The Secret Behind the Best Growth Teams
Within every growth experiment, there are so many hypotheses and assumptions baked into the smallest of details. You can sit around and endlessly discuss or explore the validity of some of these ideas or the probability of success, but you often can never tell the fate of a growth experiment until it’s pushed live.
The best sort of (in)validation comes straight from the user and not from the product managers, developers, designers, or data scientists sitting around the table prognosticating about the fate of their experiment.
It’s a common line of thinking within growth circles that it’s very tough to increase your batting average. Or in other words, it’s awfully tough to increase the success rate of your experiments. If you’re just starting out, there’s some natural low hanging fruit which have a higher likelihood of success or if you have a ton of experience working within a specific part of your product, there may be some tricks you’ve picked up over time to help increase the probability of success by a few basis points. But even in both those instances, the returns on those type of experiments eventually run dry. Eventually you have to start venturing into newer spaces to continue to raise the bar with usage growth.
If success rate is tough to meaningfully influence in the longer term, how is it that some growth teams differentiate themselves from the rest of the crop?
They tend to differentiate themselves with how they operate and function as individuals and as a team. A process that allows them to be guided by principles that informs the next set of tactics. A process that protects them from becoming too dependent on the tactics of today that’ll eventually be commoditized. Through process, they improve the efficiency of their operations on the journey toward becoming as well oiled a machine as the rapidly growing product that they’re fine tuning.
Experimentation velocity is crucial.
That’s just a fancy way of saying that the number of experiments you push out the door makes all the difference. If over time it’s incredibly difficult to increase the success rate of something, the one surefire way to increase the number of successes is by simply trying more often. For such a basic line of reasoning, this is often the secret sauce that makes some of the best growth teams hum. The best of growth teams manage to churn out dozens and dozens of experiments when others can only manage to run one from to start to finish within the same time period.
Now this isn’t to say that this is a pure quantity game. Quality most definitely does not go out the window. Quality is what steers prioritization and ultimately defines which ideas your team and your growth model indicate as the best bet to take to move whichever metric you’re trying to move.
It’s always a matter of finding the right balance. Trying for the sake of trying something only works after having carefully thought out the ‘why.’ Why is it that we think this will work? Why is it that we should pursue this experiment over others? It’s important to run through this exercise because every moment you spend toward one particular experiment is time taken away from others. And without having thought through the key considerations at play, it also becomes hard to attribute success and/or failure.
Without a well considered plan as to why you’re undertaking a growth initiative, you’ll have no clue as to how to replicate and double down on a success. Or worse, you’ll have no idea why something didn’t pan out — thereby exposing yourself to making the exact same mistake once more.
For every growth team that thinks they can skim on quality for the sake of speed, there’s a growth team that accomplishes both the best of quality and quantity that’ll eventually run laps around those that are only ticking one of the two.
Put simply — it’s a continual optimization exercise when it comes to process. It takes meticulous experimentation to find the right process that fits with your product, your team, and your company. Though it’s very much a context driven exercise, there are some principles and best practices to keep in mind when devising a process, which I’ll go into with future posts.
First thing’s first though.
Recognizing that the experiments you push out the door pertaining to your products aren’t the only things you have to optimize is often times the first step toward crafting the right process. It’s the first step to eventually being able to ramp up your experimentation velocity in a way that doesn’t skimp on quality.
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