Blockchain and Qualitative/Market Research​

News is proliferating about blockchain and its implications for market research.  It might be a way to address, even solve, market research issues like tracing and tracking of the multiple sources of data, identifying all the steps in data retrieval, ensuring against bad data, removing bots as respondents, and helping compliance with new regulations.  We might regain our trust in the data underneath the insights, increase transparency, allow the marketer to go direct to consumers by eliminating the research middle ground, and give consumers greater control over data, improving quality of respondents. Some say there is a strong potential to remedy, eliminate, and solve the issues of fragmentation of escalating research techniques. From the GreenBook webinar on August 23, 2018, there is strong emphasis on trust related to blockchain.  M. Andreessen is quoted: “Blockchain is the ‘trust protocol’…blockchain enables trusted transactions directly between two or more parties, authenticated by mass collaboration and powered by collective self-interests, rather than by large corporations motivated by profit.” Many inflations and paradigms in research are operating in contemporary marketing—there is an obsession for new research techniques yet increased skepticism that the data is good… desire for more control over data yet slippery commitment issues from team members.  Client companies get excited about a highly advertised methodology at the outset and then are unable to follow though in interest because of its complexities and distractions. The mind of the marketer is different from the mind of a researcher; it’s easier to take shortcuts in DIY research when you don’t really resonate to the innate research process and only want results, fast.   Researchers have the inherent need to debrief the ambiguities of research findings, reduce the data thoughtfully after we have first expanded it, re-conceptualize the purpose of a study at the midpoint, spot inaccuracies and weird, spooky, or uncanny developments that spell out a major error, winnow out flash-in-the-pan superficialities from highly tested methodologies that have earned our respect, get trained and gain experience in a method, and increase transparencies without causing the consumer to build up defenses that inculcate new emotional defense systems. In a recent seminar on blockchain and market research, certain benefits for each party in the interrelationship are touted and explored.  For instance: Suggested benefits for the consumer with blockchain:  Consumers can stay involved with the research and data results. This makes the process seem true, relevant, and engaged. But, research gathering is inherently time consuming, consumers are busy, and analysis goes through a shatteringly lengthy, boring stage or two before it gets to interpretation; the best research punctures our egos and tells insights about ourselves we don’t want to know. Good research does not always make our motivations, narratives, and opinions look good to others.  Optimum research uncovers shadow needs and wounds as well as light-filled wishes and positive discoveries. So, will consumers have the time, interest, strength of character, and emotional honesty to stay involved with the data and research process? Will they permit their darker side to become known? Suggested benefit for the researcher with blockchain:  Blockchain may allow us more trust in the data and the ability to follow the data at every point.  It’s said that instead of being nervous about using data that might be corrupt and substandard, we researchers can be bolder. We will know that those who contribute to the data have specific checks, permissions, and have gone through validating identity structures. This will help us relax more and do our work in a more streamlined, trusting fashion. Since the industry is increasingly fragmented and there is proliferation, propagation, and intensification of research techniques, many of which are technology-driven as opposed to tested by social scientists, maybe blockchain will automatically fix this overwhelming aggrandizement. It’s as if a huge picnic table of indiscriminate food brought by unknown providers is laid out on a big lawn and everyone who’s hungry can go get whatever he wants on the basis of taste buds, quality, and perceived value, without having to compromise trust.  But, wait a minute, suppose the market research questions are still in the conceptualization stage? Suppose we don’t yet know the competitive framework? Suppose we don’t know what category we’re playing in? Suppose we can’t agree on indubitable questions? Suppose we need a pretest stage or two to figure out what we’re doing? Suppose we are noticing discrepancies between multiple methodologies and their disparate findings? Suppose the research disagrees with the original opinions of top management? It is a maxim that the more thorough, rich, and multifaceted the data, the less direct, obvious, and clear are the resulting data and the greater is the need for careful analysis, skillful reduction.  It is frequently the experienced, research team who struggles, smiles, advances, despairs, exalts, goes backward, goes ahead again, and generally pulls out their own hair as they massage the data, allow for ambiguities, reversals, and paradoxes, and then come up with breakthrough results.  A quant questionnaire with thousands of undifferentiated respondents that has only three yes-no-maybe questions may be easier to analyze than a client-involved, researcher-led deep-dive qualitative, multiphased, mixed methods, longitudinal methodology about emotional motivations and behaviors of segmentation with a smaller number of algorithmic consumers over a three month period with multiple researchers in several fields, and key variations like ages, segments, and usage categories.  But which findings will be more valuable to the marketers? It depends of course, but most likely the longitudinal process. Blockchain is an open decentralized data of transactions involving value.  But value in a single consumer’s mind can change from moment to moment depending upon context, mood, income, other actors, wants, and perceived needs.  It is this shifting of value that qualitative researchers are trained to notice, become aware of, analyze, and intuit as motivational factors. Suggested benefit for the marketer with blockchain:  Theoretically with blockchain, companies, brands, and marketers may be able to reach their consumers directly.  The middleman researcher can be fired; done; that was easy. But without the researcher who is trained and innately positioned to have deep unconditional regard and empathy for the human sides of consumers, the same knowledge, depth, objectivity, subjectivity, transcendence of data, and intense level of ethics may not be guaranteed.  If the marketer can go straight to the consumer and the consumer can answer the marketer’s questions directly, will the consumer only state what he or she feels it’s appropriate to answer? Will they get bored and stop answering if the inquiry is long or irrelevant? Will they balk and give false data because being asked questions by those who serve to benefit by those answers becomes obvious quickly? Very few like to be grilled by someone or something who is obviously not objective, might abuse trust, and are transparently…opportunistic.  Even for trained researchers, it can be hard to ask totally open-ended questions if one has a vested interest in the answer. The consumer can rapidly discern when the questioner (the marketer within blockchain) is asking leading questions without the objective middleman (the researcher eliminated by blockchain). Of course, as a qualitative researcher who is a trained cultural anthropologist and depth psychologist who leads large-scale market research efforts and knows what is entailed under the surface, I and others like me don’t want to be eliminated by blockchain. We don’t even like to be called middlemen. So, I guess this post can be considered suspect or a crusade for the cause of maintaining researchers within the consumer-client research paradigm.   We may be in a totally new research ecosystem, but this ecosystem is still not a fait accompli.  No one’s fate is being sealed, yet, by blockchain. Blockchain still needs to establish identity structures and do validating research about the authentic nature of data trust so that we can better understand the benefits.  When we’re talking about the need for good data, let’s see when there’s significance to having a trained observer research team spearheaded by the qualitative researcher or anthropologist with the ability to dispassionately look at what consumers actually do, don’t do, feel, don’t feel, say, and don’t say. And, let’s figure out together where are the points of definition, devaluation, aspiration, reality, confusion, polarization, ambiguity, and potential transformation.   In some ways, the advent of blockchain makes qualitative research seem more radically necessary than ever before. What are the true advantages of no intermediaries, let’s learn who the actors are, see if trust in your specific data is increased or decreased, and begin to differentiate by the specific marketing issue and nature of the explicit inquiry whether blockchain can transform a particular inquiry for the marketer, the brand, the product, or the consumer need…for the better.   ​

The reemergence of qualitative research​

I liked the article below about how big data is necessitating the reemergence of qualitative research. It’s from today’s 7-14-2016 blog from ThinkNow, an Hispanic panel group who write some great articles on miscellaneous research topics. It mirrors a situation at the recent IIex 2016 conference in Atlanta, a 3-day conference filled with insight innovation from all over the world, in which a key presenter said (about qualitative work I had conducted for their recent multiphase project for International Data Corporation and Rackspace): “I’m falling in love again with focus groups. It was wonderful to listen to high level decision makers sit around and intensely talk about their perceptions, misperceptions, confusion, and knowledge, back and forth, right in front of us in a facility. I understood so much that I couldn’t have learned with online or mobile. This jump-started the remainder of the project.” Here is Roy Kokoyachuk’s article from ThinkNow in its entirety:  As Big Data Rises So Does the Need to Talk Directly to ConsumersWhen big data came on the scene a few years ago there was a lot of hand wringing in the market research industry about what the future was going to look like if all online consumer data was going to be available for marketers to analyze and exploit. In-person qualitative research, with its old-school approach and methodology, seemed to be a good candidate for extinction in an age of pixels and clicks. Why would marketers want to talk to consumers if they could see their every purchase and eavesdrop on their online conversations? Wouldn’t consumers reveal their likes, dislikes and motivations for all to see and marketers to exploit? Now, in mid-2016, we have a pretty good sense of how things are shaking out. While it’s true that we share quite a lot about ourselves online, it’s not always the type of information that marketers can use. While Amazon, Google, and Spotify do indeed know a lot about our purchase behaviors, browsing habits and music preferences they don’t know why we bought something, looked something up or chose a certain song to listen to. All the information Amazon, Google and Spotify work with was created after we’ve searched for or clicked on something. They have a limited view, however, as to why we went to their sites in the first place. Without the ‘why’ marketers are left guessing as to how to incite future purchases or gauge interest in future products. The ProblemThe ‘why’ was supposed to come from the social listening side of the equation. Facebook, Twitter, et al were going to tell us what motivated people to do what they do. While they do uncover interesting insights there’s something coloring many of those findings – social acceptance and vanity. A significant predictor of whether an online conversation approving of or disproving of a product or service is often-times the content of the first comment in the string. Subsequent respondents then echo the initial sentiment to gain social acceptance. Additionally, the comments and images we post online for all to see are not necessarily reflective of our real selves. If they were, a large proportion of us would be walking around staring into mirrors, making duck lips and tilting our heads just so. Our ‘better’ online selves are happier, enjoy life more and have more ‘friends’ than our offline selves. The problem for marketers is that in 2016 it’s still the offline self that spends money on products and services. Amazon can set their algorithms in motion once we’ve clicked on something or made a purchase but until we do they’re clueless as to what to say to us. The SolutionWhile everyone was distracted by their glowing screens something interesting has been happening in market research – old school qualitative research has been making a comeback. After a lull in qualitative research which occurred while consumer insights teams absorbed the new tools they had at their disposal and figured out what they could and could not do, we’re experiencing a resurgence of interest in ethnographies, focus groups, shop-alongs and IDI’s. In a nod to the new online world, some of it is happening online but a lot of it is reverting to face-to-face methodologies. We recently conducted a series of focus groups among individuals without health insurance. Not having health insurance is not something people brag about on Facebook. In fact, one might get the impression from online posts that Americans are perpetually smiling, spend most of their time on vacation and are ‘living the dream’. Listening to group members describe their struggles with health insurance access, fear of financial catastrophe and concerns about their and their family’s health, one realizes that this type of conversation can only be had in-person. Several group participants hugged the moderator on the way out and thanked him for allowing them to share their feelings on the topic. The moderator had done little more than listen attentively and probe for more information but an intimacy was achieved in those groups that felt intensely human. Of course, not all focus groups revolve around such weighty topics but a good moderator can help people uncover the inner motivations for their preferences. An online post can tell us “Mustangs are cool!” but it doesn’t usually reveal that “I want a Mustang but work in a law firm where most people drive Audi’s and BMW’s so I’m kind of embarrassed by wanting one.” Further probing might lead an ad agency to have an ah-ha! moment that could lead to an ad campaign that drives buyers to showrooms. Knowing that someone clicked on a picture of a Mustang is interesting but will only get you so far in developing resonant marketing messages. As long as marketers are selling products and services to human beings there will be a need to understand them on an emotional level and thus a need for qualitative research moderated by humans​.  About the author: Roy Eduardo KokoyachukRoy is a Managing Partner at ThinkNow Research. He started his career at Warner Bros. Media Research. A desire to pursue multicultural market research full-time led him to join a full service Hispanic & multicultural market research company, in 2003 as Vice President of Advertising Research. He became Executive Vice President in 2006 and opened an operations center in Tijuana, Mexico and directed the company’s entry into online research. In 2009 he initiated the creation of the first nationally representative opt-in market research panel of U.S. Hispanics – CadaCabeza. This panel broke new ground in panel building by focusing on the recruitment of Spanish speaking Hispanics as well as the English speakers typically found on online panels. He co-founded ThinkNow Research to further pursue his passion for multicultural consumer insights. Posted in Analysis, and qualitative research, Big qualitative and big data, Methodologies and research findings, Qualitative market research | Leave a comment »

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Big Qualitative and Big Data

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