Because you don't want to be part of the 2% conversion rate crowd.

If You Want Amazing Results, Stop Asking “What Should We Test?”

I hear this question being asked all the time — even from seasoned marketers who know how to run an A/B testing program. I see people blogging about what to test, which can be helpful, but it overlooks the most important aspect of testing: learning about the test subject (your visitor, prospect, or customer!).

Your Web site is a series of design and messaging elements comprised of pixels and code. Your site is powered by Web servers, and delivered over wired and wireless connections. There is a lot of technology that goes into making it all work, but ultimately its purpose is to help people accomplish their goal (and I cannot think of a single exception to this statement).

When you ask the question, “What should we test?”, your focus is on the Web page element and not on the person who will generate your test data.

Headlines, CTAs, form fields, checkout flows, images, product copy, security assurances, trust builders, value propositions, sub-heads, cross-heads, navigation, social widgets, sign-up forms, colors, special offers, and subject lines are all things you should be testing. But if you develop your list of test ideas without explicitly calling out the human part of the equation, you’re not going to achieve the same results or return on your time/money as the person who focuses their test ideas on what they want to learn about the visitor.

So don’t ask, “What should we test?”.

Instead ask, “What do we want to learn about our visitors?“.

This seemingly benign change in wording will transform your entire testing program. Here’s how:

1. A focus on learning will spark a lot more test ideas than jumping straight into creating a tactical list of ideas, because there are so many ways to learn about your visitors. In your business, you don’t jump into tactics without first having a strategy in place, do you? Strategy drives tactics; desired learning drives test ideas.

2. A focus on learning will ensure that you learn something on every test. Testing without a customer hypothesis puts the focus on getting a winner — which we all know only happens a fraction of the time. A flat test result is still a success if you set out to learn something about what does or does not influence your visitors.

3. When you learn something about your visitors, you’ll want to learn more (follow-up tests!) — which fuels your testing engine and builds your understanding of the people coming to your site.

4. When you learn something about your visitors, you can immediately apply that learning from your Web site to your other marketing initiatives and even to product development. You can leverage a new learning across your entire business.

5. Once you develop a solid understanding of your visitors/customers, you’ll be able to predict their behavior — which is every marketer’s dream. Being able to predict behavior makes selling much, much easier (just ask any successful salesperson!).

Start asking, “What do we want to learn about our visitors?“.

It’s a simple change to the way you think about testing, but the results will amaze you.

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About Lance Jones

I have an amazing partner, Joanna, and two incredible sons, Alec and Connor. I spend too much time in front of a monitor, but I still manage to squeeze in some fun. I also have a deep respect for entrepreneurs and love reading their stories, so shoot me a note and let me know if I can help!

  • Daniel Gonzalez

    Lance, this is another great post. I’m curious, when you run a testing program for a client, how long until you typically see a conversion lift?

    There’s weeks of research that needs to be done. But… what’s a decent rule for number of tests with out a conversion lift, to  tests that get a conversion lift? 

  • http://www.toppingtwo.com/ Lance Jones

    Hi Daniel. Great question. Gosh, that really varies. And it depends on how much room for improvement there is on the client’s site.

    If the site I’m consulting for has a bunch of usability issues, I usually tackle those first… because they’re often very easy to rectify, and if you do successfully solve the usability obstacle, you can generate lift on your very first test!

    Once those “fixes” are out of the way, the length of time to achieve a win is a function of how much you already know about the visitors. If you don’t know a lot, you may have to run some initial tests to learn what resonates with them. If you have some good insights into the visitors mindset, you may only need a test or two to get a win.

    But win or not, you want to generate a clear learning from every test — the wins will follow once you get inside the minds of the target audience.

  • http://twitter.com/Qarau_ Qarau

    Great post Lance. One thing that amazes me is how much I learn by watching someone else interact with what I’ve designed. Seeing what they do and don’t do then going back to the drawing board to refine it. By asking the right question “What do we want to learn about your visitors?“ we’ve already set out a pathway that we get to refine and perfect based on the results. This approach will be more effective and should cut down testing time.   Awesome!

  • http://www.toppingtwo.com/ Lance Jones

    That is precisely how it’s supposed to work, Qarau! Sometimes it takes awhile to get there, but since you’ve already embraced the learning aspect of testing, you’re WAY ahead of most businesses. Thank you for your comment, sir.

  • http://www.decalmarketing.com/adwords-book/ Iain Dooley

    Another thing I think it’s valid to think about is what you can realistically test, given the amount of data you have access to. The very first time I ever ran an A/B test via Optimizely I was all excited until I read that they don’t declare a “winner” until they have 100 conversions *per variation*.

    If you had a 5% conversion rate then you’d need 4,000 visitors to get a statistically significant result within a month. If you have 2% (which is more likely if you’re only just starting to test) then you need 10,000 visitors to get a result within a month.

    There was an article on Marketing Experiments that talked about testing at low volumes (that I can’t find … thanks Google!) saying that you should focus on tests on things that will produce huge results, ie. you have to use “radical redesigns” rather than simpler tests on your headlines, form layouts or button colours.

    Do you have much experience with those kinds of “overhaul” tests, Lance? What are your opinions.

  • http://www.toppingtwo.com/ Lance Jones

    Hey, Iain! It’s true… you really do need substantial traffic to run a continuous testing program. And you’re also correct in that the amount of lift plays into the duration of a test. The bigger the difference in conversion, the less traffic is required to detect a statistically meaningful difference.

    We’ve got plenty of experience with “overhaul” or “radical redesign” tests. You can throw everything at a test to have a bigger impact, but you still never know if you’re going to get a winner. :-) The biggest issue with radical redesigns is that you can’t tell which of the modified elements is responsible for the lift. So you can’t apply the learning to other pages or marketing materials… you basically end up with a “one-off” test result (which may be okay).

    I hope that helps! Thanks for stopping by!