"Someone sign up on my service and does something on my service that's expected of them to do?" BOOM! Leading indicator... No shit Sherlock...
As a marketer I'm getting tired to this buzz word shit around growth hacker...
For instance, when signing up to Facebook, there is a bunch of stuff they want you to do: add friends, invite people, add content like photos, and come back on day 1, day 2, and so on. It turns out that it's the first activity that is more predictive of future engagement than the others, and specifically 7 friends in 10 days is an important threshold. You can't figure that out from your intuition alone, and you definitely can't get the values of # of friends in # of days just by consulting your intuition, or your sense of what's obvious.
At the same time Chamath from Facebook was keen to point out that there was nothing mystical about what the growth team at Facebook did. He said the best way of describing what they did on the growth team is that they:
- Measured things
- Tested things
- Tried things
His main take-away was that one should be extremely rigorous and analytical when thinking about what drives engagement, and not rely on your gut, or company lore.
Except the end result is usually the exact same.
A wildly inaccurate model for the sole purpose of impressing advertisers|investors|stakeholders with fancy, meaningless charts.
The conclusions you can draw from these models are either utterly obvious, or false. I'm looking forward to hear about a single example of the opposite.
They were also at pains to mention that you cannot A/B test your way to a great product. You need deep insight and intuition to build a great product. But once you have a great product, you can help it grow faster by being rigorous about optimizing the drivers of growth.
"If, on a graph, the plotted data does not match the
initial hypothesis, make the line fatter."
-- J. Meals
I'm still waiting for an example where such a model predicted something non-obvious.
Did Myspace have growth hackers?
I suggest that we respectfully agree to disagree.