Amazon.com An online retailer that uses web analytics

Of all of the categories of businesses that exist today, it is almost a no-brainer that online retailers are among the main ones using web analytics as a routine part of their business. After all, the success or fail of that business seems to rely solely on online traffic, clicks, conversions, etc. But a recent survey suggests that a vast majority of e-commerce sites are failing to make the most of their web analytics.

The DBD Media survey, conducted in October 2012, includes responses from 50 e-commerce sites, of which 73 percent are inflating their traffic in their reports, while 67 percent haven’t integrated social media. Some other eye-opening stats from the survey include:

--50 percent of e-commerce businesses track main conversion points

--60 percent of Google Analytics accounts were not correctly synced with Google AdWords

--33 percent of websites with on-site search function do not track site search keywords

--73 percent do not track micro conversion goals such as newsletter signups or account registrations

--30 percent of websites have incorrect e-commerce tracking implementation

As you can see, although the “bread and butter” of many e-commerce sites is traffic and conversions, many of them are not tracking this information at all or not tracking this information properly. To seemingly be the master of all things online, online retailers certainly leave a lot to be desired when it comes to their use of web analytics.

One online retailer that does a pretty good job utilizing web analytics, though, is Amazon. Have you ever been to Amazon.com to shop for a Christmas gift (or any other occasion) and, while reading up on the specifications for a particular item, notice that they also list the top three or four items customers ultimately bought after viewing that particular item, as well as the top items that customers buy in addition to that particular item? This is one of the ways Amazon uses web analytics.

This tactic is part of a much larger strategy – to sell and cross sell through recommendations. Amazon’s recommendation system is based on a number of things: what someone has bought in the past, which items they have in their shopping cart, items they have rated and liked and what other customers have viewed and purchased. All of this analytical data is collected and pushed back out to the customers in the form of a recommendation, which customizes the online shopping experience for each consumer. According to an article on Fortune.com by JP Mangalindan, this tactic seems to work for Amazon, as the company reported a 29 percent sales increase.

Since there are Amazon employees that are responsible for promoting certain purchases, they may think up similar items and make sure that customers who have viewed those items receive an email encouraging them to check out the product the employee is responsible for promoting.  Mangalindan’s article also discusses how web analytics are also used in this scenario. If, for example, a customer qualifies for both an email for book recommendations and video game recommendations, the email with the higher average revenue per mail sent will win out.

This is pretty cool from a consumer perspective, because it prevents my email inbox from being flooded and from a marketing perspective because it maximizes the purchase opportunity, as Amazon’s conversion rate and efficiency of such emails are “very high” – significantly more than on-site recommendations.

Something else Amazon does is optimize the use of its Thank You page. It uses this page as an opportunity to reengage with an already highly engaged visitor. For many retailers, it is easy to assume that as soon as a consumer is finished with their purchase that they will leave the site, so they don’t see a need to reengage. But with Amazon, the Thank You page is a place for them to thank the customer for their order and allow customers to track the status of their order, cancel items from their order, edit the shipping method, see the status of all orders, organize book and music and video purchases in their Media Library. There are also recommendations there, including some based on the purchase that brought the consumer to this page as well as recommendations for items that are frequently bought with the consumer’s recent purchase. Other retailers use the Thank You page as an opportunity to tempt the visitor back into the store, having them sign up for a next-time buy coupon, or have them participate in a survey.

This page is also measured and the analytics can be pretty mind-blowing. I image that by tracking the clicks post-purchase, Amazon determines what percentage of customers leave the site and what percentage of customers do not. And of those that exit the site, Amazon can examine how can they serve those customers better.

In terms of tools, methods and metrics that can also be used to improve Amazon’s overall web analytic efforts, I am not sure what other tactics Amazon can deploy in order to improve. From a consumer’s point of view, every time I visit the site, I am logged in and my recommendations appear on the page. I also receive email recommendations. When I visit other sites, I see advertisements from Amazon for the specific item I was shopping for previously.

When I try to think outside of the box, Amazon has that covered too. They allow competitors to sell on their site but once they see high conversion rates, Amazon begins to sell those products as well, this time at a lower price. Amazon even tracks clicks on its competitors’ advertisements on its site. Pricing and product placement are tweaked to maximize the use of this analytical data.

To reiterate my previous point, many online retailers have begun to use web analytics to better their business, but either there isn’t enough businesses doing it, or there isn’t enough businesses doing it well. Amazon seems to be doing quite well on this front, although there is always new data to collect and new strategies and tactics to deploy.