The Hip Bone’s Connected to the Knee Bone…
Let’s get a few things about A/B testing out of the way up front:
- Changing one thing will affect other (often unexpected) things
- You’re going to screw up
- It’ll be OK, because you’re nimble and can quickly course-correct
Changing one thing will affect other (often unexpected) things
Making our KISSinsights product more robust had left us with a fairly long snippet of Javascript that we were asking our customers to add to their sites. (Longer than this paragraph.)
I’d seen in previous startups that “long chunks of code” performed badly.
(Setup:
- showed the same ‘install this widget on your site’ page – variation A was 2 lines long and variation B was 6 lines long. Otherwise identical.
- People rated A as “seems easy, I could do this right now”)
So one of our developers tweaked our code until it was a slim and non-intimidating 2 lines. Looked easy! Installation rates went up!
…and I started getting a bunch of support emails from developers. As it turns out, the “long” version had one advantage – if you were a person who cared about these things, you could scan the code and see for yourself that it was asynchronous-loading and supported both secure and non-secure web pages. Shortening the code made it more obscure, so you could no longer “see” asynchronous and https support on your own.
But numbers went up! Yes – sometimes information is hidden in averages. We were making life a lot easier for non-technical folks — the 90% of our customers who don’t care or even know what “asynchronous” means. But our support inbox showed that we had, inadvertently, made life harder for that other 10%.
So we kept the shorter code. But we added information to that page’s sidebar so that people scanning for the keywords “asynch” or “https” could easily get the information they needed.
You’re going to screw up
We had a bunch of feedback from less-technical users who were not sure they had installed their code correctly. This made us suspect that there were a lot more silent users who would just decide not to risk installing us at all. Fine, we thought, we’ll give them a button and that will give them the confidence and reassurance needed.
And, in true lean startup fashion, we built an MVP solution. It didn’t work for every single case, but it worked most of the time.
Can you predict where this is going? Yup. Even when people were clearly using the product already — i.e. of course it was working, they would click on that “verify code” button. So we created a big group of people who got a false negative and immediately panicked that they had done something wrong. Never mind that they were able to use the product – the presence of that “verify failed” message was so alarming that they were worried that something was broken and there would be consequences later.
We solved (or started to solve) the problem of “customers can’t verify their installation”. But that wasn’t the problem — the problem was “customers don’t feel confident enough in their technical abilities”, and we inadvertently made that worse. Feature pulled. Problem re-stated. New solution attempt coming soon.
It’ll be OK, because you’re nimble and can quickly course-correct
6 months into the release of KISSinsights, I found myself answering a different breed of question. Previously, our survey responses and support inbox had been centered around tinkering with the product and bug reports (pretty typical early-adopter communications) — but now, people were asking about premium features, wanting to see screenshots and customer testimonials, wanting to present to their bosses why they should subscribe to premium. Welcome to the beginnings of mainstream (or mainerstream) adoption!
“We need to add this information to the website, now,” I said.
So we did.
And our conversion rate tanked. Within days of adding the new pages, we saw our conversion rate drop by over 50%.
The homepage had a prominent “SIGN UP” call to action. The new pages did not. I’d been so eager to add that needed new content that I didn’t think about how to continue funneling those people to sign up. So, basically, almost everyone who clicked off our homepage failed to convert. Oops.
This leads me a related point: statistical significance is highly overrated. When you can tell an experiment is failing, pull the plug fast. You do not need to subject your “B” audience to failure for an extra 3 days just so your Excel spreadsheet looks better.
We commented out the links. Then we added call-to-action buttons to each new page, and only then did we add them back and start a new A/B test. It took less than a week to recover to our previous conversion rate, and since then we’ve been moving in the right direction.
Popularity: 6% [?]
