GRIT Insights Practice Sneak Peek: Adoption of Emerging Methods

Editor’s Note: Many people eagerly look forward to the release of a new GRIT Report. In anticipation of the latest Insights Practice edition, here’s a sneak peek by Ray Poynter on the emerging methods in the market research industry. Ray’s summary, as well as more detailed findings on a host of other topics, will be printed in the full report. 

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In looking at what research approaches/ methods are in use or under consideration it is important to remember that the GRIT sample is not a representative sample of the market research population. The GRIT sample tends to be drawn from those more engaged with the future of research, so the ‘in use’ figures will tend to be higher than for the wider market research population. The GRIT Report’s key usefulness lies in the relativities between the approaches, the trends over time, and the differences between key groups (such as the Buyers and Suppliers of research/insight).

The 2019 questionnaire has been updated and the changes are outlined in the longitudinal analysis section.

Adoption Traction

Table 1 shows the 19 approaches included in the 2019 GRIT study ranked in terms of how many people said they were already using these techniques. Remember, ‘using a technique’ does not necessarily mean using it heavily; it may mean it is sometimes used, and sometimes not. The table is ranked from highest to lowest in terms of ‘In Use’.

At the top of the list is Mobile-First Surveys, with 56% saying they use them. However, in 2019 it is worrying that 20% of people only list Mobile-First Surveys as being under consideration. For some time, it has been necessary to accommodate mobile devices for most projects, and it is widely recognized that Mobile First is the best way of doing that. The 23% who are not in the use or considering groups include 15% who are not sure (perhaps they are not involved in the detail of surveys), and 6% who are not interested (perhaps their company does not use surveys – e.g. pure qual, pure big data, or pure social media). But the 20% who are ‘Considering’ Mobile First should probably get a move on.

In addition to Mobile First surveys, five other methods are in use by at least 40%, and these divide neatly into two extremes. Text Analytics (50% using), Social Media Analytics (50%), and Big Data Analysis (44%) are all about quant, computer programs, and analytics. On the other hand, Mobile Qualitative (48%) and Mobile Ethnography (41%) are all about using new tools to enable qualitative insights. This suggests that both analytics AND qual are strong. The next group of approaches is perhaps best thought of as established niches. This group ranges from Research Gamification (25% using and 29% considering) to Micro Surveys (36% using and 27% considering). This group covers a range of techniques, methods, and philosophies. The bottom group of seven approaches, ranging from Biometric Response (12% using/16% considering) to Passive Data Measurement (19% using/26% considering) are a mixture of small niches, future trends, and perhaps ideas already on the way down. The two techniques with the highest ‘Under Consideration’ (and not using) figures are Text Analytics (31%) and Chatbots (31%). Text Analytics has been growing its ‘Use’ figure over the last five years and seems set to grow further. Chatbots were added to the GRIT questionnaire for the first time this year, and they seem to be set to grow.

We also read the open-ended suggestions for emerging techniques that were not part of the existing survey. There was only one technique that stood out for inclusion and that was AI/Machine Learning – which is covered in the investigation into which techniques are real and which just buzz. A word cloud of the suggestions is shown below.

Short-Term Stability, Long-Term Winners

Table 2 shows the ‘In Use’ data from 2014 to 19W2, a period of five years. This longitudinal view of the data highlights some of the changes to the GRIT survey, showing items that are no longer asked, and the three new items asked in 2019 (Passive Data Measurement, Causal Analysis, and Chatbots).

The changes over the last 12 months column shows that very little has changed in the last year, and this is normally the case in our industry. The one big change over the last 12 months has been the increase in people reporting they are using Applied Neuroscience, up from 20% a year ago to 29%, and it is up 16 percentage points since 2014.

However, behind the short-term stability, there are some interesting long-term trends. Text Analytics, Mobile Qualitative, Big Data Analytics, Mobile Ethnography, Micro Surveys, and Applied Neuroscience are all up 10 percentage points or more over the last five years. These are the real winners and most of the items near the top of the table are there because they have grown in usage over the last few years (unlike Social Media Analytics which was already in widespread use in 2014 and has only grown modestly since.)

By contrast, there are a number of techniques that were only used by fewer than 20% of companies in 2014 and have not increased their footprint since, such as Biometrics (13% in 2014, and 12% in 2019). This does not mean these techniques are not providing value to some people with specific applications, but it does suggest that they are not going to be mainstream any time soon.

Buyers and Suppliers

One key split in the insights industry is between those whose main role is producing and selling insights, for example, the market research agencies, and those commissioning, buying and using the insights, for example, client-side insight teams.

Table 3 shows those techniques ‘In Use’ for both groups. The methods are sorted by the gap between Buyer use and Supplier use, with the methods that Buyers more at the top and methods that Suppliers use more at the bottom.

The main story in this table is Social Media Analytics and Big Data Analysis. In both cases, more clients are using the techniques than agencies providing these services. This gap has existed for several years, but it has grown larger. In 2018, the gap in the use of Social Media Analytics was 18 percentage points; now it is 24. The gap last year in Big Data Analysis was 14 percentage points; now it is 19. The data suggest that many clients are buying their social media and big data analysis from non-market research suppliers and/or they are conducting the analyses internally.

Differences Among the Suppliers

The term ‘Suppliers’ covers a wide range of organizations, with different areas of focus. To enable a more detailed analysis we have divided Suppliers into four categories Technology Providers,null/Field Service, Data/Analytics, and Strategic Consultancy. Table 4 shows the use of emerging technologies by these four groups.

The technology providers tend to be less likely to use emerging technologies, compared with the other three groups. The two high points for technology providers, Mobile First Surveys and Research Gamification, are not appreciably higher than most of the others.

The Full/Field Service companies do not have any high standouts, but there are a wide range of technologies where it is the leader; for example, its 23% for Facial Analysis, 21% for Virtual Environments, and 16% for Biometrics are not high, but they are higher than the other three categories.

The highest standout for Full/Field Service is Mobile Qualitative at 54%, but this is matched by Strategic Consultancies with 52%.

The key standouts for the Data Analytics companies are Text Analytics and Big Data Analytics, each of which is used by at least 58% and lead the next highest group by 12% or more.

The Strategic Consultancies have the smallest number of standouts (both high and low). They are high for Social Media, Mobile Ethnography and Behavioral Economics.

Across the four groups, none of the niche techniques becomes a major player, reinforcing the niche nature of these technologies. At the high end of usage, the key differences are the low scores for Social Media Analytics for Technology Providers, Mobile First Surveys for Strategic Consultancies, Mobile Qualitative and Mobile Ethnography for Data/Analytics, and Big Data Analytics for the Full/ Field Service companies.

Differences by Region

There are a few interesting differences by region. However, the main message is that the advanced market research world (i.e. the world that can be reached via GRIT surveys) is essentially a homogeneous one. Table 5 shows the data for North America, Europe, and APAC regions.

In general, the claimed usage from Europe seems higher than from North America, but this may be partly due to sampling differences. For example, it may be the case that in North America the GRIT survey reaches more deeply into the industry while in Europe (and APAC) it may be collecting responses from those most engaged with the English-speaking world of advanced market research.

Two interesting differences of note are Applied Neuroscience and Eye Tracking. In 2018, Europe was ahead of North America in Applied Neuroscience (26% versus 17%); that gap has now widened to 43% in Europe and 25% in North America. The method has expanded in both regions, but even more in Europe.

In 2018, the standout difference in the regional comparisons was Eye Tracking: in North America, 35% of companies said it was in use, but in Europe, that figure was 51%. This year the gap has narrowed. In North America, the figure is 32%, and in Europe, the figure has dropped to 41% – reminding us not to read too much into a single year’s data.

If the sample were a random probability sample, the differences between North America and Europe would need to be 9% to be significant at the 95% confidence level and the gaps between APAC and the USA would need to be 11%, therefore differences below those levels should be treated with extra caution. The cells highlighted in yellow are ones where the gap between Europe and North America is 9 percentage points or more.

The Big Picture

The three main messages are 1) over the last five years things have been relatively stable, 2) that the advanced research world is pretty similar globally (yes, you can find differences, but the overall pattern is one of similarity), and 3) clients use of Social Media and Big Data Analysis is increasingly not coming from market research suppliers.

The stability message is of particular interest to those championing the exciting approaches that have yet to take off, for example, Biometrics. When and if we see these techniques becoming more mainstream, we will see them moving up the GRIT league table – but there is no sign of that yet.

If you are running a middle-sized organization, then the data suggest that unless you are an outlier, you should be using Mobile First Surveys, Text Analytics, Social Media Analysis, and Mobile Qualitative research – plus some of the other items.

The main worry for market research providers is the suggestion from the data that many research buyers are turning to non-market research sources for their Big Data and Social Media Analytics – something the GRIT report has been showing for some time now.