Shanelle Mullin previously did content and growth at CXL. She’s a jill-of-all-trades marketer with a 12-year background in growth and content marketing.
In 2023, we’re all familiar with the standard “best practices” of CRO: always use social proof, always reduce form fields, never use image sliders, and so on.
As someone who believes that best practices are merely common practices, I’m always looking to test the tried and true to see how, well, true it really is.
First up? Social proof.
Quick! How many CRO “best practices” can you name off of the top of your head? I’m willing to bet the number is quite high.
Best practices are merely common practices. That’s why in this post we’re putting another “tried and true” concept to the test, just like we did with social proof.
One of my favorite UX quotes comes from Chikezie Ejiasi, Head of Studio and Design Systems at Google.
He wrote: “Life is conversational. Web design should be the same way. On the web, you’re talking to someone you’ve probably never met—so it’s important to be clear and precise. Thus, well-structured navigation and content organization goes hand in hand with having a good conversation.”
Do you remember when Slack launched? At the time, I was a diehard HipChat fan. Needless to say, I wasn’t interested in trying Slack.
I considered it nothing more than a passing trend. Now? I use it for an average of 10 hours a day for personal and professional reasons. (Sorry, HipChat.)
What’s going on here? How’d I go from loathing something to using it daily in the span of just 3-4 weeks? It’s called the mere-exposure effect, which means we tend to develop a preference for things just because we’re familiar with them.
“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital,” said Aaron Levenstein, a former professor of business administration at Baruch College. [Tweet it!]
The same is true of your data in Google Analytics. Most of what you spend your time looking at (and re-looking at) is merely suggestive.
Sites that don’t work, don’t convert.
That’s why optimizers conduct quality assurance on sites, landing pages, test treatments, email campaigns, you name it—to make sure they work the way they’re supposed to.
While it’s common knowledge that quality assurance is something you should do, not enough optimizers complete it properly. If they did, there wouldn’t be so many sites that just plain don’t work.
You’ve read about color psychology, system one and two, emotional persuasion, etc. I know you have because it’s everywhere. It’s on Forbes, Entrepreneur, Inc., HelpScout, HubSpot… you name it. Hell, we’ve covered some of these topics ourselves.
Why? Well, because many psychological triggers do, in fact work.
But there’s another side to using psychology online that almost no one is talking about: backfiring.
Psychology isn’t a magic formula that can be applied to optimization seamlessly in all scenarios, despite what many self-identified experts are preaching today. [Tweet It!]
You’d like to think that you’re a completely rational person making completely rational decisions, right? It’s nice to believe that you haven’t made major life decisions based on how you were feeling.
Well, you have. Many times.
Think you’re sitting on the next big idea for a product or a product feature? Before you spend dozens of hours and tens of thousands of dollars on the idea, you need to validate it.
In other words, you need to make sure your audience is just as excited about the idea as you are.
So, how can you validate the ideas sitting in your startup notebook or your product feature backlog without wasting resources? By running a smoke test.
Propensity modeling lets us look at what people are likely to do—in the future.
My interest is in the future because I am going to spend the rest of my life there.
C.F. Kettering
When we look at data and analytics, we’re focused on the past. How did we do last quarter? What happened H1 2019? And how does that compare to H1 2018? How well did landing pages X, Y, and Z convert last Monday at 1:03 p.m.? (I’m kidding, I’m kidding.)
Data becomes more valuable when we use it to predict the future instead of just analyzing the past. That’s where propensity modeling comes in.