In the never ending conga-line of purported shiny new methodologies purported to relegate traditional marketing research to the scrap heap, “big data” has certainly captured its share of attention in recent years. There’s been an ongoing popular debate among insights professionals regarding the utilization of behavioral data (BIG DATA) as a surrogate for or even a disruptor of traditional market research. The disruption argument gets the headlines, but it strikes me that the more thoughtful discussion should be about how the two complement each other.Big data has become more popular as it becomes more personal and more accessible. With easier collection and cultivation of transactional information and online conversations, marketers are able to drill down and examine what the customer is looking for, as well as their buying habits. In our sports and leisure industry work, we’ve seen resorts, casinos, cruise lines, professional teams and governing sports bodies use this data to surface current trends, and recommend specific offers to the customer. Those in favor of big data believe that if we can track what the consumer spends, what they do and where they go, that this is superior to a survey or interview, which relies on recollection.
Yet behavioral data does have its shortcomings. Quite obvious from the name, big data has extremely large files that have to be analyzed to reveal trends and patterns that reflect consumer behaviors. Big data can be so large and complex that it can become difficult to store, analyze, and transfer using traditional database and software techniques. It is also limited to those customers that readily provide access to personal information that can be linked to their transactions or other behaviors. One can also recognize that the big data approach is limited in that it gets at the what, but not necessarily the how and why. It’s also somewhat self-selecting, rather than rigorously and representatively sampled, as good traditional market research can be.
Traditional marketing research, particularly attitudinal studies, focuses on identifying factors that influence the buying decisions of consumers. Data is collected through focus groups, surveys, one on one interviews, observational research, and intercept surveys. Through this, marketers are able to find out the consumers’ likes and dislikes, as well as the magnitude of those attitudes in driving consumer choice. By conducting focus groups or in depth qualitative interviews, researchers are able to get a better understanding of the consumer and their emotional reactions. Moderators are also able to intervene, challenge the consumer, and ask any additional questions that they may have. Such face to face interaction also allows for the introduction of body language and projective techniques into the analysis, both of which yield insights that are masked or even falsely attributed, through other methodologies. In quantitative surveys, forced choice exercises, attitudinal agreement batteries and importance scales can often reveal insights that go beyond the behavior to derive motivations and even the potential for those behaviors to change, with alternatives present. These are all beyond the scope of transactional data,that is the typical byproduct of “big data” collection.
My school of thought is that the ultimate holy grail is to be able to meld and model behavioral data (BIG DATA) alongside attitudinal data (Traditional MR) thus enabling both modalities to work in concert to provide a more robust customer segmentation as well as better targeted and customized marketing communications. With both behavioral data and attitudinal data working in concert, researchers and marketers can collectively derive insights never before possible. The output is both descriptive and prescriptive, and can accrue to more efficient and better business decision making and evaluation. The power of attributing specific attitudes or communications hot buttons to a customer’s recency, frequency and monetary value of purchase is a truly synergistic byproduct of the integration of behavioral and attitudinal data. So the next time someone suggests that big data portends the end of traditional MR, it would be important to remind him or her of the complementary role that each can play in advancing marketing science and continuing to evolve the researcher’s role to one of strategic consultation, rather than simply presenting data.
Jon Last is President of Sports and Leisure Research Group, a full service marketing research consultancy serving the sports, travel and media sectors with consultative custom research. Learn more at www.sportsandleisureresearch.com.