Understanding how to collect, organize, and then perform sophisticated analysis on consumer data to gain insights that lead to ideas for experiments, is another of the cornerstone requirements for teams. A growth team might not include an analyst as a full-time member, but rather have an analyst assigned to it who collaborates with the team but performs other work for the company as well. That was the case in the beginning for the BitTorrent team. But if a company can afford to appoint an analyst full-time to the team, that’s ideal.
A team’s data represents needs to udnerstand how to design experiments in a rigorous and statistically valid way; how to access your various customer and business data sources and connect them to one another in order to draw insights into user behavior, and how to quickly compile the results of experiments and provide insights into them. Depending on the degree of experiments a team is running, it might be possible for the marketing or engineering team member to play this role, as in both of those fields, a certain level of data analytics aptitude has become important. At more technically advanced companies, analysts with expertise in reporting of experiments as well as data scientists, who are mining for deep insight, should both play a role.
What is essential is that data analysis not be farmed out to the intern who knows how to use Google Analytics or to a digital agency, to cite extreme but all too frequent realities. Too many companies do not place enough emphasis on data analysis, and rely too heavily on prepackaged programs, such as Google Analytics, with limited capacity for combining various pools of data, such as from sales and from customer service, and limited ability to delve intoo that data to make discoveries. A standout data analyst can make the difference between a growth team squandering its time and mining data gold.
The above text is an excerpt from the book “Hacking Growth” by Sean Ellis and Morgan Brown