solve an Amazon case, so it is best to keep your answers concise and to the point.

Answer the interviewer’s question, summarize how it impacts the case objective, and then move onto the next important issue or question.

8. Be enthusiastic

Amazon wants to hire candidates that love their job and will work hard. Displaying enthusiasm shows that you are passionate about working at Amazon. Having a high level of enthusiasm and energy also makes the interview more enjoyable for the interviewer. They will be more likely to have a positive impression of you.

Recommended Amazon Interview Resources

Here are the resources we recommend to land an Amazon job offer:

For help landing interviews

• Resume Review & Editing : Transform your resume into one that will get you multiple interviews

For help passing case interviews

• Comprehensive Case Interview Course (our #1 recommendation): The only resource you need. Whether you have no business background, rusty math skills, or are short on time, this step-by-step course will transform you into a top 1% caser that lands multiple consulting offers.
• Case Interview Coaching : Personalized, one-on-one coaching with a former Bain interviewer.
• Hacking the Case Interview Book   (available on Amazon): Perfect for beginners that are short on time. Transform yourself from a stressed-out case interview newbie to a confident intermediate in under a week. Some readers finish this book in a day and can already tackle tough cases.
• The Ultimate Case Interview Workbook (available on Amazon): Perfect for intermediates struggling with frameworks, case math, or generating business insights. No need to find a case partner – these drills, practice problems, and full-length cases can all be done by yourself.

For help passing behavioral & fit interviews

• Behavioral & Fit Interview Course : Be prepared for 98% of behavioral and fit questions in just a few hours. We'll teach you exactly how to draft answers that will impress your interviewer.

Land Multiple Tech and Consulting Offers

Complete, step-by-step case interview course. 30,000+ happy customers.

Predicting The Future Of Demand: How Amazon Is Reinventing Forecasting With Machine Learning

What if you could use data to predict what a customer will buy, one year before they even know they want it?

Automating through machine learning (ML) allowed Amazon.com to predict future demand for millions of products globally in seconds. Leaders at the multinational tech giant successfully reinvented their data infrastructure to improve buying systems, automate the placement of inventory in fulfillment centers, and deliver on their promise of two-day shipping to customers.

Through a comprehensive predictive model built entirely on the cloud, Amazon.com is using data to make better decisions, streamline operations, and deliver winning consumer experiences.

Reinventing manual product forecasting through machine learning

Predicting customer demand is no easy task in e-commerce since delayed inventory or inaccurate shipments can be costly and disrupt the supply chain. Although 80% to 90% of all planning tasks can be automated, many industries still rely on manual forecasting.

E-commerce retailers sometimes need to forecast hundreds of millions of products, and “no amount of human brain power can forecast at that scale on a daily basis,” says Jenny Freshwater, vice president of Traffic & Marketing Technology at Amazon.com, and former VP of Forecasting. Freshwater’s team led forecasting of over 400 million products at Amazon.

Engineering teams, no matter how advanced, can’t do it all: assess historical trends, develop unit sales projections, and conduct independent research for such a high volume of products. Even when combined with more sophisticated models, legacy systems, like outdated computing software or manual inventory logs, won’t be as accurate as machine learning models.

And when demand spikes unexpectedly, the burden on the supply chain can become even more difficult to handle without modern forecasting methods. When toilet paper sales surged by 213% at the height of the Covid-19 pandemic, Amazon used AI-driven predictive forecasting to respond quickly to unforeseen demand signals and increase adaptability to market fluctuations Freshwater notes, “Of course, we could have never anticipated that spike prior to COVID, but our models reacted quickly to the new demand trend.”

Freshwater recommends that retailers reprioritize their machine learning roadmaps to cope with the unexpected. The pandemic was the trigger for her team to make changes and implement new ideas. The team reinvented inputs to their models, including using medical data, COVID case counts and macroeconomic data, and shifted from forecasting based on a number with confidence intervals to scenario-based forecasting. “What we found was that the work that we had to do around the pandemic, almost all of it, from adding new data, to new features, to scenario forecasting, we had thought of before, but had never prioritized, because it wasn't urgent at the time,” she says. “With the pandemic hitting, we reprioritized. And many of the things that we had wanted to implement in the past are now in production.”

How Amazon.com became a leader in product forecasting

According to Freshwater, Amazon’s journey with machine learning began about 10 years ago to improve forecast accuracy. “We started to use machine learning because our moving average models were just not as accurate as we had hoped they would be.”

Company leaders saw a need to use data and machine learning to deliver on customer promises and achieve cost-effective functionality at scale. With those goals in mind, Amazon.com set out to become an AI-driven leader in product forecasting.

To accelerate the process in the face of rising demand, the company partnered with Amazon Web Services (AWS) to build “machine learning models that have grown in terms of magnitude of data, the features that we use to predict demand, as well as the complexity of the algorithms, to where today, we're using neural network models to predict demand for the products that we sell on Amazon.” Freshwater says, “We looked at how our human forecasts were performing and how our machine learning forecasts were performing. And it was night and day in terms of the difference.”

Amazon.com uses machine learning on AWS to aggregate and analyze purchasing data on products, and run their forecasting models. Additionally, the company uses browsing and purchasing data to provide more tailored product recommendations. Machine learning allows for data experimentation that enables data scientists to create a better and more personalized experience for customers.

For Freshwater, prototyping and iteration was key to achieving machine learning success. ”We used a prototyping approach, looking at specific use cases, measuring the results against our existing models, and, at a certain point, we were able to achieve a 15 times greater improvement than we'd ever achieved before through these neural network models,” she says. “So, it was very much an iterative process.

Key takeaways for business leaders using predictive models

ML on the cloud is key to deriving valuable insights from data and making better business decisions. Consider these practices to maximize ML modeling in your reinvention journey.

• Trust the model. Regular monitoring of millions of products takes up valuable engineering time and resources. Freshwater says nearly all of Amazon’s “forecasting is automated through machine learning models, and human beings and business users only interact with the forecast and override it when they have some information that the models couldn't possibly have.” Leaders should encourage teams to selectively interact with the forecast, letting the models work while business users focus on other critical tasks. Overrides should be considered when you are confident you have more qualitative or trend-focused information than the model.
• Define a clear data strategy. It’s impossible to think of machine learning – and getting real value out of ML models – without first having a data strategy in place. At Amazon, preparing the data for ML use was a key part of the strategy. “When I talk to people about our journey from our old modeling to the new, I guess that about 40% of the time was actually spent in preparing the data,” says Freshwater. “Features are really all about getting the data in the right place. Without really spending that time and effort, we would risk either getting poor results or biased results because the data didn't properly represent our decision set.” Building a data strategy that aligns with business goals, prioritizing data cleansing, and making data representative of what you’re trying to predict or optimize is key for leaders starting their ML journey.
• Know what you’re measuring. Early on in your reinvention journey, it’s important to be crisp about what you’re measuring and how you know you’ve improved. Freshwater recalls, “In our problem space, we were forecasting for more and more products every year. So just by looking at year over year comparisons, it wasn't good enough. We had to implement a series of benchmarking models that used completely different scientific methodology to know if versus the benchmark, our new models were better.” Spend time upfront defining your measurement and success criteria to prevent time wasted on churn.
• Build a data-driven culture. Getting the most out of your machine learning initiatives requires nurturing a cultural of innovation and data-driven thinking across the organization. “Reinvention projects really are about being able to take risks and being able to fail fast,” says Freshwater. “Pick people who are OK with several failures before a success. I think that culture needs to be encouraged when you’re working on any prototype – because the first results aren't always a winner. If they are, maybe you're not thinking big enough.” When experimenting with machine learning, make sure you have people at all levels of the organization who are passionate about the prospect of what ML can deliver. Freshwater adds, “Given that Amazon is such a data-driven culture, we were able to move the needle almost entirely towards machine learning, just by looking at the fact that our models were much more accurate from a forecasting accuracy perspective.”

Amazon has paved the way for predicting the future, but they’re just getting started. Your organization too can reinvent itself using AI technologies and data. Learn more at aws.amazon.com/data/ .

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Amazon.com marketing strategy 2023: E-commerce retail giant business case study

What goes into the Amazon marketing strategy secret sauce? Our business case study explores Amazon's revenue model and culture of customer metrics, history of Amazon.com and marketing objectives

In the final quarter of 2022, Amazon reported net sales of over $149.2 billion. This seasonal spike is typical of Amazon's quarterly reporting , but the growth is undeniable as this was the company's highest quarter ever.

There is no doubt that the e-commerce retail giant continues to lead the way in e-commerce growth. The Amazon marketing strategy we are familiar with today has evolved since it was founded in 1994.

I've highlighted the Amazon marketing strategy case study in my books for nearly 20 years now since I think all types of businesses can learn from their digital business strategy. Their response to the pandemic is impressive but not entirely surprising for a brand that is ' customer obsessed '.

From startups and small businesses to large international businesses, we can all learn from their focus on the customer, particularly at this time, testing market opportunities made available by digital technology, and their focus on testing and analysis to improve results.

Their focus on customer experience put Amazon in the role of a thought leader in e-commerce experience. However, whether due to diminished customer service, or increasing customer expectations, or a mixture of the two, fulled by a global pandemic - notably, 2020 was the first time Amazon's ACSI customer satisfaction rating dropped below 80 since launch, to 65%.

With customer satisfaction now measuring at 79% in 2022 , customer satisfaction in Amazon has risen again, but is still not as high as it once was.

Currently, Forbes gives a consensus recommendation to buy Amazon stock, giving a return on assets (TTM) of 1.73%. The stock performance is not as high as we saw in 2020 and 2021, but it did show some growth in late 2022 - early 2023.

I aim to keep this case study up-to-date for readers of the books and Smart Insights readers who may be interested. In it, we look at Amazon's background, revenue model, and sources for the latest business results.

We can also learn from their digital marketing strategy, since they use digital marketing efficiently across all customer communications touchpoints in our RACE Framework :

• Reach : Amazon's initial business growth based on a detailed approach to SEO and AdWords targeting millions of keywords.
• Act : Creating clear and simple experiences through testing and learning.
• Convert : Using personalization to make relevant recommendations and a clear checkout process that many now imitate.
• Engage : Amazon's customer-centric culture delights customers and keeps them coming back for more.

Looking to optimize your marketing strategy? We've got marketing solutions for your e-commerce business. From startups to retail giants, our bespoke marketing training empowers e-commerce marketers to plan, manage and optimize their marketing strategies, with marketing tools proven to generate growth. Find out more.

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Amazon's growth and business model evolution

Forbes credits Amazon's success to 3 rules which it breaks, but we 'probably shouldn't'!

• Strategy is about focus - although Amazon has an incredible number of strands to the business today.
• Don’t throw good money after bad - with criticism in particular of Amazon's investment in groceries.
• Your core competencies determine what you can and can’t do - developing the Kindle with no hardware manufacturing experience.

In this way, Forbes outlines a 'risky' approach to marketing strategy which, for Amazon, paid off in dividends. So, there is plenty to learn from studying this company, even if we decide not to replicate all tactics and strategies.

Amazon.com mission and vision

When it first launched, Amazon’s had a clear and ambitious mission. To offer:

Earth’s biggest selection and to be Earth’s most customer-centric company.

Today, with business users of its Amazon Web Service representing a new type of customer, Amazon says:

this goal continues today, but Amazon’s customers are worldwide now and have grown to include millions of Con-sumers, Sellers, Content Creators, Developers, and Enterprises. Each of these groups has different needs, and we always work to meet those needs, by innovating new solutions to make things easier, faster, better, and more cost-effective.

20 years later, Amazon are still customer-centric, in fact, in the latest Amazon Annual report , 2021, Jeff Bezos of Amazon explains customer obsession.

"We seek to be Earth’s most customer-centric company and believe that our guiding principle of customer obsession is one of our greatest strengths. We seek to offer our customers a comprehensive selection of products, low prices, fast and free delivery, easy-to-use functionality, and timely customer service. By focusing obsessively on customers, we are internally driven to improve our services, add benefits and features, invent new products, lower prices, increase product selection, and speed up shipping times—before we have to."

Amazon business and revenue model

I recommend anyone studying Amazon checks the latest annual reports, proxies, and shareholder letters. The annual filings give a great summary of eBay business and revenue models.

The 2020 report includes a great vision for Digital Agility (reprinted from 1997 in their latest annual report) showing testing of business models that many businesses don't yet have. Amazon explain:

"We will continue to measure our programs and the effectiveness of our investments analytically, to jettison those that do not provide acceptable returns, and to step up our investment in those that work best. We will continue to learn from both our successes and our failures".

They go on to explain that business models are tested from a long-term perspective, showing the mindset of CEO Jeff Bezos:

We will continue to make investment decisions in light of long-term market leadership considerations rather than short-term profitability considerations or short-term Wall Street reactions.

The latest example of innovation in their business model is the launch of Amazon Go, a new kind of store with no checkout required. Boasting a "Just Walk Out Shopping experience",the Amazon Go app users enter the store, take the products they want, and go with no lines and no checkout.

More recently, there have been a range of business model innovations focussed on hardware and new services: Kindle e-readers, Fire Tablet, smartphone and TV, Echo (using the Alexa Artificial Intelligence voice-assistant), grocery delivery, Amazon Fashion and expansion to the business-oriented Amazon Web Services (AWS). Amazon Prime, an annual membership program that includes unlimited free shipping and then involved diversification to a media service with access to unlimited instant streaming of thousands of movies and TV episodes.

AWS is less well-known outside of tech people, but Amazon is still pursuing this cloud service aggressively. They now have 10 AWS regions around the world, including the East Coast of the U.S., two on the West Coast, Europe, Singapore, Tokyo, Sydney, Brazil, China, and a government-only region called GovCloud.

Amazon marketing strategy

In their 2008 SEC filing, Amazon describes the vision of their business as to:

“Relentlessly focus on customer experience by offering our customers low prices, convenience, and a wide selection of merchandise.”

The vision is still to consider how the core Amazon marketing strategy value proposition is communicated both on-site and through offline communications.

Of course, achieving customer loyalty and repeat purchases has been key to Amazon’s success. Many dot-coms failed because they succeeded in achieving awareness, but not loyalty. Amazon achieved both. In their SEC filing they stress how they seek to achieve this. They say:

" We work to earn repeat purchases by providing easy-to-use functionality, fast and reliable fulfillment, timely customer service, feature-rich content, and a trusted transaction environment.

Key features of Amazon include:

• editorial and customer reviews;
• manufacturer product information;
• web pages tailored to individual preferences, such as recommendations and notifications; 1-Click® technology;
• secure payment systems;
• image uploads;
• searching on our websites as well as the Internet;
• browsing; and the ability to view selected interior pages and citations, and search the entire contents of many of the books we offer with our “Look Inside the Book” and “Search Inside the Book” features.

The community of online customers also creates feature-rich content, including product reviews, online recommendation lists, wish lists, buying guides, and wedding and baby registries."

In practice, as is the practice for many online retailers, the lowest prices are for the most popular products, with less popular products commanding higher prices and a greater margin for Amazon.

Free shipping offers are used to encourage increase in basket size since customers have to spend over a certain amount to receive free shipping. The level at which free shipping is set is critical to profitability and Amazon has changed it as competition has changed and for promotional reasons.

Amazon communicates the fulfillment promise in several ways including the presentation of the latest inventory availability information, delivery date estimates, and options for expedited delivery, as well as delivery shipment notifications and update facilities.

This focus on customer has translated to excellence in service with the 2004 American Customer Satisfaction Index giving Amazon.com a score of 88 which was at the time, the highest customer satisfaction score ever recorded in any service industry, online or offline.

Round (2004) notes that Amazon focuses on customer satisfaction metrics. Each site is closely monitored with standard service availability monitoring (for example, using Keynote or Mercury Interactive) site availability and download speed. Interestingly it also monitors per minute site revenue upper/lower bounds – Round describes an alarm system rather like a power plant where if revenue on a site falls below $10,000 per minute, alarms go off! There are also internal performance service-level-agreements for web services where T% of the time, different pages must return in X seconds.

The importance of technology and an increased focus on Artificial Intelligence and Machine Learning

According to founder and CEO, Jeff Bezos, technology is very important to supporting this focus on the customer. In their 2010 Annual Report (Amazon, 2011) he said:

“Look inside a current textbook on software architecture, and you’ll find few patterns that we don’t apply at Amazon. We use high-performance transactions systems, complex rendering and object caching, workflow and queuing systems, business intelligence and data analytics, machine learning and pattern recognition, neural networks and probabilistic decision making, and a wide variety of other techniques." And while many of our systems are based on the latest in computer science research, this often hasn’t been sufficient: our architects and engineers have had to advance research in directions that no academic had yet taken. Many of the problems we face have no textbook solutions, and so we — happily — invent new approaches”… All the effort we put into technology might not matter that much if we kept technology off to the side in some sort of R&D department, but we don’t take that approach. Technology infuses all of our teams, all of our processes, our decision-making, and our approach to innovation in each of our businesses. It is deeply integrated into everything we do”.

The quote shows how applying new technologies is used to give Amazon a competitive edge. A good recent example of this is providing the infrastructure to deliver the Kindle “Whispersync” update to ebook readers. Amazon reported in 2011 that Amazon.com is now selling more Kindle books than paperback books. For every 100 paperback books Amazon has sold, the Company sold 115 Kindle books. Kindle apps are now available on Apple iOS, Android devices and on PCs as part of a “ Buy Once, Read Anywhere ” proposition which Amazon has developed.

Some of the more recent applications of AI at Amazon are highly visible, for example, the Amazon Echo assistant and technology in the Amazon Go convenience store that uses machine vision to eliminate checkout lines.

In their 2017 report, they describe the increased use of machine learning and AI ‘behind the scenes’ at Amazon:   "much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type – quietly but meaningfully improving core operations".

Amazon Customers

Amazon defines what it refers to as three consumer sets customers, seller customers and developer customers.

There are over 76 million customer accounts, but just 1.3 million active seller customers in it’s marketplaces and Amazon is seeking to increase this. Amazon is unusual for a retailer in that it identifies “developer customers” who use its Amazon Web Services, which provides access to technology infrastructure such as hosting that developers can use to develop their own web services.

Members are also encouraged to join a loyalty program, Amazon Prime, a fee-based membership program in which members receive free or discounted express shipping, in the United States, the United Kingdom, Germany, and Japan.

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As we know, e-commerce marketing is all about the customers. Our RACE Growth System down your customer journeys into a simple 5-step structure of plan - reach - act - convert - engage. Create a winning retail e-commerce marketing strategy with Smart Insights, to acquire and retain more customers, and accelerate your ROI. Get started today.

Competition

In its 2017 SEC filing Amazon describes the environment for our products and services as ‘intensely competitive’. It views its main current and potential competitors as:

• 1) online, offline, and multichannel retailers, publishers, vendors, distributors, manufacturers, and producers of the products we offer and sell to consumers and businesses;
• (2) publishers, producers, and distributors of physical, digital, and interactive media of all types and all distribution channels;
• (3) web search engines, comparison shopping websites, social networks, web portals, and other online and app-based means of discovering, using, or acquiring goods and services, either directly or in collaboration with other retailers;
• (4) companies that provide e-commerce services, including website development, advertising, fulfillment, customer service, and payment processing;
• (5) companies that provide fulfillment and logistics services for themselves or for third parties, whether online or offline;
• (6) companies that provide information technology services or products, including on- premises or cloud-based infrastructure and other services; and
• (7) companies that design, manufacture, market, or sell consumer electronics, telecommunication, and electronic devices.

It believes the main competitive factors in its market segments include "selection, price, availability, convenience, information, discovery, brand recognition, personalized services, accessibility, customer service, reliability, speed of fulfillment, ease of use, and ability to adapt to changing conditions, as well as our customers’ overall experience and trust in transactions with us and facilitated by us on behalf of third-party sellers".

For services offered to business and individual sellers, additional competitive factors include the quality of our services and tools, their ability to generate sales for third parties we serve, and the speed of performance for our services.

From Auctions to marketplaces

Amazon auctions (known as zShops) were launched in March 1999, in large part as a response to the success of eBay. They were promoted heavily from the home page, category pages and individual product pages. Despite this, a year after its launch it had only achieved a 3.2% share of the online auction compared to 58% for eBay and it only declined from this point.

Today, competitive prices of products are available through third-party sellers in the ‘Amazon Marketplace’ which are integrated within the standard product listings. A winning component of the Amazon marketing strategy for marketplaces was the innovation to offer such an auction facility, initially driven by the need to compete with eBay. But now the strategy has been adjusted such that Amazon describe it as part of the approach of low-pricing.

Although it might be thought that Amazon would lose out on enabling its merchants to sell products at lower prices, in fact Amazon makes greater margin on these sales since merchants are charged a commission on each sale and it is the merchant who bears the cost of storing inventory and fulfilling the product to customers. As with eBay, Amazon is just facilitating the exchange of bits and bytes between buyers and sellers without the need to distribute physical products.

Amazon Media sales

You may have noticed that unlike some retailers, Amazon displays relevant Google text ads and banner ads from brands. This seems in conflict with the marketing strategy of focus on experience since it leads to a more cluttered store. However in 2011 Amazon revealed that worldwide media sales accounted for approximately 17% of revenue!

Whilst it does not reveal much about the Amazon marketing strategy approach in its annual reports, but there seems to be a focus on online marketing channels. Amazon (2011) states “we direct customers to our websites primarily through a number of targeted online marketing channels, such as our Associates program, sponsored search, portal advertising, email marketing campaigns, and other initiatives”.

These other initiatives may include outdoor and TV advertising, but they are not mentioned specifically. In this statement they also highlight the importance of customer loyalty tools. They say: “while costs associated with free shipping are not included in marketing expense, we view free shipping offers and Amazon Prime as effective worldwide marketing tools, and intend to continue offering them indefinitely”.

How ‘The Culture of Metrics’ started

A common theme in Amazon’s development is the drive to use a measured approach to all aspects of the business, beyond the finance. Marcus (2004) describes an occasion at a corporate ‘boot-camp’ in January 1997 when Amazon CEO Jeff Bezos ‘saw the light’. ‘

At Amazon, we will have a Culture of Metrics’, he said while addressing his senior staff. He went on to explain how web-based business gave Amazon an ‘amazing window into human behaviour’.

Marcus says: ‘Gone were the fuzzy approximations of focus groups, the anecdotal fudging and smoke blowing from the marketing department' - the Amazon marketing strategy was reborn!

A company like Amazon could (and did) record every move a visitor made, every last click and twitch of the mouse. As the data piled up into virtual heaps, hummocks and mountain ranges, you could draw all sorts of conclusions about their chimerical nature, the consumer. In this sense, Amazon was not merely a store, but an immense repository of facts. All we needed were the right equations to plug into them’.

James Marcus then goes on to give a fascinating insight into a breakout group discussion of how Amazon could better use measures to improve its performance. Marcus was in the Bezos group, brainstorming customer-centric metrics. Marcus (2004) summarises the dialogue, led by Bezos:

"First, we figure out which things we’d like to measure on the site", he said.

"For example, let’s say we want a metric for customer enjoyment. How could we calculate that?"

"There was silence. Then somebody ventured: "How much time each customer spends on the site?"

"Not specific enough", Jeff said.

"How about the average number of minutes each customer spends on the site per session" someone else suggested. "If that goes up, they’re having a blast".

"But how do we factor in the purchase?" I [Marcus] said feeling proud of myself.

"Is that a measure of enjoyment"?

"I think we need to consider the frequency of visits, too", said a dark-haired woman I didn’t recognize.

“Lot of folks are still accessing the web with those creepy-crawly modems. Four short visits from them might be just as good as one visit from a guy with a T-1. Maybe better’.

"Good point", Jeff said. "And anyway, enjoyment is just the start. In the end, we should be measuring customer ecstasy"

It is interesting that Amazon was having this debate about the elements of RFM analysis (described in Chapter 6 of Internet Marketing), 1997, after already having achieved $16 million of revenue in the previous year. Of course, this is a minuscule amount compared with today’s billions of dollar turnover. The important point was that this was the start of a focus on metrics which can be seen through the description of Matt Pounds work later in this case study.

Amazon marketing strategy experiments!

Amazon have created their own internal experimentation platform called a “Weblab” that they use to evaluate improvements to our websites and products. In 2013, they ran 1,976 Weblabs worldwide, up from 1,092 in 2012, and 546 in 2011. Now many companies use AB testing, but this shows the scale of testing at Amazon.

One example of how these are applied is a new feature called “Ask an owner”.  From a product page, customers can ask any question related to the product, Amazon then route these questions to owners of the product who answer.

From human to software-based recommendations

Amazon marketing strategy has developed internal tools to support this ‘Culture of Metrics’. Marcus (2004) describes how the ‘Creator Metrics’ tool shows content creators how well their product listings and product copy are working. For each content editor such as Marcus, it retrieves all recently posted documents including articles, interviews, booklists and features. For each one it then gives a conversion rate to sale plus the number of page views, adds (added to basket) and repels (content requested, but the back button then used).

In time, the work of editorial reviewers such as Marcus was marginalised since Amazon found that the majority of visitors used the search tools rather than read editorial and they responded to the personalised recommendations as the matching technology improved (Marcus likens early recommendations techniques to ‘going shopping with the village idiot’).

Experimentation and testing at Amazon.com

The ‘Culture of Metrics’ also led to a test-driven approach to improving results at Amazon. Matt Round, speaking at E-metrics 2004 when he was director of personalisation at Amazon describes the philosophy as ‘Data Trumps Intuitions’. He explained how Amazon used to have a lot of arguments about which content and promotion should go on the all important home page or category pages. He described how every category VP wanted top-center and how the Friday meetings about placements for next week were getting ‘too long, too loud, and lacked performance data’.

But today ‘automation replaces intuitions’ and real-time experimentation tests are always run to answer these questions since actual consumer behaviour is the best way to decide upon tactics.

Marcus (2004) also notes that Amazon has a culture of experiments of which A/B tests are key components. Examples where A/B tests are used include new home page design, moving features around the page, different algorithms for recommendations, changing search relevance rankings. These involve testing a new treatment against a previous control for a limited time of a few days or a week. The system will randomly show one or more treatments to visitors and measure a range of parameters such as units sold and revenue by category (and total), session time, session length, etc. The new features will usually be launched if the desired metrics are statistically significantly better.

Statistical tests are a challenge though as distributions are not normal (they have a large mass at zero for example of no purchase) There are other challenges since multiple A/B tests are running every day and A/B tests may overlap and so conflict. There are also longer-term effects where some features are ‘cool’ for the first two weeks and the opposite effect where changing navigation may degrade performance temporarily. Amazon also finds that as its users evolve in their online experience the way they act online has changed. This means that Amazon has to constantly test and evolve its features.

With the latest announcement from Google to sunset their Google Optimize A/B testing , digital marketers will do well to look out for new technology to assist in their testing efforts. We'll keep our members updated with announcements

Amazon.com technology marketing strategy

It follows that the Amazon technology infrastructure must readily support this culture of experimentation and this can be difficult to achieved with standardised content management. Amazon has achieved its competitive advantage through developing its technology internally and with a significant investment in this which may not be available to other organisations without the right focus on the online channels.

As Amazon explains in SEC (2005) ‘using primarily our own proprietary technologies, as well as technology licensed from third parties, we have implemented numerous features and functionality that simplify and improve the customer shopping experience, enable third parties to sell on our platform, and facilitate our fulfillment and customer service operations. Our current strategy is to focus our development efforts on continuous innovation by creating and enhancing the specialized, proprietary software that is unique to our business, and to license or acquire commercially-developed technology for other applications where available and appropriate. We continually invest in several areas of technology, including our seller platform; A9.com, our wholly-owned subsidiary focused on search technology on www.A9.com and other Amazon sites; web services; and digital initiatives.’

Round (2004) describes the technology approach as ‘distributed development and deployment’. Pages such as the home page have a number of content ‘pods’ or ‘slots’ which call web services for features. This makes it relatively easy to change the content in these pods and even change the location of the pods on-screen. Amazon uses a flowable or fluid page design unlike many sites which enables it to make the most of real-estate on-screen.

Technology also supports more standard e-retail facilities. SEC (2005) states: ‘We use a set of applications for accepting and validating customer orders, placing and tracking orders with suppliers, managing and assigning inventory to customer orders, and ensuring proper shipment of products to customers. Our transaction-processing systems handle millions of items, a number of different status inquiries, multiple shipping addresses, gift-wrapping requests, and multiple shipment methods. These systems allow the customer to choose whether to receive single or several shipments based on availability and to track the progress of each order. These applications also manage the process of accepting, authorizing, and charging customer credit cards.’

Data-driven Automation

Round (2004) said that ‘Data is king at Amazon’. He gave many examples of data driven automation including customer channel preferences; managing the way content is displayed to different user types such as new releases and top-sellers, merchandising and recommendation (showing related products and promotions) and also advertising through paid search (automatic ad generation and bidding).

The automated search advertising and bidding system for paid search has had a big impact at Amazon. Sponsored links initially done by humans, but this was unsustainable due to range of products at Amazon. The automated programme generates keywords, writes ad creative, determines best landing page, manages bids, measure conversion rates, profit per converted visitor and updates bids. Again the problem of volume is there, Matt Round described how the book ‘How to Make Love Like a Porn Star’ by Jenna Jameson received tens of thousands of clicks from pornography-related searches, but few actually purchased the book. So the update cycle must be quick to avoid large losses.

There is also an automated email measurement and optimization system. The campaign calendar used to be manually managed with relatively weak measurement and it was costly to schedule and use. A new system:

• Automatically optimizes content to improve customer experience
• Avoids sending an e-mail campaign that has low clickthrough or high unsubscribe rate
• Includes inbox management (avoid sending multiple emails/week)
• Has growing library of automated email programs covering new releases and recommendations

But there are challenges if promotions are too successful if inventory isn’t available.

Your Recommendations

Customers Who Bought X…, also bought Y is Amazon’s signature feature. Round (2004) describes how Amazon relies on acquiring and then crunching a massive amount of data. Every purchase, every page viewed and every search is recorded. So there are now to new version, customers who shopped for X also shopped for… and Customers who searched for X also bought… They also have a system codenamed ‘Goldbox’ which is a cross-sell and awareness raising tool. Items are discounted to encourage purchases in new categories!

See the original more detailed PDF article on Amazon personalization / recommendation collaborative filtering system .

He also describes the challenge of techniques for sifting patterns from noise (sensitivity filtering) and clothing and toy catalogues change frequently so recommendations become out of date. The main challenges though are the massive data size arising from millions of customers, millions of items and recommendations made in real time.

Amazon marketing strategy for partnerships

As Amazon grew, its share price growth enabled partnership or acquisition with a range of companies in different sectors. Marcus (2004) describes how Amazon partnered with Drugstore.com (pharmacy), Living.com (furniture), Pets.com (pet supplies), Wineshopper.com (wines), HomeGrocer.com (groceries), Sothebys.com (auctions) and Kozmo.com (urban home delivery). In most cases, Amazon purchased an equity stake in these partners, so that it would share in their prosperity. It also charged them fees for placements on the Amazon site to promote and drive traffic to their sites.

Similarly, Amazon marketing strategy was to charge publishers for prime-position to promote books on its site which caused an initial hue-and-cry, but this abated when it was realised that paying for prominent placements was widespread in traditional booksellers and supermarkets. Many of these new online companies failed in 1999 and 2000, but Amazon had covered the potential for growth and was not pulled down by these partners, even though for some such as Pets.com it had an investment of 50%.

Analysts sometimes refer to ‘Amazoning a sector’ meaning that one company becomes dominant in an online sector such as book retail such that it becomes very difficult for others to achieve market share. In addition to developing, communicating and delivering a very strong proposition, Amazon has been able to consolidate its strength in different sectors through its partnership arrangements and through using technology to facilitate product promotion and distribution via these partnerships. The Amazon retail platform enables other retailers to sell products online using the Amazon user interface and infrastructure through their ‘Syndicated Stores’ programme.

For example, in the UK, Waterstones (www.waterstones.co.uk) is one of the largest traditional bookstores. It found competition with online so expensive and challenging, that eventually it entered a partnership arrangement where Amazon markets and distributes its books online in return for a commission online. Similarly, in the US, Borders a large book retailer uses the Amazon merchant platform for distributing its products.

Toy retailer Toys R’ Us have a similar arrangement. Such partnerships help Amazon extends its reach into the customer-base of other suppliers, and of course, customers who buy in one category such as books can be encouraged to purchase into other areas such as clothing or electronics.

Another form of partnership referred to above is the Amazon Marketplace which enables Amazon customers and other retailers to sell their new and used books and other goods alongside the regular retail listings. A similar partnership approach is the Amazon ‘Merchants@’ program which enables third party merchants (typically larger than those who sell via the Amazon Marketplace) to sell their products via Amazon. Amazon earn fees either through fixed fees or sales commissions per-unit. This arrangement can help customers who get a wider choice of products from a range of suppliers with the convenience of purchasing them through a single checkout process.

Finally, Amazon marketing strategy has also facilitated formation of partnerships with smaller companies through its affiliates programme. Internet legend records that Jeff Bezos, the creator of Amazon was chatting to someone at a cocktail party who wanted to sell books about divorce via her web site. Subsequently, Amazon.com launched its Associates Program in July 1996 and it is still going strong.

Here, the Amazon marketing strategy has created a tiered performance-based incentives to encourage affiliates to sell more Amazon products.

Amazon Marketing strategy communications

In their SEC filings Amazon state that the aims of their communications strategy are (unsurprisingly) to:

• Increase customer traffic to our websites
• Create awareness of our products and services
• Promote repeat purchases
• Develop incremental product and service revenue opportunities
• Strengthen and broaden the Amazon.com brand name.

Amazon also believes that its most effective marketing communications are a consequence of their focus on continuously improving the customer experience. This then creates word-of-mouth promotion which is effective in acquiring new customers and may also encourage repeat customer visits.

As well as this Marcus (2004) describes how Amazon used the personalisation enabled through technology to reach out to a difficult to reach market which Bezos originally called ‘the hard middle’. Bezos’s view was that it was easy to reach 10 people (you called them on the phone) or the ten million people who bought the most popular products (you placed a superbowl ad), but more difficult to reach those in between. The search facilities in the search engine and on the Amazon site, together with its product recommendation features meant that Amazon could connect its products with the interests of these people.

Online advertising techniques include paid search marketing, interactive ads on portals, e-mail campaigns and search engine optimisation. These are automated as far as possible as described earlier in the case study. As previously mentioned, the affiliate programme is also important in driving visitors to Amazon and Amazon offers a wide range of methods of linking to its site to help improve conversion.

For example, affiliates can use straight text links leading direct to a product page and they also offer a range of dynamic banners which feature different content such as books about Internet marketing or a search box. Amazon also use cooperative advertising arrangements, better known as ‘contra-deals’ with some vendors and other third parties. For example, a print advertisement in 2005 for a particular product such as a wireless router with a free wireless laptop card promotion will feature a specific Amazon URL in the ad. In product fulfilment packs, Amazon may include a leaflet for a non-competing online company such as Figleaves.com (lingerie) or Expedia (travel). In return, Amazon leaflets may be included in customer communications from the partner brands.

Our Associates program directs customers to our websites by enabling independent websites to make millions of products available to their audiences with fulfillment performed by us or third parties. We pay commissions to hundreds of thousands of participants in our Associates program when their customer referrals result in product sales.

In addition, we offer everyday free shipping options worldwide and recently announced Amazon.com Prime in the U.S., our first membership program in which members receive free two-day shipping and discounted overnight shipping. Although marketing expenses do not include the costs of our free shipping or promotional offers, we view such offers as effective marketing tools.

Marcus, J. (2004) Amazonia. Five years at the epicentre of the dot-com juggernaut, The New Press, New York, NY.

Round, M. (2004) Presentation to E-metrics, London, May 2005. www.emetrics.org.

By Dave Chaffey

Digital strategist Dr Dave Chaffey is co-founder and Content Director of online marketing training platform and publisher Smart Insights. 'Dr Dave' is known for his strategic, but practical, data-driven advice. He has trained and consulted with many business of all sizes in most sectors. These include large international B2B and B2C brands including 3M, BP, Barclaycard, Dell, Confused.com, HSBC, Mercedes-Benz, Microsoft, M&G Investment, Rentokil Initial, O2, Royal Canin (Mars Group) plus many smaller businesses. Dave is editor of the templates, guides and courses in our digital marketing resource library used by our Business members to plan, manage and optimize their marketing. Free members can access our free sample templates here . Dave is also keynote speaker, trainer and consultant who is author of 5 bestselling books on digital marketing including Digital Marketing Excellence and Digital Marketing: Strategy, Implementation and Practice . In 2004 he was recognised by the Chartered Institute of Marketing as one of 50 marketing ‘gurus’ worldwide who have helped shape the future of marketing. My personal site, DaveChaffey.com, lists my latest Digital marketing and E-commerce books and support materials including a digital marketing glossary . Please connect on LinkedIn to receive updates or ask me a question .

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Lessons from Amazon’s Early Growth Strategy

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So much has been written about Amazon’s outsized growth. But Harvard Business School professor Sunil Gupta says it’s the company’s unusual approach to strategy that has captured his scholarly attention. Gupta has spent years studying Amazon’s strategy and its founder and former CEO Jeff Bezos.

In this episode, Gupta shares how Amazon upended traditional corporate strategy by diversifying into multiple products serving many end users, instead of having a narrow focus.

He argues that some of Amazon’s simplest business strategies — like their obsession with customers and insistence on long-term thinking — are approaches that companies, big and small, can emulate.

Key episode topics include: strategy, innovation, leadership, scaling, Jeff Bezos, long-term thinking, customer focus.

HBR On Strategy curates the best case studies and conversations with the world’s top business and management experts, to help you unlock new ways of doing business. New episodes every week.

• Listen to the full HBR IdeaCast episode: How Jeff Bezos Built One of the World’s Most Valuable Companies (2020)
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HANNAH BATES: Welcome to HBR On Strategy , case studies and conversations with the world’s top business and management experts, hand-selected to help you unlock new ways of doing business.

So much has been written about Amazon’s outsized growth. But Harvard Business School professor Sunil Gupta says it’s the company’s unusual approach to strategy that has captured his scholarly attention.

Gupta has spent years studying Amazon’s strategy and its founder and former CEO, Jeff Bezos.

In this episode, Gupta shares how Amazon upended traditional corporate strategy by diversifying into multiple products serving many end users instead of focusing more narrowly.

And he argues that some of their simplest business strategies – like their obsession with the customer and insistence on long-term thinking – are approaches that companies, big and small, should emulate.

If you’re interested in innovation strategy, this episode is for you. It originally aired on HBR IdeaCast in November 2020. Here it is.

ALISON BEARD:  Welcome to the HBR IdeaCast from Harvard Business Review.  I’m Alison Beard.

If you had to name the most successful business leader alive today, who would you say?  I can’t hear you from my basement podcasting room, but I would bet that for many of you, the answer is Jeff Bezos, CEO of Amazon.  This is a man who over the past 25 years turned his online bookstore startup into a diversified company currently valued at $1.6 trillion.

Amazon is a digital retailing juggernaut, it’s also a web services provider, media producer, and manufacturer of personal technology devices like Kindle and Echo.  Oh, and Bezos also owns the Washington Post and Blue Origin, a space exploration company.  Forbes tells us he is the richest person in the world.

How did he accomplish so much?  How did he change the business landscape?  What mistakes has he made along the way?  A new collection of Bezos’s own writing, which full disclosure, my colleagues at Harvard Business Review Press have published, offer some insights.  Here’s a clip from one speech that’s included.  The book is called Invent and Wander.

And our guest today, who has spent years studying both Amazon and Bezos, is here to talk with me about some of the key themes in it, including the broad drivers of both the company and the CEO’s success.  Sunil Gupta is a professor of business administration at Harvard Business School and cochair of its executive program, and cochair of its executive program on driving digital strategy, which is also the title of his book.  Sunil, thanks so much for being on the show.

SUNIL GUPTA:  Thank you for having me, Alison.

ALISON BEARD:  So Invent and Wander.  I get that Bezos is inventive.  You know, he created a new way for us to buy things – everything.  How is he also a wonderer?

SUNIL GUPTA:  So he’s full of experiments.  His company and his whole style is known for experimentation, and he says that in so many words that if you want big winners, then you have to be willing to have many failures.  And the argument is, one big winner will take care of a thousand failed experiments.  So I think that’s the wandering part.  But also his experiments are not aimless.  There is a certain thought and process behind what experiments to do and why they will connect to the old, old picture of what Amazon is today.

ALISON BEARD:  And your expertise is in digital strategy.  How does he break the traditional rules of strategy?

SUNIL GUPTA:  So for the longest time the way, at least I was taught in my MBA program and the way we teach to our MBA students and executives, is strategy is about focus.  But if you look at Amazon, Amazon certainly doesn’t look like it’s focusing on anything, so obviously Jeff Bezos missed that class, otherwise it’s a very, very different thing.

And then you’d say, why is it that so called lack of focus strategy seems to be working for Amazon?  And I think the fundamental underlying principle that he’s guiding his whole discussion of strategy is, he’s changed the rules of strategy.  So the old rules of strategy were, the way you gained competitive advantage is by being better or cheaper.  So if I am selling you a car, my car is better of cheaper.  But the inherent assumption in that strategy statement is, I’m selling one product to one customer.  And what Amazon is basically arguing is, the digital economy is all about connection.  We have got to connect products and connect customers.  Let me explain why that is so powerful.

So connecting products, here the idea is, I can sell you, this is a classic razor and blade strategy.  I can sell you a razor cheap in order to make money on the blade.  So I can sell you Kindle cheap in order to make money on the ebooks.  Now, at some level you might say, hey, razor and blade have been around forever.  What’s so unique today?  I think unique today is razor could be in one industry and blades could be in completely different industrys.

So for example, if you look at Amazon’s portfolio of businesses, you sort of say, not only Amazon is an e-commerce player, but also is making movies and TV shows, its own studio.  Well, why does it make sense for an e-commerce player, an online retailer to compete with Hollywood.  Well, Walmart doesn’t make movies.  Macy’s doesn’t make movies?  So why does it make sense for Amazon to make movies?

And I think once you dig into it, the answer becomes clear that the purpose of the movies is to keep and gain the Prime customers. Two day free shipping is fine, but if  you ask me to pay $99 or $119 for two day free shipping, I might start doing the math in my head, and say, OK, how many packages do I expect to get next year?  And is the Prime membership worth it or not?

But once you throw in, in addition to the two-day free shipping, you throw in some TV shows and movies that are uniquely found only on Amazon, I can’t do this math.  And why is Prime customers important to Amazon?  Because Prime customers are more loyal.  They buy three or four times more than the non-Prime customers, and they’re also less price sensitive.

And in fact, Jeff Bezos has said publicly that every time we win a Golden Globe Award for one of our shows, we sell more shoes.  So this is, and he said it in your book, Invent and Wander, also, that we might be the only company in the world which has figured out how winning Golden Globe Awards can actually translate into selling more products on the online commerce.

So this is a great example of the razor being in a very different industry and blade being in another industry.  Take another example.  Amazon has a lending business where they give loans to small and medium enterprises. If Amazon decides to compete with banks tomorrow, Amazon can decide to offer loans to the small merchants at such a low price that banks would never be able to compete.  And why would Amazon be able to do that?  Because Amazon can say, hey, I’m not going to make money on loans, as much money on loans, but I’ll make more money when these businesses, small businesses grow and do more transactions on my marketplace platform.  And I get more commissions.  So again, loan can become my razor in order to help the merchants grow and make money on the transaction and the commission that I get from that.  The moment I make somebody else’s, in this case the banks, core business my razor, they will make a very hard time competing.  So I think that’s the key change, the fundamental rules of strategy and competition in that direction.

The second part of connection is connecting customers, and this is the classic network effect.  So marketplace is a great example of network effects.  The more buyers I have, the more sellers I have.  The more sellers I have, the sellers I have, the more buyers I get, because the buyers can find all the items.  And that becomes flywheel effect, and it becomes a situation where it’s very hard for a new player to complete with Amazon.

ALISON BEARD:  In this diversification that Amazon has done, how have they managed to be good at all of those things?  Because they’re not focused.  You know, they’re not concentrated on an area of specific expertise.  So how have they succeeded when other companies might have failed because they lacked that expertise, or they were spreading themselves too thin?

SUNIL GUPTA:  So I think it depends on how you define focus.  Most of us, when we define focus, we sort of define focus by traditional industry boundaries, that I’m an online retailer, therefore going into some other business is lack of focus.  The way Amazon thinks about is focus on capabilities.

So if you look at it from that point of view, I would argue that Amazon had three fundamental core capabilities.  Number one, it’s highly customer focused, not only in its culture, but also in its capability in terms of how it can actually handle data and leverage data to get customer insight.  The second core capability of Amazon is logistics.  So it’s now a world class logistics player.  It uses really frontier technology, whether it’s key word, robotics, computer vision, in its warehouse to make it much more efficient.

And the third part of Amazon’s skill or the capability is its technology.  And a good example of that is Amazon Web Services, or AWS.  And I think if you look at these three core capabilities, customer focus and the data insight that it gets from that, the logistics capability, and the technology, everything that Amazon is doing is some way or the other connected to it.  In that sense, Amazon, and there’s no lack of focus, in my judgment on Amazon.

Now, if he starts doing, starts making cream cheese tomorrow or starts making airplane engines, then I would say, yes, it’s got a lack of focus.  But one of the other things that Jeff Bezos has said again and again is this notion of work backwards and scale forward.  And what that means is, because you’re customer obsessed, you sort of find ways to satisfy customers, and if that means developing new skills that we don’t have because we are working backwards from what the customer needs are, then we’ll build those skills.

So a good example of that is, when Amazon started building Kindle, Amazon was never in the hardware business.  It didn’t know how to build hardware.  But Bezos realized that as the industry moved, people are beginning to read more and more online, rather, or at least on their devices, rather than the physical paper copy of a book.  So as a result, he says, how do we make it easier for consumers to read it on an electronic version?  And they’re spending three years learning about this capability of hardware manufacturing.  And by the way, Kindle came out long before iPad came out.  And of course, that capability now has helped them launch Echo and many other devices.

ALISON BEARD:  Right.  So it’s the focus on the customer, plus a willingness to go outside your comfort zone, the wander part.

SUNIL GUPTA:  Exactly.

ALISON BEARD:  Yeah.  How would you describe Bezos’s leadership style?

SUNIL GUPTA:  So I think there are at least three parts to it.  One is, he said right from day one that he wants to be a long-term focus.  The second thing is being customer obsessed.  And many times he has said that he can imagine, in the meetings he wants people to imagine an empty chair.  That is basically for the customer. And he says, we are not competitor focused.  We are not product focused.  We are not technology focused.  We are customer focused.  And the third is, willingness to experiment.  And fail, and build that culture in the company that it’s OK to fail.

ALISON BEARD:  What about personally, though?  Is he a hard charger?  Is he an active listener?  What’s it like to be in a room with him?

SUNIL GUPTA:  Oh, he’s certainly a hard charger.  I mean, he’s also the kind of guy, when he hires people, he says, you can work long, hard, or smart.  But at Amazon, you can choose two out of three.  And I think this is similar to many other leaders.  If you look at Steve Jobs, he was also a very hard charging guy.  And I think some people find it exhilarating to work with these kind of leaders.  Some find it very tough.

ALISON BEARD:  Do you think that he communicates differently from other successful CEOs?

SUNIL GUPTA:  So the communication style that he has built in the company is the very famous now, there’s no PowerPoints.  So it’s a very thoughtful discussion.  You write six-page memos, which everybody, when their meeting starts, everybody sits down and actually reads the memo.

In fact, this was a very interesting experience that I had.  One of my students, who was in the executive program, works at Amazon in Germany.  And he is, he was at that point in time thinking of moving to another company and becoming a CEO of that company.  So he said, can I talk to you about this change of career path that I’m thinking about?  I said, sure.  So we set up a time, and five minutes before our call, he sends me an email with a six-page memo.  And I said, well, shouldn’t he have sent this to me before, so I could at least look at it?  He says, no, that’s the Amazon style.  We’ll sit in silence and read it together.  And so I read it together, because then you’re completely focused on it.  And then we can have a conversation.  But this discipline of writing a six-page memo, it’s a very, very unique experience, because you actually have to think through all your arguments.

ALISON BEARD:  You also mentioned the long term focus, and that really stood out for me, too, this idea that he is not at all thinking of next year.  He’s thinking five years out, and sometimes even further.  But as a public company, how has Amazon been able to stick to that?  And is it replicable at other companies?

SUNIL GUPTA:  I think it is replicable.  It requires conviction, and it requires a way to articulate the vision to Wall Street that they can rally behind.  And it’s completely replicable.  There are other examples of companies who have followed a similar strategy.  I mean, Netflix is a good example.  Netflix hadn’t made money for a long period of time.  But they sold the vision of what the future will look like, and Wall Street bought that vision.

Mastercard is exactly the same thing.  Ajay Banga is giving three year guidance to Wall Street saying, this is my three-year plan, because things can change quarter to quarter.  I’m still responsible to tell you what we are doing this quarter, but my strategy will not be guided by what happens today.  It will be guided by the three-year plan that we have.

ALISON BEARD:  There are so many companies now that go public without turning any profit, whereas Amazon now is printing money, and thus able to reinvest and have this grand vision.  So at what point was Bezos able to say, right, we’re going to do it my way?

SUNIL GUPTA:  I think he said it right from day one, except that people probably didn’t believe it.  And in fact, one of the great examples of that was, when he was convinced about AWS, the Amazon Web Services, that was back in the early 2000s, when a majority of the Wall Street was not sure what Jeff Bezos was trying to do, because they say, hey, you are an online retailer.  You have no business being in web services.  That’s the business of IBM.  And that’s a B2B business.  You’re in a B2C business.  Why are you going in there?

And Bezos said, well, we have plenty of practice of being misunderstood.  And we will continue with our passion and vision, because we see the path.  And now he’s proven it again and again why his vision is correct, and I think that could give us more faith and conviction to the Wall Street investors.

SUNIL GUPTA:  Oh, absolutely.  And he’s one of the persons who has his opinion, and you always surround yourself with people better than you.

ALISON BEARD:  How has he managed to attract that talent when it is so fiercely competitive between Google, Facebook, all of these U.S. technology leaders?

SUNIL GUPTA:  So a couple of things I would say.  First of all, it’s always good fun to join a winning team.  And all of us want to join a winning team, so this certainly is on a trajectory which is phenomenal.  It’s like a rocket ship that is taking off and has been taking off for the last 25 years.  So I think that’s certainly attractive to many people, and certainly many hard charging people who want to be on a winning team.

And a second thing is, Amazon’s culture of experimentation and innovation.  That is energizing to a lot of people.  It’s not a bureaucracy where you get bogged down by the processes.  So the two type of decisions that we talked about, he gives you enough leeway to try different things, and is willing to invest hundreds of millions of dollars into things that may or may not succeed in the future.  And I think that’s very liberating to people who are willing to take on the ownership and build something.

ALISON BEARD:  But don’t all of the tech companies offer that?

SUNIL GUPTA:  They do, but if you think about many other tech companies, they’re much more narrow in focus.  So Facebook is primarily in social media.  Google is primarily in search advertising.  Yes, you have GoogleX, but that’s still a small part of what Google does.  Whereas if you ask yourself what business is Amazon in, there are much broader expansive areas that Amazon has gone into.  So I think the limits, I mean, Amazon does not have that many limits or boundaries as compared to many other businesses in Silicon Valley.

ALISON BEARD:  So let’s talk a little bit about Bezos’s acquisition strategy.  I think the most prominent is probably Whole Foods, but there are many others.  How does he think about the companies that he wants to bring in as opposed to grow organically?

SUNIL GUPTA:  So some acquisitions are areas where he thinks that he can actually benefit and accelerate the vision that he already has.  So for example, the acquisition of Kiva was to improve the efficiency and effectiveness of the systems that he already put in place in his warehouse.  And logistics and warehouse is a key component or key part of Amazon’s business, and he saw that Kiva already was ahead of the curve in technology that he probably wanted to have that in his own company.  So that was obvious acquisition, because that fits in the existing business.

Whole Foods is kind of a slightly different story, in my judgment, because I some ways, you can argue, why is Amazon, an online player, buying an offline retail store, Whole Foods?  And in fact, they bought it at 27% premium.  So that doesn’t make sense for an online retailer commerce to go to offline channels.  And I think, in fact, part of the reason in my judgment is, it’s not just Whole Foods, but it’s about the food business, per se.  And why is Amazon so interested in food?  In fact, Amazon has been trying this food business, online food delivery for a long period of time without much success.  And Whole Foods was one, another way to try and get access to that particular business.  And why is that so important to Amazon, even though you could argue, food is a low margin business?

And I would say, part of the reason is, food is something, grocery is something that you buy every week, perhaps twice a week.  And if I, as Amazon, can convince you to buy grocery online from Amazon, then I’m creating a habit for you to come onto Amazon every week, perhaps twice a week.  And once you are on Amazon, you will end up buying other products on Amazon.  Whereas if you are buying electronics, you may not come to Amazon every day.

So this is a habit creation activity, and again, it may not be a very high margin activity to sell you food.  But I’ve created a habit, just like Prime.  I’ve created a loyal customer where you think of nothing else but Amazon for your daily needs, and therefore you end up buying other things.

ALISON BEARD:  And Amazon isn’t without controversy.  You know, and we should talk about that, too.  First, there are questions about its treatment of warehouse employees, particularly during COVID.  And Bezos, as you said, has always been relentlessly focused on the customer.  But is Amazon employee centric, too?

SUNIL GUPTA:  So I think there is definitely some areas of concern, and you rightly said there is a significant concern about the, during the COVID, workers were complaining about safety, the right kind of equipment.  But even before COVID, there were a lot of concerns about whether the workers are being pushed too hard.  They barely have any breaks.  And they’re constantly on the go, because speed and efficiency become that much more important to make sure customers always get what they are promised.  And in fact, more than promised.

Clearly Amazon either hasn’t done a good job, or hasn’t at least done the public relations part of it that they have done a good job.  Now, if you ask Jeff Bezos, he will claim that, no, actually, they have done things.  For example, they offer something called carrier choice, where they give 95% tuition to the employees to learn new skills, whether they’re relevant to Amazon or not.  Pretty much like what Starbucks does for its baristas, for college education and other things.  But I think more than just giving money or tuition, it requires a bit of empathy and sense that you care for your employees, and perhaps that needs, that’s something that Amazon needs to work on.

ALISON BEARD:  And another challenge is the criticism that it has decimated mom and pop shops.  Even when someone sells through Amazon, the company will then see that it’s a popular category and create it itself and start selling it itself.  There’s environmental concerns about the fact that packages are being driven from warehouses to front doors all over America.  And boxes and packaging.  So how has Bezos, how has the company dealt with all of that criticism?

SUNIL GUPTA:  They haven’t.  And I think those are absolutely valid concerns on both counts, that the small sellers who grow to become reasonably big are always under the radar, and there are certainly anecdotal evidence there, small sellers have complained that Amazon had decided to sell exactly the same item that they were so successful in selling, and becoming too big is actually not good on Amazon, because Amazon can get into your business and wipe you away.  So that’s certainly a big concern, and I think that’s something that needs to be sorted out, and Amazon needs to clarify what its position on that area is, because it benefits from these small sellers on his platform.

And your second question about environmental issues is also absolutely on the money, because not only emission issues, but there’s so many boxes that pile in, certainly in my basement, from Amazon.  You sort of say, and it’s actually ironical that Millennials who are in love with Amazon are extremely environmentally friendly.  But at the same time, they would not hesitate to order something from Amazon and pile up all these boxes.  So I think Amazon needs to figure out a way to think about both those issues.

ALISON BEARD:  And at what point will it have to?  I mean, it seems to be rolling happily along.

SUNIL GUPTA:  Well, I think those issues are becoming bigger and bigger, and it’s certainly in the eye of the regulators, also, for some of these practices.  And not only because it’s too big, and there might be monopoly concerns, but these issues will become larger, and any time you become a large company, you become the center of attraction for broader issues than just providing shareholder value.

ALISON BEARD:  Yeah.  So those are weaknesses possibly for the company.  What are some of Bezos’s personal weaknesses that you’ve seen in studying him and the company?

SUNIL GUPTA:  So I think one thing that stands out to me, and at least in the public forums, I have not seen any empathy.  And it’s, I mean, we talk about that the leaders have, should have three qualities.  They should be competent.  They should have a good character.  And they should have compassion.  So he’s certainly very competent.  I mean, he’s brilliant in many aspects, right, from the computer vision and AI and machine learning, to the nuances of data analytics, to the Hollywood production, etc.  He also seems to have good character, at least I have not heard any personal scandals, apart from his other issues in his personal life, perhaps.

Those characteristics of competence and character make people respect you.  What makes people love you is when you show compassion, and at least I haven’t seen compassion or empathy that comes out of him.  I mean, he certainly comes across as a very hard charging, driven person, which probably is good for business.  But the question of empathy is perhaps something lacking right now.

ALISON BEARD:  Yeah.  The other issue is his just enormous wealth.  He did invent this colossally valuable company, but should anyone really be that rich?

SUNIL GUPTA:  Well, I guess that’s, you can say that’s the good or the bad thing about capitalism.  But I think, and again, my personal view is there’s nothing wrong in becoming rich, if you have been successful and done it with hard work and ingenuity.  But how you use your wealth is something that perhaps will define Jeff Bezos going forward.  I think Bill Gates is a great example how he actually has used his wealth and his influence and his expertise and his brilliance into some certain thing that actually is great for humanity.

Now, whether Jeff Bezos does that down the road, I don’t know, whether his space exploration provides that sort of outlet which is both his passion as well as good for humanity, I don’t know.  But at some point in time, I think it’s the responsibility of these leaders to sort of say, my goal is not simply to make money and make my shareholders rich, but also help humanity and help society.

ALISON BEARD:  If you’re talking to someone who’s running a startup, or even a manager of a team at a traditional company, what is the key lesson that you would say, this is what you can learn from Jeff Bezos?  This is what you can put to work in your own profession?

SUNIL GUPTA:  So I would say two things that at least I would take away if I were doing a startup.  One is customer obsession.  Now, every company says that, but honestly, not every company does it, because if you go to the management meetings, if you go to the quarterly meetings, you suddenly go focus on financials and competition and product.  But there’s rarely any conversation on customers.  And I think, as I mentioned earlier, that Jeff Bezos always tells his employee to think of the imaginary chair in which a customer is sitting, because that’s the person that we need to focus on.  Howard Shultz does the same thing at Starbucks, and that’s why Starbucks is so customer focused.

So I think that’s the first part.  And the argument that Bezos gives is, customers are never satisfied.  And that pushes us to innovate and move forward, so we need to innovate even before the rest of the world even sees that, because customers are the first ones to see what is missing in the offering that you have.

And the second I would say that I would take away from Jeff Bezos is the conviction and passion with what you do.  And many times that goes against the conventional wisdom.  And the Amazon Web Services is a great example of that.  The whole world, including the Wall Street Journal and the Wall Street analysts were saying, this is none of Amazon’s business to do web services.  But he was convinced that this is the right thing to do, and he went and did that.

And part of that conviction may come from experiments.  Part of that conviction comes from connecting the dots that he could see that many other people didn’t see.  I mean, that’s why he went, left his job, and went to Seattle to do the online bookstore, because he could see the macro trends as to what the Internet is likely to do.  So, I think that’s the vision that he had.  And once you have the conviction, then you follow your passion.

ALISON BEARD: Sunil, thanks so much for coming on the show.

SUNIL GUPTA:  Thank you for having me. Alison.

HANNAH BATES: That was Harvard Business School professor Sunil Gupta, in conversation with Alison Beard on the HBR IdeaCast .

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The Integration of Digital Business Models: The Amazon Case Study

• First Online: 21 May 2022

Cite this chapter

• Carlo Bagnoli 10 ,
• Andrea Albarelli 11 ,
• Stefano Biazzo   ORCID: orcid.org/0000-0003-3373-2964 12 ,
• Gianluca Biotto 13 ,
• Giuseppe Roberto Marseglia 14 ,
• Maurizio Massaro   ORCID: orcid.org/0000-0001-6461-2709 15 ,
• Matilde Messina 13 ,
• Antonella Muraro 16 &
• Luca Troiano 17  

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The final chapter involves the description of the Amazon case study. The intention is to reconnect the various categorizations illustrated in the previous chapter to a real-world example for the purpose of presenting a successful case of business disruption as Amazon is known to have disrupted retail. The analysis aims at highlighting the fact that Amazon combines all the business model frameworks described in the preceding chapters as well as investigating their coexistence within a single organization.

The present chapter also explains a few methodologies which have been developed in order to guide companies through the process of disrupting their existing business models and facilitating the shift towards an innovative framework. Digital technologies can ease the above-mentioned transition as firms are required to select the technological advancements enabling them to accomplish particular organizational goals.

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Bagnoli, C. et al. (2022). The Integration of Digital Business Models: The Amazon Case Study. In: Digital Business Models for Industry 4.0. Future of Business and Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-97284-4_4

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Amazon.com, Inc.: a case study analysis

This paper is a case study analysis of Amazon.com, Inc. (Amazon). In this paper, I look at the business strategy of Amazon. Special attention is given to five parts, including a historical overview, organizational structure, business operations, financial performance, and the future outlook of Amazon. The historical overview chronologically describes landmark events of Amazons beginnings to their current position today. The companies departmental structure is categorized and briefly commented on in section two. An analysis is provided for Amazons operations with a breakdown of major products and services offered. A comprehensive financial analysis of Amazon follows (section four) with matching insight that links performance to events and business strategies. The future outlook of Amazon is discussed last, offering a topical overview of where Amazons business interest is shifting.

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Amazon: Big Data Analysis Case Study

A big data analysis case study of amazon.

Akshay Gautam

Big data is one of the advanced technologies mainly used for evaluating and integrating the collected data in the companies. The use of big data is increasing, and many companies are using the key features of big data for improving the performance of businesses and developed systems. Amazon is one of the leading e-commerce organizations that provide various services and products to their consumers [1]. The essential purpose is to examine the significance of big data in Amazon and evaluate the critical aspects of big data in the context of the Amazon e-commerce industry. This article mainly focuses on the significant three sections: contemporary elements of big data, characteristics of data, and big data preparation.

Security Issues And Challenges

Amazon is the largest e-commerce industry that provides many services to their customers and big data in an effective technology used by Amazon to improve their performance and effectiveness of the data collection processes. Two significant aspects are selected from the contemporary sections, including security issues and challenges [5]. It is identified that big data can reduce complexity and errors from the business, and Amazon is using such kind of technology for improving their performance. Security is one of the significant issues associated with the big data approach used by Amazon. The criminals send unwanted signals to the central server and collect all reliable data [1]. A recent study identified that data security is challenging for the amazon because of unauthentic access present in the servers and computing networks.

However, three major risk factors are linked with big data that increase security-related issues in the Amazon industry, such as lack of security, utilization of unauthentic networks, and misconfiguration of servers. Therefore, it is stated that amazon should focus on security while using big data technology in their businesses. According to Bello, Jung, and Camacho (2016), there are various security issues and threats in big data technology, such as DDOS attacks, malware activities, fake data generation, data breach issues, and phishing attacks and so on [1]. DDOS and malware are pervasive security threats associated with big data, which directly impact the security of amazon and reduced the performance of computing networks used by amazon.

The previous investigation found that most criminals use unauthentic networks and malicious tools to produce a large number of traffic signals and networks. These signals transfer from one network to another and impact the privacy of data [6]. It is identified that big data uses internet connections and computing networks for performing data integration activities. Still, sometimes the users use third-party applications to obtain reliable data from consumers, which directly impact privacy and lead to cyber-security attacks. Moreover, it is argued that utilizing big data technology, controlling and managing data privacy is another challenge faced by amazon. According to Bowker (2014), misconfiguration of networks is a key issue that increases the chances of a data breach in Amazon. Developers cannot identify the key elements that produce challenges and risks in the workplace [2].

Controlling and managing the malware activities and signals from the IT systems used by Amazon is another challenge that helps the criminals enter into the main server and collect data of amazon without taking any permission. Moreover, there are several other challenges associated with the big data faced by the Amazon industry, for example, unauthentic access of networks, data integration, data protection issue, the confidentiality of data, monitoring fake data from the system, and so on. Therefore, it is argued that while using the key features of big data Amazon should focus on privacy-related concerns and develop the proper security plans for securing the collected data. Moreover, data integration-related issues can be solved by providing proper training and education to the employees and evaluating the effective data integration techniques while using big data analysis approaches [9].

Data Source and Data Format

From the aspects of data, there are two major factors selected, including data source and data format in the context of the Amazon e-commerce industry. It is argued that big data is an effective computing technology that can integrate both structured and unstructured data appropriately. A recent study identified that Amazon is now providing cloud-based services to the consumers by which the small business communities can enhance the performance of computing systems and networks. It is identified that data format is an essential part of the big data technology used by Amazon for evaluating the collected data from various resources [10].

Moreover, Amazon uses various file formats in their businesses, such as text files, sequences files, Avro data files, etc. With the help of big data technology, the data may be formatted effectively where amazon can reduce complexity from the systems and improve the performance of the networks. Such data formats help the developers collect data or facts from numerous sources and effectively evaluate each data using big data analysis approaches. According to Chen and Zhang (2014), big data can improve the performance of data integration processes and help amazon improve their productivity by monitoring data formats in an effective manner [3].

While using the big data analysis technique, Amazon can effectively evaluate semi-structured and unstructured data and reduce complexity from the system. While storing data in Hadoop, Amazon needs to identify the fake data generation and unwanted signals, which may directly impact the performance of the computing devices and servers. It is recognized that there are three major kinds of data file formats involved by amazon and big data technology, for example, optimized row columnar, Parquet, and Avro [11]. All these kinds of data formats can store data files of amazon and help the management for reducing data format-related issues and problems. In the big data process, files recorded in such kinds of data formats may be split across various disks and help the Amazon industry improve the scalability and availability of data.

All these data formats mainly carry the data in the computer files and provide a platform where amazon can easily effectively evaluate the collected data. The major issue with the data formats is that the management requires effective methods for storing reliable data into the data centers, producing complexity in the systems [12]. Mainly, amazon uses a column-oriented type of data format for storing and recording the data of consumers and employees. Still, it is suggested that the management include row-based storage systems while using big data technology because of their ability to reduce system errors.

It is argued that data source is a vital part of the big data that provide a platform where amazon can collect and evaluate the data related to the customers and stakeholders. Chong, Ch’ng, Liu and, Li (2017) identified that mainly amazon uses third-party applications and social media networking sites for obtaining the data related to the consumers and store in file formats using big data networks [4]. Moreover, AWS is one of the effective services provided by Amazon, which helps other small business communities. It is observed that big data technology helps amazon for collecting data in very little time. The management team uses various data sources, including Facebook, Twitter, online communities, data-driven systems, and other IT sources.

Social interaction is a common source used by Amazon and other e-commerce companies because it provides many data sets in very little time, including both structured and unstructured data [13]. In this modern era, most consumers are using social networks and applications while searching on the internet. Amazon uses social networks as a data source to collect huge amounts of data and then integrate using big data techniques. Conclusiseveral electronic files can be used as the data source in Amazon and help obtain reliable data, including information related to the consumers and stakeholders. Therefore, it is stated that the adopted data sources by Amazon help for getting effective and reliable data but sometimes the hackers produce fake data, which may create conflicts in the system and make errors in the extensive data analysis processes.

De-Normalization And Data Integration

There are numerous aspects of big data preparation, for example, de-normalization, data integration, aggregation, and data cleansing. In this research essay, de-normalization and data integration, both aspects, will be explained in the context of the Amazon e-commerce industry. The term normalization in big data is a kind of process that Amazon uses for normalizing and evaluating the collected data to enhance the business’s overall performance. Erevelles, Fukawa, and Swayne (2016) argued that de-normalization is defined as enhancing the read performance of the developed database and reducing errors from the systems [5]. It is observed that Amazon is a leading e-commerce industry that provides AWS services to consumers. The management requires a de-normalization process along with the big data for evaluating the previously obtained data sets.

Such kind of data preparation can enhance the performance of the data warehouse used by Amazon and provide a platform where the organization can store a large number of data sets. The major issue linked with de-normalization is that it may impact the performance of Amazon if the developed system does not work properly in the database systems [14]. Moreover, while developing and implementing such a process in the business, Amazon can produce an effective relationship between the data model and the query model. With the help of the de-normalization process, Amazon can easily reduce the integrity-related problem in big data systems. Still, it requires proper communication between the servers and data sets.

In the last few years, the management team of Amazon changed their database systems and included the key aspects of de-normalization for improving the effectiveness of the proposed systems. After reviewing the recent reports, it has been found that Amazon adopted big data technology and de-normalization process in the current systems that provided better platforms for reducing problems and complexity faced by the developers [15]. Lack of proper resources and communication between the networks and data sets may increase the rate of degradation, affecting the performance of developed systems.

Therefore, it is stated that while using de-normalization along with the big data, Amazon should ensure that they focus on the networks and issue of degradation and identify the risk factors which may produce breach and data loss-related issues. Hashem, et al. (2015) provided their views on big data and suggested that in the context of big data, the better option for data modeling is de-normalization which does not require more time and reduces the rate of waste time from the systems [6]. Because of such benefits, Amazon uses the key aspects of de-normalization and big data technology.

According to Kim, Trimi and Chung, (2014), the term data integration is a part of big data that combines business and technical processes for evaluating and integrating the stored data effectively [7]. Mainly, Amazon Company uses data integration approaches and big data for evaluating both unstructured and semi-structured data. Such a process offers enterprises related services to Amazon and helps scale the obtained data in various data sets by which management can easily store data effectively.

Recent literature identified that data integration provides a wide range of data quality abilities to Amazon. The management can monitor and improve the quality of collected data from various sources. Data integration is one of the best platforms where amazon and other business companies can integrate and evaluate a large number of data sets and monitor the effectiveness of the gathered data. With the help of big data, technology amazon is now performing data integration-related activities. Still, fake data generation is a key problem produced by criminals that cannot be solved easily, and amazon may suffer from the security-related issue. It is analyzed that big data integration plays a major role in the e-commerce industry, also used as a data protection tool in Amazon. Generally, such kind of process combines data originating and software formats. It then delivers consumers with an undefined view of the accumulated data, which may produce problems in the Amazon industry.

Controlling and managing the integration of data is a complex step for amazon because it requires better decisions making approaches and reliable systems that evaluate the collected data inappropriately. According to Kiran, Murphy, Monga, Dugan, and Baveja (2015), Amazon faces various kinds of challenges while using the data integration process and the big data. These challenges include data uncertainty, finding insights, availability of data, and syncing across data resources [8]. Uncertainty of data is a major problem that directly impacts the databases and systems used by Amazon. Most criminals send unauthentic networks and fake data to Amazon to enter into the data sets and collect all consumers’ sensitive data.

Therefore, it is stated that de-normalization and data integration are effective data preparation aspects used by Amazon, which help evaluate the reliable and effective data sets from data sources.

After reviewing big data aspects in the context of Amazon, it is concluded that big data is an effective technology that improved the performance of amazon and monitored a large amount of data in very little time. This study critically reviewed the role of big data aspects and networks in the Amazon e-commerce industry. It highlighted the security issues associated with big data and amazon networks. It is identified that DDOS and malware are widespread security threats that occurred in big data techniques, which impact the personal data of amazon and their performance. While using the key aspects of big data Amazon can enhance its performance and evaluate both unstructured and semi-structured data effectively. Still, it requires advanced computing networks and large space for storing data of consumers.

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[2]. G.C., Bowker, “Big data, big questions| the theory/data thing,” International Journal of Communication , vol. 8, no. 7, p.5, 2014.

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[5]. S., Erevelles, N. Fukawa and, L., Swayne, “Big Data consumer analytics and the transformation of marketing,” Journal of Business Research , vol. 69, no. 2, pp.897–904, 2016.

[6]. I.A.T., Hashem, I., Yaqoob, N.B., Anuar, S., Mokhtar, A. Gani and, S.U., Khan, “The rise of “big data” on cloud computing: Review and open research issues,” Information systems , vol. 47, no. 7, pp.98–115, 2015.

[7]. G.H., Kim, S. Trimi and, J.H., Chung, “Big-data applications in the government sector,” Communications of the ACM , vol. 57, no. 3, pp.78–85, 2014.

[8]. M., Kiran, P., Murphy, I., Monga, J. Dugan and, S.S., Baveja, “Lambda architecture for cost-effective batch and speed big data processing,” In 2015 IEEE International Conference on Big Data (Big Data) , vol. 7, no. 6, pp. 2785–2792, 2015.

[9]. G., Manogaran, C. Thota and, M.V., Kumar, “MetaCloudDataStorage architecture for big data security in cloud computing,” Procedia Computer Science , vol. 87, no. 7, pp.128–133, 2016.

[10]. G., Manogaran, R., Varatharajan, D., Lopez, P.M., Kumar, R. Sundarasekar and, C., Thota, “A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system,” Future Generation Computer Systems , vol. 82, no. 6, pp.375–387, 2018.

[11]. M.J. Mazzei and, D., Noble, “Big data dreams: A framework for corporate strategy,” Business Horizons , vol. 60, no. 3, pp.405–414, 2017.

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[13]. H., Özköse, E.S. Arı and, C., Gencer, “Yesterday, today and tomorrow of big data,” Procedia-Social and Behavioral Sciences , vol. 195, no. 7, pp.1042–1050, 2015.

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Amazon’s Organizational Culture Characteristics (An Analysis)

Amazon has an organizational culture that enables business capacity for responding to opportunities in the e-commerce market. A company’s organizational or corporate culture sets the traditions and values that influence employees’ behaviors. For example, Amazon’s corporate culture pushes employees to go beyond traditional limits and conventions to develop bright ideas and solutions. As the world’s top-performing online retailer, the company continues to seek fresh talent. However, to maintain a capable workforce, Amazon must reinforce its organizational culture to shape the development of human resources for long-term competitive advantage. The business culture facilitates knowledge-sharing to keep the technology company’s human resources competitive in the face of rapid innovation in the industry.

Amazon’s organizational culture is seen as a critical factor in the success of the online retail business. The corresponding cultural characteristics define the capabilities of Amazon’s human resources and, in turn, the e-commerce organization. This link to business capability indicates that the company culture reinforces the competitive advantages described in the SWOT analysis of Amazon . Through its influence on the workforce, the business culture keeps the company competitive against other technology firms, like Google (Alphabet) , Apple , and Microsoft , as well as retailers, such as Walmart and Costco . Thus, Amazon’s work culture supports market positioning, competitive advantages, and financial performance.

Features of Amazon’s Organizational Culture

Amazon is known for a corporate culture that pushes employees to explore ideas and take risks. This cultural condition is responsible for the company’s capacity to seek new opportunities to utilize data-intensive processes to provide efficient online services. Amazon states that it is a company of pioneers that make bold bets and invent on behalf of customers, focusing on success based on what is possible. This statement shows that Amazon’s organizational culture has the following characteristics:

• Customer-centricity
• Peculiarity

Boldness . Amazon promotes boldness among its workers. This characteristic of the corporate culture is seen in how the company pioneered to sell a wide array of items online, initially starting with books, through data-intensive information technology. Also, Amazon’s employees are encouraged to take risks, such as in considering new ideas to do business. In emphasizing boldness, the company also facilitates openness toward new ideas based on an organizational diversity policy. This feature of the organizational culture enables Amazon to identify the best possible ideas to solve problems or improve the e-commerce business. Boldness supports innovation, which is a factor in the product-development goals described in Amazon’s generic competitive strategy and intensive growth strategies . Thus, this work culture strengthens the company’s competitiveness in the international market for consumer electronics and online services.

Customer-Centricity . Amazon’s mission statement and vision statement highlight the centrality of customers in the business, and the significance of management support for employees’ ability to provide high-quality service to customers. This factor is also included in the company’s organizational culture. For example, Amazon encourages workers’ focus on customers’ needs and preferences. The company continually strives to determine trends and changes in consumer demand and preferences and applies these changes in its online retail and related services. Through this characteristic of the corporate culture, Amazon maintains its effectiveness in satisfying customers as the e-commerce business expands.

Peculiarity . Amazon’s organizational culture also involves peculiarity. This cultural characteristic refers to the idea of challenging conventions. For example, Amazon motivates its employees to view themselves and their work as different from conventional ways of doing business. The company believes that conventions impose limits on potential business growth. Thus, through this feature of its workplace culture, Amazon motivates employees to think outside the box to bring the e-commerce business to its maximum potential.

Amazon’s Culture: Implications, Advantages & Disadvantages

Amazon’s corporate culture reinforces the company’s pioneering efforts in its online business, as espoused in the vision of Jeff Bezos. The firm’s cultural characteristics have the advantage of supporting innovation. For example, boldness and peculiarity promote new ideas to improve Amazon’s information technology and online service business. Another advantage of this organizational culture is its focus on the customer, ensuring that the company satisfies consumer expectations and preferences. These traits of the company culture promote human resource development necessary for protecting the business against the effects of the tough competition described in the Five Forces analysis of Amazon . The business culture supports the organizational development of the e-commerce company and its subsidiary, Whole Foods . However, a disadvantage of Amazon’s organizational culture is that it imposes a strain on human resources, especially in pushing employees to take a bold, peculiar, and non-conventional approach to doing their jobs.

• Amazon Jobs – Pioneers .
• Amazon.com, Inc. – Form 10-K .
• Amazon.com, Inc. – Leadership Principles .
• Amazon.com, Inc. – Our Employees .
• Riani, A., Asya, V. R., & Yuwono, F. S. P. (2023). Literature study of the effect of corporate culture on work motivation and employee performance. American Journal of Economic and Management Business (AJEMB), 2 (3), 89-93.
• U.S. Department of Commerce – International Trade Administration – Retail Trade Industry .
• U.S. Department of Commerce – International Trade Administration – Software and Information Technology Industry .
• Working at Amazon .
• Zhang, W., Zeng, X., Liang, H., Xue, Y., & Cao, X. (2023). Understanding how organizational culture affects innovation performance: A management context perspective. Sustainability, 15 (8), 6644.
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• Educators, Researchers, and Students: You are permitted to quote or paraphrase parts of this article (not the entire article) for educational or research purposes, as long as the article is properly cited and referenced together with its URL/link.

You are here: Influencer Marketing Hub » eCommerce » The Ultimate Guide to Amazon Dynamic Pricing Strategy in 2024

The Ultimate Guide to Amazon Dynamic Pricing Strategy in 2024

Dynamic pricing is no longer a niche strategy limited to the airline and travel industries; it’s on the verge of widespread adoption by all types of retailers. This shift is driven by the increasing demand for better and more seamless shopping experiences. For instance, more than half (55%) of Gen X online shoppers want eCommerce sites to improve their frictionless payment methods. Meeting these expectations requires retailers to be agile, and dynamic pricing is one of the key strategies that can help achieve this.

As Warren Buffet once famously said,

"The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business."

Fortunately, new AI technologies are significantly improving dynamic pricing in 2024, making it easier for retailers to adopt and implement.

In this context, Amazon's dynamic pricing strategy stands out as a prime example of how to use pricing as a competitive advantage. Using sophisticated algorithms, Amazon updates the prices of millions of products multiple times a day, offering the most competitive prices to its shoppers. Join us as we delve into the key components of Amazon's dynamic pricing strategy, its benefits, and how it works.

• What is Dynamic Pricing? 
• Key Factors in Amazon’s Dynamic Pricing

Benefits of Dynamic Pricing on Amazon

Examples from different industries, amazon dynamic pricing implementation.

• Third-Party Dynamic Pricing Software Tools 
• The Reluctance of Retailers to Adopt Dynamic Pricing Software 

Frequently Asked Questions

What is dynamic pricing  .

Dynamic pricing is a pricing strategy where the price of a product or service fluctuates based on current market conditions. It is used by retailers to optimize product prices, improve conversion rates, and increase revenue. In Amazon's case, the pricing of millions of products changes multiple times a day, ensuring that they offer the most competitive prices to shoppers.  

An intriguing aspect of Amazon's dynamic pricing strategy is the use of " price anchoring " to influence customer behavior. Price anchoring is a clever tactic that involves listing a high-priced item alongside a lower-priced item to make the lower-priced option seem like a better deal.

For instance, if a customer is eyeing a $1,000 laptop, Amazon may showcase a similar laptop for $1,200 next to it, making the $1,000 laptop appear to be a more appealing choice. By using this technique, Amazon can sway customers towards purchasing the lower-priced product while still maintaining a healthy profit margin.  

Another interesting aspect of dynamic pricing is that it can lead to price discrimination , where different customers are charged different prices for the same product. This is because retailers can use customer data, such as location, browsing history, and purchase behavior, to tailor prices to individual customers. While this can be a profitable strategy for retailers, it can also lead to concerns about fairness and privacy.  

Use price anchoring in dynamic pricing to make lower-priced options more appealing. Be cautious with price discrimination to avoid customer trust issues related to fairness and privacy.

Key Factors in Amazon’s Dynamic Pricing

Amazon's prowess in dynamic pricing is unparalleled, with the marketplace giant adjusting its product prices a remarkable 2.5 million times each day . It's evident that ignoring the benefits of dynamic pricing is akin to abandoning oneself to the fierce competition of the marketplace. Amazon's dynamic pricing strategy is anchored on cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), and big data analytics. The repricing feature deploys sophisticated algorithms to assess and update the prices of millions of products multiple times daily, taking into account a host of factors such as demand, stock availability, and customer behavior. The algorithms leverage both historical and real-time market data to identify trends and make accurate predictions.  

Although Amazon's pricing strategy remains a closely guarded secret, we can infer that the company considers certain parameters when executing its price changes. These parameters consist of global values and user values. Global values refer to factors such as demand volume and stock volume, while user values include product visit frequency and time of purchase. By evaluating both global and user values, Amazon is better positioned to optimize its pricing strategy and offer the most competitive prices.  

Global values refer to market behavior  

Demand & stock volume  .

Amazon leverages global values such as demand volume, adjusting prices based on anticipated market demand for a product. The company considers whether the demand is seasonal, predictable, and what kind of need motivates the customer's purchase. If the stock units are running low and continued demand is expected, Amazon may increase the prices, provided it doesn't limit a consumer segment's purchases.

Check out the 8 Steps to Growing your eCommerce Business in 2024

User values refer to consumer behavior  

Sku visit ratio & day/time of purchase.

On the other hand, user values such as SKU visit ratio and day and time of purchase help Amazon evaluate consumer behavior. By tracking user behavior through cookies, Amazon can determine how many times the customer has viewed a particular product, if they viewed it at specific times or if they tend to browse related products together. Amazon uses this data to develop more attractive pricing strategies for potential buyers, boosting sales figures and the average value of each transaction. Similar to the tourism industry, certain products may be purchased more frequently on specific days of the week or times of the day, and Amazon promotes price changes during these moments when customers are more likely to browse, compare and make purchasing decisions.  

Check out the 27 eCommerce Marketing Tips to Drive Sales in 2024

Dynamic pricing has helped Amazon maintain its position as the market leader in online retail. Amazon's dynamic pricing algorithms continuously evaluate, review, and update the prices of millions of its products multiple times a day, ensuring that they offer the most competitive prices to shoppers, ensuring retention and brand loyalty. Dynamic pricing has been a controversial topic among consumers, as some argue that it leads to price instability and uncertainty.

However, for Amazon, the benefits of dynamic pricing have been too significant to ignore. In fact, Amazon updates prices 50 times more in average than Walmart, and while some customers may be annoyed by the frequent price changes, it has allowed Amazon to boost its profits significantly.  

Here is a list of key benefits:  

1. Increased Revenue

Dynamic pricing enables Amazon to increase its revenue by adjusting prices in real-time based on market demand, stock levels, and user behavior. This results in more sales at optimal prices, which maximizes revenue.  

2. Improved Customer Retention

By offering competitive prices, Amazon can improve customer retention and brand loyalty. Shoppers are more likely to return to a retailer that consistently offers fair prices.  

3. Competitive Advantage

Dynamic pricing gives Amazon a competitive advantage over other retailers. With the ability to adjust prices multiple times a day, Amazon can stay ahead of the competition and attract more customers.  

Check out the The Ultimate Guide to Amazon Competitor Analysis

Dynamic pricing was first used by airlines and the travel industry, where prices are constantly fluctuating based on supply and demand. However, many other industries have since adopted dynamic pricing strategies, including:  

1. E-commerce

Amazon is the prime example of dynamic pricing in e-commerce. Its algorithms continuously evaluate and adjust prices, ensuring that shoppers receive the best deal possible.  

2. Entertainment

Streaming services such as Netflix and Spotify use dynamic pricing to offer personalized pricing plans based on user behavior and preferences.  

3. Hospitality

Hotels and resorts use dynamic pricing to adjust room rates based on demand and seasonal factors. For example, a hotel may charge more during peak tourist season or for special events.  

4. Transportation

Ride-sharing services like Uber and Lyft use surge pricing to adjust fares during high demand periods.  

Traditional brick-and-mortar retailers like Walmart and Target are also adopting dynamic pricing to stay competitive in the online space.  

Check out the The 15 Best Online Marketplaces for E-Commerce Brands and Sellers

At Amazon, the dynamic pricing tool provides two options for automated repricing: the Pre-Defined Automated Pricing Rule and the Create a Customized Pricing Rule.  

The Pre-Defined Automated Pricing Rule, also known as the Competitive Price Rule, ensures competitive pricing by matching the Buy Box price for a given ASIN, comparing prices from external sources, and updating prices if other sellers of the same ASIN change their prices.  

On the other hand, the Create a Customized Pricing Rule allows sellers to establish their own repricing thresholds based on four fundamental pricing principles: Buy Box, Lowest Price, External Price, and Based on Sales Units. This customization enables sellers to tailor their repricing strategy based on their unique business objectives and competitive landscape.  

To create and implement a repricing rule through Amazon Automate Pricing, it's important to follow these technical steps for optimal results: 

• Visit the Automate Pricing homepage and click "Get Started" to begin creating a new dynamic pricing rule.  
• Select the type of rule that best suits your needs from the drop-down list, taking into consideration your unique business objectives and competitive landscape.  
• Name the rule you are creating to help you recall why you assigned a particular SKU to it later on. This will save you time and effort when managing multiple repricing rules.  
• Choose the SKUs you intend to enroll and define the corresponding rules for each. You can enroll SKUs one by one or in bulk, and even download a file to enroll all unenrolled SKUs. It's important to set a minimum price to sustain your targeted profit margin. Afterward, click "Proceed to marketplace(s) selection" and select the marketplaces where you want to implement that dynamic pricing. Then, click "Save and Continue" to proceed.  
• Choose the primary price action, such as "match", "beat", or "stay above", depending on the repricing principle you have chosen. This will help you tailor your repricing strategy to your unique business goals and help you stay competitive.  
• Specify the price margin in percentage or amount by which you want to automate the price. This will ensure that your pricing remains within your desired range while also remaining competitive.  
• Apply filters to fine-tune your pricing changes to only relevant offers. For example, you can set your price to be compared only to other FBA offers to help ensure that you remain competitive with similar products.  
• Review the Rule Summary to ensure that you have set the rule in accordance with your specific requirements, and then click the "Save this rule" button to make it a part of your repricing strategy. This step is crucial to ensure that your repricing strategy is aligned with your unique business goals and objectives.  

Check out the How Amazon FBA Works & Ways to Maximize It in 2024

To assess the efficacy of your dynamic pricing strategy , keep a close watch on the automated pricing page and examine Seller Central business reports. Analyzing these metrics will enable you to track the impact of the repricing mechanism on your sales and assess its influence on the Featured Offer win percentage. Continuously monitor these parameters to measure the success of your repricing strategy.  

• 15 Amazon Analytics and Tracking Tools for Sellers
• The Best Amazon Pricing Strategy for Incremental Growth
• How to Start an E-Commerce Business in 2024 | The Ultimate Guide

Third-Party Dynamic Pricing Software Tools  

Amazon sellers rely on third-party software tools that integrate with Amazon as well, to automate and create dynamic pricing because these tools provide more advanced features and functionality compared to Amazon's built-in repricing tool. Third-party software tools offer additional features such as competitor analysis, price history, and Buy Box monitoring , which are not available in Amazon's built-in tool.  

Furthermore, third-party repricing tools offer more control over pricing and allow sellers to adjust prices based on a variety of factors such as sales velocity, inventory levels, and competitor prices. This level of customization and control allows sellers to optimize their pricing strategies and maximize profits while still remaining competitive in the Amazon marketplace.  

Another benefit of using third-party repricing tools is that they offer better customer support and troubleshooting assistance. While Amazon's support can be slow to respond and often provide limited solutions, many third-party tools offer dedicated support teams and extensive knowledge bases to help sellers address issues and make the most out of the software.  

The Reluctance of Retailers to Adopt Dynamic Pricing Software  

Retailers may be hesitant to use dynamic pricing software because of concerns about the complexity of implementation, the cost of the software, and the potential negative impact on brand loyalty if prices change too frequently. The list of cons includes amongst others;  

1. Legal Risks

Retailers need to consider the legal risks associated with dynamic pricing. Discrimination based on gender, race, and other categories, as well as privacy issues, are major concerns as states tighten their laws around data collection. Retailers that use dynamic pricing algorithms must be careful to ensure that they are not engaging in any discriminatory or unethical practices that violate anti-discrimination laws or breach consumers' privacy.  

2. Practical Problems

Dynamic pricing presents practical problems as well. One of the most significant issues is the risk of alienating consumers as prices change regularly. This risk can be especially high during times of high demand when prices may increase, leading to consumer backlash. Issues with returns are also common because dynamic pricing may not take into account factors such as product quality, which could lead to higher return rates.  

3. Negative Perception

Dynamic pricing also faces negative consumer perceptions, which can impact brand loyalty. Consumers may feel that they are being manipulated or exploited by retailers using this strategy. They may feel that prices are unfair or arbitrary, leading to a lack of trust in the retailer.  

4. Comparison with Personalized Pricing

While personalized pricing has not been widely adopted in retail, the Organisation for Economic Co-operation and Development (OECD) has found that it can improve the lot of customers in aggregate. However, personalized pricing also raises transparency, consumer protection, and antitrust issues. Dynamic pricing presents similar issues, but on a larger scale, as prices change regularly and are often based on real-time data, making it difficult for consumers to understand the pricing logic.  

Dynamic pricing has become more sophisticated with the help of advanced technologies like machine learning and big data analytics. This has resulted in improved accuracy and reliability of market data, allowing retailers to make more informed pricing decisions in real-time. The implementation of automated pricing tools has further simplified the process, freeing up retailers to focus on other aspects of their business.  

With the increased transparency of dynamic pricing strategies, consumers are more likely to trust retailers and view price changes as fair and reasonable. However, it is important for retailers to be mindful of the potential risks associated with dynamic pricing, including legal issues and negative consumer perceptions.  

Despite these challenges, dynamic pricing has proven to be an effective strategy for retailers looking to boost profits and remain competitive in the marketplace. As technology continues to improve, we can expect dynamic pricing to become even more accurate and reliable, making it an even more attractive option for retailers.  

What is Amazon's dynamic pricing strategy?

Amazon's dynamic pricing strategy involves using sophisticated algorithms to update the prices of millions of products multiple times a day based on various factors such as demand, stock availability, and customer behavior.

How does Amazon use dynamic pricing to compete with other retailers?

By offering competitive prices through dynamic pricing, Amazon can stay ahead of the competition and attract more customers. Its algorithms continuously evaluate, review, and update the prices of its products, ensuring that they offer the most competitive prices to shoppers, which helps in improving customer retention and brand loyalty.  

How does Amazon use data to tailor prices to individual customers?

Amazon uses customer data, such as location, browsing history, and purchase behavior, to tailor prices to individual customers. This can lead to price discrimination, where different customers are charged different prices for the same product.  

How does Amazon address concerns about fairness and privacy in its dynamic pricing strategy?

Amazon has become more transparent about its dynamic pricing strategies in recent years, providing clear explanations for price changes and being upfront about the data used to make pricing decisions. This can help to build trust with consumers and mitigate concerns about unfair or discriminatory practices.  

What are the benefits of Amazon's dynamic pricing strategy?

Amazon's dynamic pricing strategy has helped the company maintain its position as the market leader in online retail. It has enabled Amazon to increase its revenue by adjusting prices in real-time based on market demand, stock levels, and user behavior. It has also improved customer retention and brand loyalty by offering competitive prices.  

Are there any risks or challenges associated with Amazon's dynamic pricing strategy?

Yes, there are some risks and challenges associated with Amazon's dynamic pricing strategy. It can lead to concerns about fairness and privacy, as well as practical problems such as issues with returns and negative consumer perceptions. Retailers must also be mindful of the legal risks associated with dynamic pricing, such as discrimination and privacy issues.

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This repository contains an in-depth analysis of Amazon Sales Data using SQL 🚚📦.Whether you’re a data analyst, business strategist, or SQL enthusiast, this analysis offers a comprehensive look at e-commerce dynamics through the lens of Amazon’s vast sales data. Feel free to explore the queries and contribute to enhancing the analysis! 📊🚀

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Amazon-sales-data-case-study-using-sql-and-dashboard.

Note: Check out the .pdf and .pbix files to get clear view of the project ☺️

Dashboard using powerbi:.

Objective Of The Project

The main aim of the project is to dive into the Amazon Sales Data and draw insights from it and analayze which factors affect the sales of different cities and their corrosponding branches using SQL. The project aims to uncover insights into sales trends, customer behavior, and product performance. By leveraging the power of SQL queries, we extract meaningful statistics and patterns from complex datasets.

Overview Of The Dataset

The dataset consist sales record for three cities of Myanmar which are Naypyitaw, Yangon and Mandalay and their respective branches A, B & C. The sales took place in the first quarter of year 2019. The dataset consist of 1000 records and 17 fields like (Invoice Id, Branch, City, Customer Type, Gender, Product Line, Unit Price, Quantity, VAT, Total, Date, Time, Payment Method, Cogs, Gross Margin Percentage, Gross Income, Rating).

Steps Performed On Dataset

• 1] Data Wrangling
• 2] Feature Engineering
• 3] Exploratory Data Analysis

Analysis Performed On Dataset

• 1]Sales Analysis
• 2]Product Analysis
• 3]Customer Analysis

Questions Answered

• What is the count of distinct product lines in dataset?
• Which payment method occours most frequently?
• Which product line has highest sales?
• How much revenue is generated each month?
• Which product line generated highest revenue?
• Which city has highest revenue record?
• Which product line incurred highest VAT?
• Which customer type occours most frequently?
• Which branch exceeded average number of product sold?
• Which product line is most frequently associated with each gender?
• Identifying cusstomer type contributing highest revenue?

And many more....

For more such intresting projects do check out my other repositeries....keep learning...keep growing...piece✌️