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You are here: Home / Advertising / The Real Reason for Amazon’s Success

The Real Reason for Amazon’s Success

May 31, 2018 by Charlie Liang Leave a Comment

Amazon has and will remain one of the worlds fastest growing companies. Since 2006, the online retailer has grown an average of 31% year over year, with no end in sight. 

To maintain their massive growth rate, Amazon has been expanding by acquiring everything from Whole Foods to Zappos. This allows them to dominate their competition but Amazon’s key obsession and rapid optimization is what sets them apart.

Three things have allowed Amazon to maintain its position in the online retail space and become the go-to shop for 75% of US online consumers.

  1. Amazon’s obsession with its customers.
  2. The websites user experience.
  3. Conversion rate optimization focused on the first point.

All three center around a customer-centric growth strategy where customer satisfaction trumps profit.

A Culture of Customer Obsession

Do you know the original name for Amazon? Cadabra.

Terrible, I know.

But that was one of the names Jeff Bezos toyed with alongside Relentless, Bookmall, Aard, and then finally, Amazon. In the early days of the internet, website directories listed companies alphabetically, making Amazon the top link on many sites. This decision set the stage for Amazon’s relentless optimization, starting with the homepage.

From the moment you land on Amazon’s homepage, everything from the left corner of the site to the auto-scrolling container focuses on your needs, right now.

Amazon’s customer-centric strategy is so ingrained into the culture that it’s no surprise Bezos hand delivered books to the local post office in their early days. And when the company started looking at expanding its offerings, the first thing they did is send an email out to 1,000 random customers and ask.

“I sent an email message out to the customer base, actually a thousand randomly selected customers, and I said, besides books, music and video, what would you like to see us sell? And the list came back incredibly long,” explains Bezos.

That was the spark that helped Amazon become “The Everything Store”.

Why Conversion Rate Optimization Is Key

It wasn’t only customer obsession that lead Amazon to become successful. Amazon tests every step of it’s user experience and interface for the greatest impact, a process driven by it’s ‘Culture of Metrics’. In fact, if you look at the industry benchmarks for e-commerce conversion, Amazon stands out as an outlier with a conversation rate that is several multiples higher than any of its competitors.

To give you an idea of what this means, according to a study by Millward Brown Digital, Amazon Prime members convert at 74% and non-prime members at 13%. That’s 4x higher than the average online retailer who converts users at a paltry 3.32%!

But this is just one area Amazon has been able to innovate in. The companies item-to-item collaborative filtering which displays on the site as the ‘Customers also bought’ section has been studied by numerous publications for its novelty and ability to efficiently encourage users to add additional items to their cart. Not surprisingly, it accounts for 35% of Amazon’s revenue according to a study by McKinsey & Company.

Amazon’s User Funnel

Let’s take a look at a sample user funnel. At the Amazon sign-in page you’re presented with deals which are timely and affordable. Mother’s Day is around the corner, so you’re shown “Gifts as unique as your mom” and “Deals for Mother’s Day”.

Screenshot of Mother's Day shopping results from Amazon

Once you select a gift, you’re sent to a product page where you can see that:

  1. This product has a high number of reviews.
  2. It’s received an Amazon’s Choice label for “Top Gifts for Women”.
  3. And it has a “Low Return Rate” further solidifying your decision.

Screenshot of bath bomb gift set on Amazon

After you’ve added the item to your cart, Amazon knows exactly what other users have purchased alongside it. So you’re presented with a list of complementary items “Customers also bought”. This seemingly simple option has resulted in $12.83 billion dollars in additional revenue (a 29% lift in sales) for Amazon in their second fiscal quarter of 2012.

Screenshot of recommended bath and beauty products

Going into your cart, you’re immediately shown how much you’ll save if you’re approved for an Amazon Rewards Visa Card. Signup and you’ll receive a gift card worth $50, taking your total cost to $0. Amazingly, you’ll have $23.37 remaining to splurge on other items.

Screenshot of credit offer advert from Amazon shopping basket

Without a doubt, it’ll be tempting to add another $23.37 worth of gifts from the “Customers Who Bought Items in Your Recent History Also Bought” section.

Screenshot of items customers who bought items in your recent history also bought

And finally, during checkout, you can get free shipping if you’re an Amazon Prime member. You don’t want to feel left out of this elite group so you’re going to click-through to see what Prime is all about!

In the end, you’ve spent nothing, shopped for Mothers Day, and even had Amazon gift wrap your items.

Congratulations, you’ve become a lifelong member of ‘The Everything Store’.

How To Use Analytics To Optimize For Growth

Amazon’s culture of metrics serves as an example for every company to follow. And just like Amazon, the core your growth is a combination of data that helps you make decisions, analytics and CRO (conversion rate optimization). Without data, you’re testing blindly, which requires 10x the number of experiments, not to mention time, to turn up positive results.

However, there is one glaring issue with data and analytics which hasn’t been solved up until recent – analytics is iterative. This brings up an interesting problem.

Until recent, a big hurdle with analytics was balancing marketing’s needs with engineering’s limited resources. To make this efficient, marketing teams typically create a tracking plan where you document the events that you need to track in your product. Then you pass your documentation over to engineering and have the engineering team code the tracking, test it, and release it.

But what happens when you notice a drop-off in your funnel later?

You may need to segment the drop-off point and create a sub-funnel or compare two different user flows to build hypothesis on the drop-off. If you didn’t track these events in your plan, you’ll have to go through another cycle of working with engineering then wait for data to fill your funnel.

This can take months, especially since you’re not Amazon and you don’t have enough users in your product to generate immediate actionable data. (Amazon receives 197 million visits per day as of December 2017 according to Statista).

Code-Less Retroactive Analytics

The better approach is to capture everything once and analyze the data retroactively.

With tools like Heap you can auto-track the entire customer journey. Install one snippet of code into your product and track everything. In fact, that’s all the engineering help you’ll need because you can use a WYSIWYG event visualizer to define custom events.

And since your data is captured the moment you first installed the tool, once you define a new event, you’ll get all of your past data. This allows you to define custom funnels and cohorts then analyze them to build and test your hypothesis right away.

You can then run split tests with A/B testing tools, collect additional data, and attach the experiment name and variation as a property associated with their behavior in Heap.

You may not have Amazon’s daily visitors but with the right tools and process in place, you can test and iterate quickly. In fact, you can get ahead of your competition and build a more customer-centric product today using the right CRO process similar to how Sur La Table used Heap to increase their conversions by 6%.

Filed Under: Advertising, Amazon, behavioral targeting, Conversion Rate Optimization

About Charlie Liang

Charlie Liang is the Head of Demand Generation at Heap. Charlie has almost 10 years of experience with analytics tools and is passionate about conversion rate optimization and helping marketers and product leaders optimize for revenue on their websites. Previous to Heap, Charlie was the first marketing hire at Engagio. He is a long time resident of the San Francisco Bay Area and enjoys runs with his American Pitbull puppy.

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