Amazon's Web Analytics Capabilities

Amazon. They’ve conquered e-commerce, changed the way we buy groceries, and may now potentially change healthcare. With all of the data Amazon has access to, how do they make sense of it? How do they take the raw data of people’s past purchases, how often people visit the website and so much more? Let’s dive into Amazon’s web analytics as well as their on-page SEO to gain a better understanding.

At their core, Amazon’s mission has been to simplify the way customers buy things. (Wills, 2016) The brand starts by using a comprehensive collaborative filtering engine (CFE) to analyze which items a visitor previously purchased as well as items that are searched for and in their shopping cart, and uses an algorithm to recommend additional products that are similar. (Wills, 2016) These product recommendations - and the outreach of additional products users should purchase - have been able to increase Amazon’s revenue by around 30% annually.

Big data is another component Amazon uses to make sense of the customer data they have available to them. (Investopedia, 2018) Big data comes from multiple sources and can arrive in multiple formats so it’s up to brands to make sense of everything that’s coming through on their customers and focus on the metrics that can make a difference. Amazon interpreted their big data in a few different ways that allowed them to come up with unique features of their service that have contributed to their success as an e-commerce site. (Wills, 2016) Amazon found out that customers will shop somewhere else if their products will arrive more quickly so that’s how they created One-Click ordering. This allows customers to purchase items more easily on Amazon’s website by making the entire purchase cycle extremely seamless. The brand has also used big data to determine the prices of items on their website to ensure they receive an optimal ROI. (Wills, 2016) Prices on Amazon are determined by a particular user’s activity on the site, competitor’s pricing, order history and several other factors.

Not surprising to most, Amazon chooses to host their customer and e-commerce data in-house and mostly on the cloud. (Ann, 2016) Amazon’s Elastic MapReduce is built on top of a Hadoop framework that allows them to catalogue billions of their products as well as house their global fulfillment center information on an Amazon S3 interface. (Ann, 2016) The product catalog usually goes through about 50 million updates every week and is sent to Amazon’s various data warehouses about every hour.

Looking at the menu options in your Amazon’s Account & Lists menu gives the first glimpse in how the brand uses their data for their on-page SEO structure. Hovering over the drop-down menu shows categories titled “Your Recommendations”, “Your Pets”, and “Your Garage” show how unique and tailored their data is to each individual user.

(Amazon, 2018)

Amazon can gain insights directly from these specific categories and see how much traffic and revenue is generated from this menu. Another feature that I’ve mentioned already is the “Product Recommendations” section at the bottom of every product page. For example, looking at a smart coffee maker, if you scroll down you’ll see other items Amazon recommends such as other coffee makers and bags of coffee on the same product page.

(Amazon, 2018)

The brand also implements SEO best practices to ensure the page ranks well even when someone is conducting a search on Google or Bing. After clearing my cache, I opened up Google and typed in “Brewgenie Coffee Maker” and Amazon had the first organic search result placement on Google’s first SERP. The word Brewgenie is listed in the URL and all throughout the title and body copy of the product page which makes it an excellent candidate for the first Google organic placement.

We can’t talk about Amazon without mentioning their voice assistant Alexa. Amazon’s Echo houses the voice of Alexa that can answer anything from “What’s the weather?” to “How many ounces are in a cup?” The fact that Amazon now has data on what people are actually asking and the natural language people use opens up numerous possibilities for the brand. Amazon created their own platform to track Alexa’s users’ activity on a skills metric dashboard. (Blankenburg, 2017) The dashboard allows a brand to see how many people are using a certain skill, peak usage time and the time of day the most people used a skill. Brands can then use analytics from voice assistants like Alexa to gain a holistic view of their customer’s experience so they can prioritize features that will help increase their skill’s level of engagement.

Amazon Echo users are actually able to see the questions they have asked Alexa in their device history and can delete certain queries or the entire log history. The fact that Amazon saves these questions on a data server has so much potential for how they can personalize a user’s experience. As I mentioned earlier, Amazon’s home page looks different to every user and has different menu options based on how they use the site. With information from Alexa, Amazon can use the questions and other items users talk to the device about to tailor the content the user sees on Amazon’s site. This will also tie back to all of the brand’s on-page SEO efforts and how they ultimately use data to drive their insights and how users interact with Amazon.

Amazon has and will continue to become a pioneer in a lot of things because they use the data provided to them from their customers and turn it into meaningful experiences for their users.

Amazon. (2018). Retrieved February 19, 2018 from https://www.amazon.com/

Ann. (2016). How Amazon Uses Its Own Cloud to Process Vast, Multidimensional Datasets. Big Data Zone. Retrieved February 19, 2018 from https://dzone.com/articles/big-data-analytics-delivering-business-value-at-am

Blankenburg, J. (2017). Leverage the New Metrics Dashboard to Deepen Skill Engagement, Drive Retention. Amazon Alexa. Retrieved February 19, 2018 from https://developer.amazon.com/blogs/alexa/post/2b3912a9-c6ec-4642-9c1a-55c42d0f14b6/leverage-the-new-metrics-dashboard-to-deepen-skill-engagement-drive-retention1

Investopedia. (2018). Big Data. Retrieved February 19, 2018 from https://www.investopedia.com/terms/b/big-data.asp

Wills, J. (2016). 7 Ways Amazon Uses Big Data to Stalk You (AMZN). Investopedia. Retrieved February 19, 2018 from https://www.investopedia.com/articles/insights/090716/7-ways-amazon-uses-big-data-stalk-you-amzn.asp