The Right Data is More Important Than ‘Big Data’: Soeren Lueders PhD

Soeren Lueders PhD, VP, Effectiveness and ROI Modeling at SevenOne Media, outlines his team’s ‘questions first’ data science strategy and why focusing on the right data beats traditional ‘big data’ approaches

Marketing analytics is a key focus for German broadcasting company SevenOne Media. But while many marketing analytics teams prioritize gathering huge volumes of data to micro-target potential customers, SevenOne Media is bucking this trend.

As Soeren Lueders PhD, VP, Effectiveness and ROI Modeling at SevenOne Media, says in this week’s Business of Data podcast episode, this isn’t necessarily the best approach for all companies.

“As soon as you talk about ‘data-driven’, [people think] it’s about data collection and it’s still about collecting as much data as possible,” Dr Lueders says. “I think it’s slowly changing. And what we’re doing as well is to look at, ‘Is all this data really necessary for what we’re doing? Or, what we’re doing with all this data, is it really getting us where we want to go?’”

Having the Right Data Beats Having ‘Big Data’

Dr Lueders argues that many companies are drawn to approaches such as microtargeting because the tech companies that sell the data and tools needed to them generally have compelling sales pitches.

However, he notes that research suggests focusing narrowly on ‘ideal’ customer segments can be counterproductive.

“Traditional digital targeting is all about data collection,” he says. “So, you try to get as many data as possible. You try to build groups upon that data and to try to target niche markets.”

“[But] when you look closely at your marketing campaigns,” he continues. “Niche targeting or surgically targeting certain groups is not really necessary for most companies because, most of the time, your product is really available for a broad audience.”

“You can easily analyze this by yourself, if you just look at, ‘Who are you aiming at?’ and then at the end, ‘Who is buying your product?’” he adds. “If you make this analysis [and] you see that there’s a big difference, then you should think, ‘Maybe this approach doesn’t really make sense.’”

For Dr Lueders, unnecessary microtargeting causes many companies to neglect large portions of their true customer base. In the end, it’s customers who lose out, with some audience segments receiving too many ads and others being served none at all.

A ‘Questions First’ Approach to Data Science

Ultimately, the key to avoiding this kind of trap is to flip the approach that many companies take to data science. Rather than collecting lots of data first and then working out what to do with it, data-focused executives should start by asking questions about the problems they want to solve.

“The right data is the data which is necessary for the project to fulfill the task or to get the results,” Dr Lueders. “It’s very common in the market to collect as much data as possible. And then, once you’ve got data, you kind of decide what to do with it.”

“[This is], I would say, the wrong approach,” he concludes. “You should really focus on what kind of question you want to answer, and then you look at, OK, what kind of data do you really need? And you shouldn’t take more data than [is] really necessary.”

Key Takeaways

• Adopt a ‘questions first’ approach. Start with the problem the business needs to solve and work out what data is necessary to create a solution to that challenge
• Match your tactics to the business need. Analytics pitfalls such as over-targeting can harm the effectiveness of marketing campaigns, rather than help them
• Having the right data is better than ‘big data’. Storing too much data is resource intensive. Companies may benefit from focusing their efforts on business-critical datasets