Long gone are the days when it was sufficient to deliver to all users the same content or experience. These days, customer experience optimization must be personalized. However, the kinds of optimizations that most customer experience professionals typically engage in are not sufficient either. Personalization based on demographics and categories, such as geography or device type, is very basic.
To reap the greatest rewards, one must use web analytics data to truly understand their users’ behavior. Collecting this data, analyzing it, and using that insight to personalize the experience by creating different scenarios that relate to the main behavioral clusters in real time is the ideal way to serve users and increase conversions.
I have found that the best way to understand how to maximize web analytics data is by taking a look at some examples.
Adobe, for example, shows this home page to a new user:
I surfed their site looking for marketing information on responsive websites. The next time I hit the home page, I was presented with a completely different page – one that targets visitors who are interested in marketing on mobile devices:
Adobe studied my online behavior to understand my interests. By browsing the Adobe site for specific topics and watching videos of sessions from past conferences, the company’s web analytics intelligence identified me (correctly) as a marketer.
What can you learn about your visitors based on their online behavior? If you find that their interests surround one product type, serve them a customized home page the features that product type.
Amazon: Personalization Genius
We all know (and love!) Amazon because it is perfect for us. But it turns out that my Amazon may be quite different from your Amazon.
When I used my daughter’s computer to go to Amazon.com, I was presented with this home page:
The page highlights deals for college students, fashion purses, and blockbuster movies. Amazon has her figured out!
Going to Amazon using my computer, the home page looks quite different:
This home page highlights tablets and business books. Yes, this certainly is more up my alley.
I have never clicked on the book called “Ask.” My daughter doesn’t own a fringed purse. And yet, based on our past browsing behavior and previous purchases, Amazon found new items that certainly are of interest to each of us. They also know better than to show my teenage daughter business books or try to interest me in a movie called “Hercules.”
Monitor your visitors’ behavior to offer them products or services that may interest them based on what you know about them.
Zappos: Cross-channel User Behavior Personalization
Zappos may have reached the top of its vertical because of its free shipping and amazing returns policy, but the company’s understanding (and capitalization) of user behavior is helping them maintain the top spot.
I recently shopped on the Zappos site for sneakers I wanted to give as gifts to my niece and nephew. I did find the exact model the teens wanted on Zappos, but I didn’t end up buying them. However, the company’s web analytics took note of my incomplete purchase. Needless to say, when browsing the Zappos site now, I am reminded of the items left in my cart:
Studying user behavior can tell us a great deal, not just about their preferences, but also about their online personality type. Zappos carefully words its email message to prompt me not to let my chosen shoes escape my grasp.
If your web analytics show you that visitors are hesitating to complete a conversion (or purchase), use multiple channels to urge them along.
American Express: Understand what Users Love
American Express may have a bit of an unfair advantage in the user behavior game. Not only can the company track my online behavior on its site (I checked out travel-related rewards and tried to understand more about American Express’ travel insurance), but the company also has access to my offline purchase history.
It is certainly no surprise then that when I am logged into my AmEx account and hit the home page, I am shown travel-related images and messaging.
When American Express got a clear picture of what a user like me is interested in, it doesn’t try to push me into funnels that are of no interest to me (like telling me about interest rates, for example). Instead, the company capitalizes on what it knows I like. The company speaks my language. It appeals to my senses. And it works!
Web analytics data are not about just user profile information or referring sites (although those are important things to consider). Today’s web analytics data can monitor a users’ behavior – the pages that interest them, the types (and price range) of products they are likely to buy, even their hesitations in completing a conversion. Understanding this important information will certainly help you innovate creative campaigns to increase conversions.
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Efrat Ravid is the Chief Marketing Officer at ClickTale. She is responsible for leading worldwide marketing initiatives targeting global fortune 500 companies, as well as creating and publishing Digital Customer Experience thought leadership content for the industry.
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