Alex Birkett is a former content and growth marketer at CXL. Currently, he is the co-founder at Omniscient Digital and works on user acquisition growth at HubSpot. Follow his writing at alexbirkett.com.
Are you sold on the idea that it’s beneficial to understand your customer personas?
Hope so. If not, it’s guesswork. When you know who your customers are, where they are, what they love, and what they hate, you can market to them much more effectively.
It’s a cultural trope to “want what you can’t have,” but it’s also a principle based on decades of psychological research.
That principle, scarcity, is incredibly powerful in marketing, persuasion, and conversion optimization—when done right, especially in a free market with limited resources. If people believe that they’ll be missing out on something, they’ll be prompted to act more quickly to get it.
If you’re not following form design best practices, you’re leaving a lot of money on the table.
While forms aren’t the sexiest part of conversion optimization, they tend to be the closest to the money—the macro-conversions. Spending a little time optimizing forms can be some of the most important optimization work you can do.
Of course, best practices don’t work the same on all sites. It’s contextual. But generally, implementing form design tactics that work more often than not is a good way to get started.
You put tons of time into creating your product, experimenting with acquisition channels, and honing your messaging.
Yet here I am, about to tell you that consumers are often swayed by such subtle nudges as the order in which you present your products, or the “serial position effect.”
A/B testing splits traffic 50/50 between a control and a variation. It’s a new term for an old technique—controlled experimentation.
Yet despite all the content about it, people still test the wrong things and run A/B tests incorrectly.
When should you use bandit tests, and when is A/B/n testing best?
Though there are some strong proponents (and opponents) of bandit testing, there are certain use cases where bandit testing may be optimal. Question is, when?
At a certain point, the results from your A/B testing will likely slow down. Even after dozens of small iterations, the needle just won’t move.
Reaching diminishing returns, is never fun. But what exactly does that mean? In most cases, you’re probably hit a local maximum.
So the question is, what do you do now?
“What is beautiful is good,” the saying goes.
This saying stems from a belief that attractiveness correlates to other good qualities. In a phrase, attractiveness is a Halo Effect.
Of course you can see that on the surface, the logic in that saying is flawed. What’s beautiful has nothing to do with what is good. But we still associate perception and individual traits, making our judgement often inaccurate.
Heat maps are a popular conversion optimization tool, and for good reason. We leveraged correctly they are a powerful way to better understand your audience and deliver more value.
So what can heat maps answer?
In digital analytics, it’s all about asking the right questions.
Sure, in the right context, you can probably get by doing what Avinash Kaushik refers to as “data puking,” but you won’t excel as an analyst or marketer.
In addition, you’ll consistently come up short on bringing true business value to your company.