The explosion of mobile web and mobile app usage presents enormous opportunities for consumer insights professionals to deepen their understanding of consumer behavior, particularly for “in the moment” findings and tracking consumers over time (when they aren’t actively participating in research. . .which is 99%+ of the time for most people). Insight nerds like us can’t ignore this burgeoning wealth of data—it is a potential goldmine. But, working with passive mobile behavioral data brings with it plenty of challenges, too. It looks, smells, and feels very different from self-reported survey data:
- It’s big. (I’m not gonna drop the “Big Data” buzzword in this blog post, but—yep—the typical consumer does indeed use their smartphone quite a bit.)
- It’s messy.
- We don’t have the luxury of carefully curating it in the same way we do with survey sampling.
As we all find ourselves increasingly tasked with synthesizing insights and a cohesive “story” using multiple data sources, we’re finding that mobile usage and other data sources don’t always play nicely in the sandbox with survey data. Each of them have their strengths and weaknesses that we need to understand in order to use them most effectively.
So, in our latest in a series of sadomasochistic self-funded thought leadership experiments, we decided to take on a challenge similar in nature to what more and more companies will ask insights departments to do: use passive mobile behavioral data alongside survey-based data for a single purpose. In this case, the topic was an analysis of the U.S. mobile wallet market opportunity. To make things extra fun, we ensured that the passive mobile behavioral data was completely unlinked to the survey data (i.e., we could not link the two data sources at the respondent level for deeper understanding or to do attitudinal + behavioral based modeling). There are situations where you’ll be given data that is linked, but currently—more often than not—you’ll be working with separate silos and asked to make hay.
During this experiment, a number of things became very clear to us, including:
- the actual value that mobile behavioral data can bring to business engagements
- how it could easily produce misleading results if you don’t properly analyze the data
- how survey data and passive mobile behavioral data can complement one another greatly
Chris leads CMB’s Tech Practice. He enjoys spending time with his two kids and rock climbing.
Watch our recent webinar with Research Now to hear the results of our recent self-funded Consumer Pulse study that leveraged passive mobile behavioral data and survey data simultaneously to reveal insights into the current Mobile Wallet industry in the US.