Courtney Lindau is the Head of Practice for Web Analytics and Business Intelligence at Nimble Gravity, a consultancy specializing in data science, digital strategy, e-commerce, near-shore engineering teams, analytics, and organizational strategy. Courtney helps companies track the right KPIs for their business in order to uncover actionable insights, and she’s here today to talk about data storytelling in marketing.
Our interview with Courtney began with an overview of what data storytelling is, how it’s used, and also how it can be misused.
“Data storytelling is deep analysis to uncover the ‘what & why’ of the data,” starts Courtney. “It’s essentially about uncovering the origin of the data and its purpose. Say your revenue is down, you would start to analyze the channel mix, new users vs returning users, something that you can pinpoint the ‘why.’ Once you have the data points, you can connect them and then that story tells itself. The misuse comes when people make the data tell the story they want to tell, rather than using the data as an unbiased metric.”
I then asked Courtney how someone who feels like they could brush up their data storytelling efforts would begin their work.
“The best place to start with data storytelling is to start with an audit of web analytics, making sure tracking codes are in the right places, establishing data pipelines, rudimentary stuff like that,” says Courtney. “Can we get the data we need, and are we measuring the things we need to measure? Starting with that audit can reduce duplicates and clean up the data before you need to rely on it for analytics or business intelligence.”
Making sure data storytelling is speaking directly to the audience, be that clients or shareholders or internal partners, is a point Courtney stressed.
“I usually start every project with an interview with the target audience for the data,” explains Courtney, “asking them what questions they are commonly asking their team that no one seems to know how to answer, what metrics they rely on, so we can start the process with that end result in mind.”
The conversation then pivots to data-driven decision making, and how A/B testing can provide tons of usable information and data points that can drive decision making.
“One thing that I’m absolutely in love with is A/B testing,” admits Courtney. “It gives you a really clear sense of what’s working and what’s not working. If you’re on a product team, and you have a bunch of dreams and hopes, A/B testing every product release gives you the data to check your dreams against, so you can align your work better with UX and outcomes most likely to succeed. Rather than having to retract a fancy new release or feature and figure out what went wrong, you can A/B test along the way and hopefully prevent those mistakes.”
To hear a fantastic story from Courtney about data storytelling gone amazing, a horror story about data storytelling in a dumpster fire, and to learn if Courtney prefers Gandalf over Merlin, listen to the full show at the links provided in this blog.