Are Big Data and survey-based research destined to be enemies? It’s a much-discussed question with huge implications for consumer insights. Will inconceivably large packets of passive data from consumers’ journeys across websites and on their smartphones reveal more about them than they can possibly reveal about themselves when they answer researchers’ written questions?
It seems more productive to reframe the question. When it comes to Big Data and surveys, can they be used to complement each other to achieve “both-and” insights solutions instead of clashing in a battle of “either-or?” First, here’s the gist of what Big Data does:
– Amasses incredible amounts of consumer information from multiple digital touchpoints and passive inputs.
– Makes inferences from the data to model consumer behavior.
And here’s what Big Data omits:
– The uniquely human dimension – the “why” and “how” that form consumer sentiment and drive the “what” in what they do.
– Thoughts, feelings and motivations, expressed by the people who have them.
Now let’s look at how Big Data and survey data can be combined for a solution to one particularly thorny research challenge: measuring mobile ads’ effectiveness.
– First, identify a bucket of Big Data that will be relevant to the task of ad measurement.
– In this case, it’s a huge list of the unique codes that identify each mobile device.
– Next, obtain the identifying code for each mobile device that received the ad.
Now you can make Big Data and survey panel methodology work together.
– First, match the identifying codes for all the devices that have received the ad (a large bucket of Big Data), against the codes for phones used by members of a proprietary, app-based consumer research panel.
– The matches from these two lists make up the ad-measurement study’s pool of survey-takers. It represents a synthesis of Big Data (the mobile device codes) with technologically advanced mobile survey methodology (recruitment and engagement of a validated, proprietary panel, exemplified by the more than 1.3 million active U.S. members who use MFour’s Surveys on the Go® research app to participate in consumer research on their phones).
– Because each panelist has provided detailed demographic data upon sign-up, advertisers can see who these validated ad recipients are — and gain important insights into whether a mobile ad is reaching the right audience.
– Then, to measure the ad’s effectiveness, the advertiser can survey verified ad recipients and ask about awareness of the ad, the brand and the product, along with the consumer’s interest in shopping and buying.
– Advertisers can take the process even a step further, by recontacting the initial respondents who said they intended to shop. After a period of time has gone by, send these panelists another survey, asking whether they did, in fact, shop for or buy the advertised product.
There are many other ways in which turning Big Data and mobile-app survey data into allies can yield illuminating insights. For a productive conversation about how combining the two kinds of data can meet your specific research needs, just get in touch by clicking here.