Testing can mean taking bigger risks; you don't have to go with the safe or plain options.
Last week in a client meeting, one of our senior Web analysts gave an overview to a new client about site optimization and summed it up nicely with four simple words: "No more design guess."
Those four simple words summarize what it means to have a site optimization program leveraging A/B or multivariate testing and behavioral targeting. Now, you can say the value isn't in reducing guesses but in maximizing site performance based on business goals. But the way we do that is to reduce guesses or gambles.
You can even get it down to three words: "no more guesses." No more guesses about design -- and many other things. If we have defined site goals, understand the impact of different behaviors on our sites (see past columns on monetizing site behaviors), and are really looking to maximize site performance, we may want to look at reducing the guesses for key pages and throughout the site in a number of areas, including:
As you can see, there are many things we could guess about. When you combine these factors together, your chance of guessing the correct combination is about as close to zero as you can get. In many cases, testing can mean taking bigger risks; you don't have to go with the safe or plain options. You can try edgier copy or imagery; you can push the envelope a bit. If you're simply guessing what will work, a group or committee will always guess the safe bet, as the risk is too high to be wrong.
Let's take the guessing to the next level. How can we guess which version of all the above elements will help us convert different people in different segments? Now the decisions are even harder. We could guess at which version will best convert the average visitor and only roll out one version of a page, offer, or call to action. In some cases that could work really well. But we could also look to understand through site optimization testing which versions convert better for different audiences. If we find different combinations work far better (or worse) for one audience than another, we may decide it's worthwhile to present different content based to different audience segments.
Our chance of success will start to climb once we tune the message to our different segments, targeting to each segment's desires and needs. But when we get to this level, guessing can create a ton of problems.
Site optimization can reduce those guesses, reduce the blind gambling of ideas, and ultimately help us be more successful faster. And remember: a test that doesn't produce a winner over the control isn't a failure; we learn something. A failure is putting all your eggs in one basket, guessing on what will work, and not taking the time to truly understand the impact of that guess or seeing what the impact could be with different versions.
Thanks to our Web analyst for simplifying what we are all trying to do in making better decisions about our Web channel. While we know it's more than just about visual design, it's a great way of thinking about site optimization and improving your business. Even when we feel we know a ton about our customers, their behaviors, attitudes, and needs, we still can't forecast perfectly what will get different people to convert.
Are you reducing the number of guesses your company makes about changes on your site? Are you helping your company make smarter, proven decisions? Are there people in your organization who enjoy gambling with the success of your Web business because they don't know any better? If so, help educate them on the benefits of testing, segmenting, and maximizing the impact of their work.
Site optimization means "no more guesses" and eliminates concern over being wrong, meaning you can try new things that you wouldn't have been able to before. The risk of being wrong in a world of testing is much less than the one big guess.
How do you think about or easily explain site optimization? Comment below and share your thoughts.
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As President of the Americas at POSSIBLE, Jason is responsible for leading the long-term stability and growth of the region. With more than 20 years experience in digital strategy, he is a long-time advocate of using data to inform digital strategies to help clients attract, convert, and retain customers. Jason supports POSSIBLE's clients and employees in driving new engagements and delivering great work that works. He is the co-author of Actionable Web Analytics: Using Data to Make Smart Business Decisions.
Follow him on Twitter @JasonBurby.
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