As someone who has spent most of my career in the data space, essentially behind the scenes, I find it funny that this self-proclaimed “data geek” is in the spotlight more now than ever. These days, one can’t read an article or have a marketing conversation without the topic of data coming up. It’s one of the hot topics du jour, and yet 60% of marketing decision makers say they struggle to access or integrate the data they need.

In a lot of cases, people turn to more data as a solution, but the reality is that more is not always better; it’s just more. For some, more data leads to analysis paralysis, where decisions are never made. For others, data replaces instinct, historical knowledge, and one’s “gut.” At the end of the day, it’s all about finding the right balance.

Data can be extremely useful but only if it’s the right data—the most meaningful data. Meaningful data drives meaningful media.

I began my career in the digital space right around the time that ad servers were being created. The industry spotlight quickly turned to digital and digital data because it meant that we could finally measure consumers’ engagement with media and its impact on behavior. I remember we looked at every metric we could. We analyzed CTR (Click Through Rate), bounce rate, page views, unique visitors, pathways, dwell time, hover time, video views, completion rate, etc. The list goes on and could take up this whole page. And at the end of the day, we had no idea how the campaign performed because there was too much data. We needed balance.

Measurement plans and primary KPIs (Key Performance Indicators) were among the best things that came out of this barrage of data. It forced us to make informed decisions about the single KPI that drove business value, which became the only thing we optimized and measured success against.

Next came third-party data. Third-party data wasn’t born with digital; we’ve always (and I say always as a relative term) had syndicated research that helped us understand consumer behavior based on what those consumers told us. It is sample-based and modeled out to the general population, and it provided a lot of great value, even to this day. However, with the creation of the internet and cookies, companies realized they could collect data on consumer behavior without consumers having to actually tell us anything. We can infer everything from this data,—from age and gender to intent and interests—and we can use it to refine our targets and media.

But that data has a cost. Not just a tangible CPM (Cost Per Thousand [impressions]), although that is a real factor, but also a cost of narrowing our focus so much that we create too much of a niche. We could miss out on all the people we thought would never be consumers of our products, and, in turn, they wouldn’t learn about us because they’re outside of our cookie pool. Again, we need to find balance.

Meaningful data is another term for finding that balance. It means identifying the right data sets, at the right price, which allows us to understand our consumers and find them wherever they are. This data is not throwing everything we know at a wall and hoping it sticks; it’s about applying rigor to data selection and measurement, so we can ensure what we’re doing both resonates with our consumers and drives our business value. Meaningful data is what drives meaningful media.