Editor’s Note: The new GRIT Report for Q3-Q4 2017 will be released in the next two weeks, but to start the New Year out right we wanted to give readers a sneak peek of one of the most popular sections we cover: the adoption of emerging methods in the industry. Ray Poynter always leads the charge on this analysis, and this year Elissa Moses of Ipsos Neuro and Behavior Science contributed a deeper dive into analysis of nonconscious techniques. As you plan for the year ahead, this list should be a guide on what to experiment with or invest in.
In addition to the emerging methods section, in the forthcoming report we explore a variety of topics, some new and some that our readers have already come to depend on GRIT to cover. These include: the use of traditional methods, satisfaction levels with suppliers, the perception of challenges & opportunities (and what to do about them), financial outlook and projected spending, how research professionals use their time and what tools they use most to do their jobs, buzz topics such as automation or AI, and the next iteration of our industry benchmark. Look for new info soon on the publication date soon!
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 MR 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 sellers of research and insight).
One important note in the 2017 figures is that there have been several minor questionnaire changes (slight improvements to wording), but one major change. Before 2017 the term Mobile Surveys was used, and this had reached the point where 75% of participants said they were using Mobile Surveys. So, from 2017 we are using the term ‘Mobile First Surveys’ and this has, not surprisingly, reduced the ‘In Use’ figure, to 50% for the Total sample in 2017.
The Overall Picture
Table 1 shows the 21 approaches included in the GRIT study ranked in terms of how many people said they were already using these techniques. Remember, ‘using a technique’ does not necessarily means using it heavily, it may mean it is sometimes used, and sometimes not. We are combing “In Use” and “Under Consideration” for a cumulate “Interest” metric.
|Rank||Labels||In use||Under Consideration||Interest|
|3||Mobile First Surveys||50%||24%||74%|
|4||Social Media Analytics||43%||28%||72%|
|5||Big Data Analytics||38%||32%||70%|
|10||Behavioral Economics Models||29%||29%||58%|
|16||Internet of Things||12%||27%||40%|
|17||Virtual Environments/Virtual Reality||11%||27%||38%|
|19||Wearables Based Research||9%||27%||36%|
Online communities are the only mainstream item amongst those examined, with 60% saying they are ‘In Use’ and 82% saying in use or under consideration. Note, the reason that the term Mobile Surveys was retired was that it was almost ubiquitous. In future editions of GRIT is is likely that Communities will also be removed from “Emerging Methods” now that it is mainstream.
Below online communities there are four items with large numbers of participants saying they are in use or under consideration, creating high ‘Interest’ scores: Text Analytics (76%), Mobile First Surveys (74%), Social Media Analytics (72%), and Big Data Analytics (70%). Three of these four are analytics and highlight the shift away from asking questions.
The next group comprises three qualitative options, that have interest scores in the range 61% to 69%, namely Mobile Qualitative, Webcam-based Interviews, and Mobile Ethnography. These three highlight the continued strength of qual in a data-centric world.
The remainder of the table can be divided into strong niches and small niches. The strong niches group runs form Applied Neuroscience, with 21% of participants saying they were already using it, up to Micro-surveys with 34% saying they are already using it and 56% showing interest. The bottom six, the smaller niches, all have fewer than 20% saying they use them, and fewer than 50% showing interest.
Stability More than Change
Table 2 shows the ‘In Use’ data for the dating back to August 2014, a period of three years. The data shows that there are changes, but few of them are large. Given the nature of the data, sampling variation etc, I would tend to ignore anything smaller than plus or minus 5%.
|Table 2||2014 Aug||2015 Oct||2016 Nov||2017 Oct||12 month Change|
|Mobile First Surveys||—||—||—||50%||NA|
|Social Media Analytics||46%||43%||52%||43%||-9%|
|Big Data Analytics||32%||34%||38%||38%||0%|
|Behavioral Economics Models||25%||21%||29%||29%||0%|
|Internet of Things||12%||9%||14%||12%||-2%|
|Wearables Based Research||7%||8%||10%||9%||-1%|
The main decline has been for Social Media Analytics, which is looking like a correction, since the 2017 figure is similar to the 2015 and 2014 figures. But, we will see something more interesting with this methodology when we look at the balance between research buyers and providers.
Most of the approaches that are in the group we described as the small niches do not appear to be showing any sign of expanding beyond their small group of users.
Buyers and Suppliers
There are a couple of good reasons why Suppliers might say they are using more research techniques than research Buyers/Users:
- Suppliers typically work with many companies, and may use a different range of techniques with different clients. Of course, it is also true that large clients use many researcher suppliers.
- Suppliers need to know all of the details of the research they are providing, such as whether Research Gamification is used in the design and what proportion of the surveys are completed via mobile device. A research buyer may want to know this too, but in many cases the buyer of the research is less involved in these details.
Table 3 shows the ‘In Use’ data for Buyers and Suppliers of market research, and the right-hand column contrasts the results.
|Table 3||Buyer||Supplier||Supplier – Buyer||Total|
|Mobile First Surveys||43%||52%||10%||50%|
|Social Media Analytics||60%||38%||-22%||43%|
|Big Data Analytics||50%||35%||-14%||38%|
|Behavioral Economics Models||25%||30%||5%||29%|
|Internet of Things||12%||13%||1%||12%|
|Virtual Environments/Virtual Reality||8%||12%||3%||11%|
|Wearables Based Research||6%||10%||4%||9%|
The pattern of techniques and approaches in use is similar between Buyers and Sellers (not surprisingly) with an r-squared value of 79%. However, there are some interesting differences.
In several of the technical areas of research the percentage of suppliers using them is considerably higher than the buyers, for example: Mobile First Surveys (Suppliers 52%, Buyers 43%), Mobile Qualitative (Suppliers 46%, Buyers 34%), and Research Gamification (Suppliers 28%, Buyers 15%).
However, the more interesting cases are those where the Buyers are more likely to be using an approach than the Suppliers. The two key ones being: Social Media Analytics (Buyers 60%, Suppliers 38%) and Big Data Analytics (Buyers 50%, Suppliers 35%). This finding is consistent with earlier waves of GRIT and we believe it indicates that for these two services many clients are buying from non-MR suppliers – which is consistent with the findings from some of the other findings from this wave of the GRIT study.
Differences By Region
There are some interesting differences by Region, and if you have a chance to dive into the data you will find some interesting differences by country too. However, the main message is that the advanced market research world is essentially a similar place – comparing North America to the other three groupings gives an r-squared of 89% or higher for each region.
Table 4 shows the data for North America, Europe, APAC, and Other – regions that have been determined by sample size and geography.
|Table 4||North America||Europe||APAC||Other|
|Mobile First Surveys||47%||56%||50%||54%|
|Social Media Analytics||41%||46%||49%||47%|
|Big Data Analytics||38%||41%||37%||38%|
|Behavioral Economics Models||25%||34%||31%||30%|
|Internet of Things||13%||10%||18%||10%|
|Wearables Based Research||7%||12%||11%||8%|
One interesting, but not strong, pattern is that North America tends to score slightly lower than Europe and APAC. It could be that the sample for North America is a bit more general, and the sample from Europe and APAC a bit more tech-focused. Or, and this would be consistent with some of the other patterns in the data, that the use of tech in market research is maturing into mainstream and niche, and North America is further ahead in that process.
What is next?
We ask respondents via a verbatim option what other emerging technologies are considering using, and these coded responses are an effective means of looking ahead to what will might be the next major trend in research. Leading the list is AI, which is twice as likely to be under consideration by Buyers vs. Suppliers compared to any other method, a theme that is echoed throughout GRIT . Video Analytics, automation in general, neural networks and multiple platforms are also of far larger interest to buyers than to suppliers, although all appear to have interest on both sides of the table.
|Insights Buyer / Provider|
|Insights buyer or client||Insights provider or supplier|
|Implicit association experiments/Test||1.3%||2.3%|
|Video Analytics/Video surveys||5.2%||4.5%|
|Combination of online + offline parts||1.3%||3.4%|
|Provide the data according to client need||0.0%||0.8%|
|Behavioral Recruitment/Digital behavior||1.3%||3.0%|
|Data management platforms||0.0%||3.0%|
|Data gained from TV||1.3%||0.4%|
|Customer/Shopper Traffic Counter Devices||0.0%||0.8%|
|Weather and spatial proxemics||0.0%||0.4%|
|Virtual plan-o-grams at retail||1.3%||0.8%|
|Face to face mobile research||0.0%||0.4%|
In the next wave of GRIT we will include some of these “next generation” methods in the general adoption rankings so we can begin to identify the next great emerging technique such as communities, mobile, and text analytics became over the past few years.
The Net on Nonconscious Measurement
For all the intense industry focus on Neuroscience and Behavioral Science methods, it has been baffling to see what appears to be low penetration for individual “System 1” tools specified in past Grit reports. We suspect that this is due to the fact that “Neuro tools” are a class of methods and that when spread out individually, they appear to be less than their shared usage and impact implies. This led us to combine the following five methods which comprise the backbone of nonconsious measurement across study types: Behavioral Economics Models, Eye Tracking, Facial Analysis, Applied Neuroscience and Biometric Response. (Implicit is also a major method in this class but is not yet included in the Grit Report.)
When we net the most prominent methods employed to capture nonconscious response, it appears that critical mass in the industry for both use (53%) and total interest (80%) has taken hold. No longer a “special occasion” consideration, nonconscious measurement has tipped to be embraced by the majority of the industry using one or more of the key methods available included in the Grit Report. Considering that the neuromarketing sub-industry is only about 10+ years old, this is a massive change in the thinking and acceptance among researchers and marketers alike.
These levels would, most likely, be even more dramatic if Implicit Reaction Time Testing were included in the study as well. Implicit is perceived to be one of the fastest growing nonconscious methods in the industry given the tool’s ability to be broadly applied and enable insight in the strength of conviction consumers hold for brand attributes and associations. It is strongly recommended that Implicit be added to future Grit Reports.
|Labels||In use||Under Consideration||Total Interest|
|Net Nonconsious Measures||53%||27%||80%|
|Behavioral Economics Models||29%||29%||58%|
Also curious is the relatively high level of agreement to using or considering Behavioral Economics Models. Leveraging Behavioral Economics is highly desirable in that it has potential to have demonstrable impact on brand outcomes. The right “framing” or “anchoring” can sway a decision in a particular context and scenario testing alternative brand positionings can have a huge impact on optimizing selection. But we wonder if almost 1 in 3 in the industry are literally applying Behavioral Economics Models, or do the words “behavior” and “models” invite selection because of other associations such as behavioral surveys, media models, etc.
To get the most accurate handle on the penetration and growth of nonconsious measurement adoption by the marketing industry, it would be elucidating to get a better sense of what people mean by these terms used going forward and be inclusive of all major nonconscious methods in usage.
But all in all, it is worth taking note that a major milestone has been achieved and most of the market research industry has entered the realm of nonconscious measurement usage or desire!
The Main Story
The two main messages are A) over the last three years things have been relatively stable, and B) that the advanced research world is pretty similar globally (yes you can find differences, but the overall pattern is one of similarity).
The stability message is of particular interest to those championing the exciting approaches that have yet to take off, for example Sensors/Telemetry, Virtual Reality, and Internet of Things. 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. However, when we see the aggregate penetration of Nonconscious Measurement total interest, there is clearly a trend toward critical mass.
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 and Online Communities, some of the techniques in the middle of the table, and perhaps one of the emergent techniques in the bottom group.
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 Text Analytics and Social Media Analytics – something the GRIT report has been showing for some time now.