Startups have access to more data than ever before, and when used efficiently it can provide valuable insights. However, given the sheer volume of data available, there is also the danger of becoming distracted.
In a recent interview with First Round Review, HotelTonight chief data and strategy officer Amanda Richardson shared four “cringe-worthy” mistakes often made by startups when it comes to using their data.
The first of those mistakes is not clearly articulating the goal you want to achieve when it comes to analysing and acting on data, and instead simply keeping track of metrics as they happen.
Richardson stresses the need for startups “to start with a specific question to answer or hypothesis to investigate”.
“A lot of times, people will launch a product and then say, ‘how’s it doing?’ rather than saying, ‘our product goal is to convert from this to this. Or grow the top of funnel or move the bottom of the funnel. Or increase our revenue per user’,” she observes.
Richardson says before every project starts “the discipline is to have something written down”.
“It’s that old SMART acronym: specific, measurable, achievable, relevant and timely,” she says.
Having a precise goal written down will help to maintain a more specific focus, and minimise the risk of getting sidetracked by other metrics that don’t directly relate to the startup’s overall objective.
“When you ask data people how a product or feature is going, they’ll almost always come back with a list of fun facts,” Richardson says.
“But don’t confuse those secondary metrics with your top metric.”
Richardson also highlights to the importance of startups having the right team structures in place when setting out to achieve goals.
“It’s the job of the leader to say, ‘we’re going to climb Everest’,” she observes.
“It’s the job of the team to figure out the best path up Everest and the requirements for each team member. But particularly at an early-stage company, it’s not fair to leave it to the product manager to set these strategic priorities.”
Read more: How alcohol delivery startup Tipple is using its data to increase orders by 54% per year