The Effects of Change in Corporate Decision Making on Market Research
I have argued that change in the marketing research industry is driven by changes in the corporate communication culture and in corporate decision-making protocols. The first happens frequently, and we see it every day. The second, however, occurs less frequently, but it can happen instantly and represent a sea of change. But, what will help us predict the timing or nature of this kind of change? The answer – at least the answer predicted by this model – is that change will come from developments in the greater corporate management environment, which alone has both the power and the interest to alter corporate decision-making structures, rather from change within the marketing department alone.
Let’s look at this a little more closely. What kind of information do current corporate decision-making protocols demand? This is a little tricky to answer succinctly; it seems as though it might require a recitation of all of the types and styles of MR projects that clients commission. But consider that markets as a whole are abstract entities and any analysis or recommendations about them must, out of necessity, be inferential. You can’t go out and talk to a “market” directly; you have to infer its properties. Customers – consumers and businesses – on the other hand, can be addressed directly although you may also infer much about them from various kinds of data.
Looking back at the 30-some years I’ve spent in MR, one repeated demand from clients when customers, rather than whole markets, are concerned, and, one that has only increased over the years, has been for “direct evidence” with “face validity” that bears immediately upon the decision to be made. More simply: modern corporations demand and pride themselves for demanding a certain style of evidence for “evidence-based decision making” when addressing customer-level decisions, and one of MR’s jobs has been to focus increasingly on the collection of data that plainly and, on its face, bears on the customer decision at hand.
So, following the reasoning I’ve laid out so far, we would predict that (a) any new approach that can be reasonably represented as providing more direct evidence for or against the specific customer-level decision at hand will be supported by clients, at least tentatively pending further evidence, and (b) any new approach that does not fit the model of “direct evidence” will wither on the vine unless client companies implement new decision-making protocols or new client companies appear based on different protocols.
I think this perspective helps explain the periodic rush to methods for obtaining consumer data more “directly,” “precisely,” and “scientifically” than the opinion-based methods that MR has always relied on. If, indeed, neuroscience, eye movement, facial expression, galvanic skin response, or quantum entangled ethnography were shown to be more capable of providing unmediated access to consumers’ “true,” interior experience of a product, then that approach would be understood as obviously superior in supporting marketing decisions and would, in fact, sweep the industry. This has not happened yet, however, despite repeated trials.
Will the inferential analysis of consumer behavior – the statistical modeling of customer data, browsing behavior, location, real-world shopping behavior, social media networks, and on- and offline purchasing – prove better at this? The jury is waiting and, of course, some of those “early results” for “Big Data” are tantalizing, but the larger problem seems to be that inferential statistical models are a poor fit for existing corporate decision support systems for customer-level decisions.
Senior-level corporate thinkers and decision makers express regular displeasure with their MR suppliers – and, by extension, their own internal MR departments – for failing to innovate and adapt to powerful new models for generating insight because most customer decision-making protocols favor a “direct” style of customer interrogation while MR departments continue to commission fairly traditional research designs.
What this means for the MR industry as a whole
I draw three main conclusions from this argument:
- The pace of change in MR data collection will generally match the pace of change in consumer communication technologies and norms and will be driven by new whatever opportunities and restrictions that accompany those technologies and norms. Since both are currently undergoing rapid change driven principally, but not exclusively, by mobile technology, methodological change will be both rapid and thoroughgoing. Companies that do not stay close to the leading edge of this change will be overtaken by it and suffer in the long run.
- Client pressure on MR is now and will likely continue to generally be a conservative, stabilizing force, especially for customer-level decisions. MR companies whose businesses are based on customer-level decision support will see most clients sending RFPs implicitly (if not explicitly) requiring traditional project designs using now-standard “evidence based Q&A” approaches providing “face validity.”Clients will, of course, continue to press for lower costs and shorter timelines. They may adopt “DIY” approaches quite broadly bringing evidence collection closer to the decision, and may require methods based on new consumer communication approaches as they recognize the pace of change in this area. But, radically new research approaches using new kinds of data and reliant on inferential modeling rather than direct interrogation will not occur at anything like the same pace.
- Clients that do, at some point, begin to demand that marketing decision-making incorporate and integrate a wider range of modeled consumer behavioral data may change “overnight” from supporting a traditional “evidence-based Q&A” decision model, but only if driven by top-down, wholesale corporate re-structuring of the decision-making environment. MR firms doing business with these clients may be asked to conduct research that incorporates continued efforts based on “evidence based Q&A” with “big” customer data from CRM systems, social media, purchase data, etc., or they may find themselves frozen out by new suppliers whose methods eliminate the need for traditional customer-level MR decision support research.
MR firms that do not stay close to the leading edge of “big data” integration and are not already known for their abilities and interest in this area will have little chance of negotiating this transition. But, not all companies will follow this path and those that do may do so over an extended a period of time. Still, it is quite possible that the pace of change, once established, will accelerate and become essentially universal in a handful of years as new decision models penetrate management training programs and become established in the corporate sphere.