How data can be leveraged to drive growth, an Uber secret

Data, and what it represents can be the biggest edge any business can have, especially when the said business knows how to use it.

Uber’s Daniel Joubert, head of growth and consumer operations pointed to a critical point in a piece about how data has long been a critical component of marketing. When looking at history and the impacting role data has played in the instances of data-based market research we see that today, data is almost sacrosanct.

Joubert says, data informs everything from what kinds of marketing someone sees to when and where they see it. The data marketing landscape is in the midst of a sea change and marketers must adapt if they’re to put their companies on an accelerated growth path.

Joubert points to experimentation as a solution.

“It’s something that’s long been critical to our operations at Uber, not least because we’ve been very careful to put data privacy policies in place which allow us to only capture data points that are critical to our operations. So, for example, when we want to launch a new feature, we don’t do so anticipating that we’ll have a complete product straight off the bat. Instead, we think about establishing what an ideal customer looks like and experiment with the product based on that. In some cases, this might entail launching slightly different versions of the product to different users, seeing how they interact with it, where they drop off and what brings them back. This data can then be fed back into the product until it reaches a point where it really enhances the customer experience.”

We agree that market research has value and yet over-reliance on it leaves some open to making inferences as opposed to data-based decisions.

Joubert concludes by noting how important successful experimentation is as you must know how to run marketing experiments successfully for them to play a pivotal role.

“The first mistake companies make is not to prioritize the build and design of technology that will allow them to run experiments seamlessly, across multiple teams (especially their growth and/or marketing teams), which allows them to analyze the results immediately.

“So prioritize and invest in the necessary technology. Secondly, they need to spend time formulating their hypothesis, clearly defining their primary and secondary KPIs, creating a controlled environment (as much as possible, but in the real world it will never be perfect and that is okay), thinking about execution before launch, and testing one hypothesis at a time.”

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