Over the past five years, I’ve analyzed data on a wide range of products from lip balm to dog food, from potato chips to kefir. And while categories of interest have changed, my general best practices for analyzing the data remain constant. Data can be complicated and challenging, but, if you know how to harness it, transform it, and understand its meaning, it can be a game-changer with immense value to your business.
As a part of SPINS’ Brand Growth Solutions team, I work with clients every day to bring the data to life and make it actionable for their businesses. While I can’t reveal all of my team’s secrets in this post, I will lay out three insider tips that we use to transform data on a daily basis.
Because there’s often so many factors that can drive business, it can be overwhelming to know where to start digging for answers. I find it helpful to generate a list of mutually exclusive and collectively exhaustive (MECE) probable hypotheses to easily identify the top contenders and eliminate those that are less likely. This planning and forethought always saves me time because it provides a targeted list of analyses to consider, and every analysis assists in either proving or disproving the most likely hypothetical causes. By setting myself up for success on the front end, I find more time to generate insights and implications on the back end.
It always helps to understand the whole picture. It’s not enough to say that a brand is growing 10%. I always make data points relevant to my audience by benchmarking it back to something. Is that 10% accelerated or decelerated from the prior year? Is that 10% higher or lower than the category? Is that 10% better or worse than projected estimates? The easiest way to make data mean something is by making a comparative “than” statement.
Visuals are the KEY to bringing data to life and telling the story. As data analysts, it’s our job to make the numbers meaningful. We’re doing the data a disservice every time we copy and paste a raw data chart from Excel onto a slide. To mitigate this, I find it most helpful to ask myself, which hypothesis will I demonstrate here? (See Tip #1.) Then my follow-up question is, what kind of chart or visualization is going to best represent this data and make the point clear? The simplest rule to follow is to visualize one point per slide. Finally, when I make the point with a visually descriptive chart, I always highlight the insight for my audience, as well. In addition to the charts and visualizations, I know it’s important for me to narrate the story in the data to help my audience fully understand each insight and implication.