Part Two: Marketing Leaders from Sunglass Hut, Wistia, & Klaviyo on What It Really Means to be Data-Driven
Part one of this post can be found here.
Recap: For all of the trendiness behind this movement toward being more data-driven, I wonder how many marketers understand what it means to be data-driven? (Hint: It’s more than tracking a few KPIs, poking around in Google Analytics, and running a monthly report).
So, what does it mean? What does a day in the life of a data-driven marketer look like? What do they think about (and why)? How is this data-driven philosophy helping them make better decisions? And what advice would they give to other marketers who are struggling to make sense of the data at their disposal?
To answer those questions, I reached out to three of the most data-driven marketers I know:
- Chris Kobus, Vice President of Marketing, Merchandising, and Digital at Sunglass Hut
- Heather Adams, Vice President of Marketing at Wistia; former SVP of Marketing at Shoebuy
- Agata Celmerowski, Vice President of Marketing at Klaviyo
Here’s what they had to say:
Q: Can you remember a time when being data-driven had a significant impact on a particular initiative, campaign, or strategy?
Agata: A few years ago, my team was running a simple CTA test on our website — it was something like “Get Started Free” vs. “Try it Now.” Our test CTA ended up driving far more clicks, which was exciting to see. But luckily, we had our website instrumented so that we could see what happened after people clicked — after all, our ultimate measure of success was around how many people became customers, not how many people clicked.
We found that while more people responded to the new test, fewer actually ended up completing their account set up. As a result, less people converted into customers. If we didn’t have the data available to us to track “down the funnel,” we would have launched something that would have ultimately been worse for our business.
Heather: In a prior job I created my own system for attribution across channels and programs, and used this system as a primary input to help optimize the media mix and specific advertising programs.
This allowed me to tremendously scale the marketing programs while meeting or beating ROI goals. Attribution is a huge and complex topic, and I do not profess to have solved it. But what I did was not get stuck thinking I needed perfect data in order to make decisions, but rather to get comfortable with using relative data sets.
Chris: To build off of Heather’s attribution example, in the last year we introduced attribution between Sunglass Hut’s online and in-store channels. This gave us a clear picture of how digital ads were impacting store sales, and it allowed us to fundamentally change our investment strategy.
Q: What advice would you give to other marketers around how to more effectively leverage data and analytics in their everyday roles?
Heather: For me, it’s all about developing good habits. For every project, make sure you know:
- What your goals are going in
- How you plan to measure success
- When you’ll know “success” has been achieved
The key here is to have a clear way to monitor your KPIs. From there, you can use technology to automate and visualize this process as much as possible. That way you can spend more time analyzing and acting, and less time gathering and calculating.
Chris: I think it really boils down to having the courage to act — and that requires an understanding that the data will not always be perfect. It must be accurate enough, but if you wait for it to be absolutely perfect, you’ll be waiting around while your competitors soar past you. Use what you know to test into what you don’t — and then continue to optimize from there.
Agata: Being data-driven does not just mean you look at numbers. In fact, qualitative data is just as important as quantitative data, which is something that most “data-driven” marketers overlook.
There is no “data-driven” field that accepts a single input of data as valid in reaching a conclusion or making a decision, and marketing is no exception. So, the successful data-driven marketer needs to understand how to look at information that comes in from a variety of sources: campaign results, transactional information, customer behavior, qualitative research, etc.
Once you buy into that perspective, you can start to assess where your strengths are — maybe you’re better at seeing trends than you are at creating complex pivot tables in Excel — and you can start balancing those skills with training, learning, and technology.
More important than any of that is the reality that you can’t be an effective data-driven marketer if you don’t know what success looks like for your company. So, make sure you’re clear on what you’re trying to achieve first, and that you have the right tools in place to measure based on what matters to your bottom line.
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