By Satish Pai, MBA (pictured right) and Annie Pettit, PhD

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A few months ago, an academic tweeted about the lack of available learnings from market research agencies about predicting market behaviours. Surely, an agency that carried out dozens of econometric marketing mix modelling studies should have discovered and been able to share quantitative patterns and learnings by now.

This was a fair request, a valid claim, and a healthy discussion followed.

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To Share or Not To Share?

One perspective was that agencies such as Nielsen BASES, Millward Brown, and Kantar have already shared some of these learnings, though not necessarily in academic journals. Much of their research learnings could be found in their own internal publications, in industry journals, as white papers on association websites, and as part of industry conferences. Seek and ye shall find.

The other perspective addressed the lack of sharing as an appreciation for intellectual property, proprietary data, and client privilege and privacy. Almost all research conducted by industry requires significant investments in terms of time and talent, as well as participation from commercial clients who share their privileged data to help test and validate such research products.

Given the significant investments required to test and validate learnings, it makes sense to recover the financial investment as early as possible. Doing so requires the protection of intellectual property (IP) to ensure they maintain their unique selling proposition (USP). Pursuing publication in an academic journal could easily prevent this from happening.

For industry researchers, the true test and validation of commercial research is not publication in academic journals, but rather success in the market with measurable financial ROI across dozens of products and categories. This external validation is sufficient, particularly since prospective clients can witness research outcomes in the marketplace themselves or follow-up on testimonials from satisfied clients.

The academic researchers, however, felt that any research learnings should be subject to the academic process of peer review prior to publication in either academic or industry journals. Peer reviews require multiple experts within the field to scrutinize the methods and processes to ensure quality standards were upheld.  They argued that since agencies generally do not do this, their research isn’t validated and doesn’t pass academic rigour.

The conversation concluded as both perspectives had merit.

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Where Should Research Results Be Shared?

There soon followed another Twitter conversation wherein a media agency head wanted to share their agency’s learnings on marketing ROI. They asked for suggestions on how to share those findings in an academic journal.

Many academics pitched in with advice. The popular suggestion was that the agency should instead try out industry forums like ARF, ESOMAR, IIEX, and MRS. Those forums would be quick to publish and offered an excellent platform to reach the industry.

Despite the original request, there wasn’t much encouragement to publish in academic journals. The agency was warned that the process from submission to publication could take as long as 18 months (though with edits and revisions it could take up to 3 years). Further, journals seen as prestigious have rejection rates as high as 95% meaning that even great quality research may not be published. Along with these warnings to avoid academic publication, several journals that covered the areas of interest were suggested, along with ideas on how to go about submitting.

The contrast between these two discussions was striking. The first discussion was grounded in a premise that industry learnings fall short as the commercial vetting process isn’t the same as the academic vetting process. The second discussion was a realistic admission that sharing industry learnings via the academic route would entail several challenges and ultimately might lead to the learnings never being shared.

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Where Should Researchers Publish?

Stepping back, it’s interesting to see the variety of publication sources that marketing and affiliated industries use today. There is social media (e.g., Linkedin, Medium), dedicated media (e.g., Adweek, Admap, Marketing Week) as well as industry publications, dedicated channels, and conferences.

Mainstream media also offers considerable opportunity. Long-form columns in diverse publications such as The Guardian, New Yorker, and Financial Times can have greater impact and currency, and some would agree that they offer the best viewpoint on industry developments and learnings.

Further, there are a few publications, such as Harvard Business Review, that have bridged the gap and offer opportunity to both industry and academics. If an academic or industry researcher were to publish in such journals, they could be assured that a good number of projects from paying clients would ensue.

In the end, however, it would be fair to say that mainstream media dominates by far, and outdoes the limited impact that both academic journals and industry publications have on marketing and related industries.

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Where Do We Go From Here?

These discussions demonstrate an ongoing divide between the working lives of academic and industry researchers.

Is there one best vetting process to identify rigorous research studies that generate valid and reliable outcomes? Clearly, there is merit in both peer review and external validation.

Is a publication process with high Type 2 error rates (rejects many great papers) preferable to a process with low Type 1 errors (accepts some poor quality papers). Again, there is merit in both being assured that every result has been validated, and preventing the loss of potentially important findings.

Academic and industry researchers are on the same team. We strive to better understand the inner workings of consumers and markets but, we do so from within different contexts. Our target audiences are different – corporate end clients or other academics. Our definitions of prestigious career achievements are different – multiple Journal of Marketing publications or multiple ESOMAR awards. The KPIs that determine our raises and promotions are different – publish or perish, or monetize or perish.

Let’s continue the discussions and let’s keep the gate open.

Satish Pai, MBA is a freelance consultant, author, and PhD Candidate who specializes in advertising, branding, strategic management, and insights. He writes the Insights about Insights blog and can be found on LinkedIn and Twitter.

Annie Pettit PhD CAIP FCRIC is the Chief Research Officer, North America, at E2E Research, an ISO 27001 certified, ESOMAR corporate member. Annie is a marketing research author, blogger, and regular conference speaker. She can be found on Linkedin and Twitter.

On March 31, 2021, ESOMAR hosted a flagship series webinar on trust which was moderated by Fiona Blades from MESH Experience and Maya Kantak from Disney Parks.

The speakers defined and described trust in a number of ways. Paul Neto described it as “consistency over time with positive experiences.” Jeff Marshall and Rogier Verhulst shared that people who trust a brand are more likely to defend it, advocate for it, buy from it, and stay loyal to it. On the other hand, they explained that people can trust a company because they do what they say they will do but, at the same time, they might not trust other aspects of the business. Rob Key clarified that having trust with the brand or the company doesn’t equate to them being right or wrong, or good or bad. For instance, we trust that Amazon will deliver our package tomorrow but we might not trust how they treat our data.

Ann Constantine shared that in their company, they build trust from the bottom up through a consultancy process of creating ownership with the people who implement those processes every day.

Paul Neto discussed trust as it applies to the research industry. Right now, only about a third of people trust market research. The consequence of insufficient trust is that a third of people will refuse to participate in research and a third will limit the information they share. By building trust, researchers and marketers can unlock more consumer data. We need to be more transparent about the research experience by telling people what’s happening with their data, why they were screened out, and why the survey and incentive weren’t the length they expected. We need to step away from privacy by compliance and move to privacy by design. When we don’t meet these basic expectations, we lose trust and we lose valuable data. An interesting idea Paul raised is whether our attempts to improve the research experience are simply patchwork fixes. Perhaps if people trusted us more, we wouldn’t have to enforce shorter surveys or worry about mobile-first designs. People would trust our words and follow our advice.

Nicolas Pochart shared a fascinating example of GSK’s  “Consumer Closeness Program” wherein their research & development scientists spoke directly to consumers using virtual qualitative tools. Though they didn’t see any cost savings and it was actually extra work, talking directly to consumers was a huge success. The scientists were nervous ahead of time because they’d never talked to consumers before. However, they enjoyed the experience and confessed they will remember those consumers’ words forever. It changed how they think about their work. In 2021, GSK will have 500 R&D scientists talk to consumers. It won’t replace their regular qualitative research, but it definitely helped to put consumers at the center of the conversation, it created empathy with the scientists, it helped them understand consumer language, and it was vastly more impactful than receiving a 200-page PowerPoint file.

Jeff Marshall and Rogier Verhulst shared how they measured trust at LinkedIn. In 2020, LinkedIn registered the most digital trust among social networks. This trust is at least partly because of the individual authentication that is built into the network. People have to behave well to ensure their career and company are successful. Further, LinkedIn doesn’t allow open APIs and they don’t share their data with third party publishers. To measure trust, they conducted a major research study using narrative analytics and machine learning models to discover the best trust metrics. They followed that up by building a trust tracking program with interviews, focus groups, and surveys. The model is very important because it allows them to identify up and coming problems and be prepared to resolve those problems before it becomes too difficult. This is particularly important because of halo effects – when another social network experiences a trust issue, it can easily be reflected onto other similar brands.

Duncan Southgate and Gonca Bubani shared their thoughts on trust in the media. They’ve identified that trust is correlated with purchase and the growth of a brand’s value growth over time. Right now, traditional media, like TV ads, receives the highest trust scores but it’s still very low. When it comes to media channels, Google is the most trust media channel followed by YouTube and Instagram. As we’ve heard so often, people feel the media is biased. A single opinion can have extremely far reaching implications quickly leading to a loss of trust. Media can improve their trust scores by being more relevant, useful, authentic, innovative, fun and entertaining, and ensuring advertisers using their platforms are trustworthy.

Speakers and topics from this webinar included:

• Ann Constantine, Direct Line Group: From Top Down to Bottom up: Transforming Direct Line Group’s Measurement Approach
• Duncan Southgate and Gonca Bubani, Kantar: Trust in Media – The New Publishing Battleground
• Jeff Marshall, Protagonist and Rogier Verhulst, LinkedIn: Building and Measuring Customer Trust at LinkedIn
• Nicolas Pochart, GSK Consumer Healthcare: Transforming our Organisation Through Consumer Closeness
• Paul Neto, Measure Protocol: Exploring the Use of Trust Principles to Unlock the Next Generation of Consumer Data Collection