Best Practices Versus Practices That Work

Best practices are typically codified

after many thousands of hours of collective learning.

We rightly go looking for best practices to tap into this collective wisdom

but get disappointed when they don’t quite work as advertised.

We often miss that best practices are contextual.

What works after a thousand hours at scale

will not necessarily work at a 100 hours.

My favorite example is reducing signup friction.

Reducing signup friction makes complete sense at scale.

You’ve got a product that you know works.

Your battle is just getting people to experience it.

And you’re reasonably confident (backed by data)

that once people do, enough will convert.

At the early stages though, you need to do the exact opposite.

Making it too easy for people to try your product

drowns you in lots of feedback.

Worse, it attracts

customers and non-customers,

good customers and bad customers,

early adopters and mainstream adopters,

Each behave differently.

The result is not only lots of feedback,

but lots of conflicting feedback that you can’t easily tell apart.

Who do you listen too?

At the earliest stages,

you shouldn’t reduce signup friction, but increase it.

That way you qualify the right early adopters

with who you build the right product,

first for them, then the masses.

You can’t just adopt a scaled down version of a best practice.

You sometimes have to adopt the anti-best practice instead.