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The Top 20 Emerging Methods In Market Research – A GRIT Sneak Peek

A sneak peek at the "Adoption of New Research Methods" section from the upcoming GRIT Q1-Q2 2014 Report.

Editor’s Note: The newest GRIT report is with the designers and will be published around October 20th! As usual. it’s just chock-full of amazing data and insights about the state of the industry that everyone is sure to find useful. Since it’s almost GRIT time, that also means sneak peeks into the findings, and today we have one of the sections that many readers look forward to the most: the adoption of new research methods analysis. This analysis was done by Ray Poynter and Jeffrey Henning based on data collected this summer.

Watch for more sneak peeks, as well as the full publication of GRIT Q1-Q2 2014, right here very soon!


By Ray Poynter & Jeffrey Henning

Adoption of New Research Methods

This section looks at the adoption, by clients and suppliers, of new research methods, and the barriers to adopting new approaches. In evaluating the current picture and changes from the previous year it should be noted that two new research methods have been added to the survey this year: Big Data Analytics and Micro-Surveys.

The data suggest that not much has changed over the last 12 months (with one big exception). The same four techniques head up the list, however, within the detail of the information there are some interesting insights, such as the way that clients seem to be adopting Social Media Analytics and Big Data Analytics more widely than MR suppliers are, and these nuances are explored in this section.

This section also looks at why approaches are not used. The data remind us that no approach is right for every situation, and that barriers can range from not understanding a new technology through to finding an older approach too slow and too expensive.

Respondents were shown a list of new (and newish) research approaches and asked to indicate which they were already using and which they were actively considering. Note, selecting ‘using’ does not mean a technique is necessarily being used heavily. This question provides an insight into what techniques are working their way into toolkits.

It’s official! Mobile surveys and market research online communities are no longer emerging techniques; both are used by a majority of researchers:

56% of respondents have used MROCs, up from 49% in the last survey 9 months ago

The growth in mobile has been even more dramatic, climbing to 64% usage, up from 41% in the last survey.



Judging by its momentum, social media analytics will be the next technique to cross over to the mainstream: usage jumped 10 points to 46%.

Client-side researchers are more likely to have used the following than supplier-side researchers: social media analytics (47% to 36%) and Big Data analytics (39% to 29%). These are areas where the traditional market research industry might be losing market share to external firms. What are suppliers more likely than clients to see as the future of the industry? Suppliers have used mobile surveys, mobile qual, mobile ethnography, webcam interviews, microsurveys, gamification, facial analysis, and virtual reality more often than clients have.

Client vs. Supplier New Method Usage

Techniques that were added to the survey for the first time, with reported client-side usage, are:

  • Behavioral Economics models – 25%
  • Internet of Things/Sensor-based data collection – 12%
  • Wearables based research – 7%

We’ll set an alarm on our Apple Watch for a year from now to see how these techniques are doing.

Trends in approaches in use and under consideration

The chart below shows the approaches in use and under consideration over the last three waves of GRIT.


In Use Trends:

The big news, but perhaps not surprising news, is that mobile surveys are now the top approach, with about two-thirds saying they are using them. This is a jump of around 50% from the previous waves. It is clear that 2014 is the year that mobile arrived in a big way.

In general, all the numbers are higher in the latest wave, compared with the earlier waves. Given that the approaches are selected because they are believed to be growing, this growth is not surprising. The numbers do not, however, reflect volumes of work.

The rest of the list (other than mobile surveys) can be broadly broken into three categories:

  1. under 20%,
  2. 20% to under 40%,
  3. 40% to under 60%.

Those techniques which are currently under 20% are clearly niche at the moment. In some cases this may be their long-term position, for others (such as wearables) it may simply reflect their newness.

The 20% to 40% group reflect approaches that are becoming established in toolkits amongst a range of companies, without yet being ‘mainstream’. This group ranges from gamification at 23% through to mobile qual at 37%. One of the interesting items in this group is Big Data analytics, which is one of the very few items that has not noticeably increased since the previous wave. Perhaps big data is proving difficult to integrate for most research companies, or hard to monetize?

The 40% to 60% group represent mainstream approaches that all researchers should be considering and many should be using. Text analytics and social media analytics have grown their scores well since the last wave. Online communities has been the top scorer in this category for a few years and has again grown the number who say they are using it. Communities have lost their top spot in the list due to the rapid growth in mobile surveys, not because their growth has plateaued.

Under Consideration Trends:

Two phenomena jump out of when comparing in use vs. under consideration

  1. The range is narrow, from 21% considering biometric response to 38% considering big data analytics.
  2. A number of the scores for the most recent wave have fallen from the previous wave, e.g. mobile surveys fell from 41% considering to 26% considering.

The scores for the items at the top of the ‘In Use’ table have fallen in the consideration column because they are beginning to reach natural limits. For example, since 64% said they were using mobile surveys, the number saying they were ‘considering’ had to fall from 41%. The total of using and considering mobile surveys is now 90%. Presumably some of those not using or considering mobile surveys will be organisations that do not use surveys, e.g. some qualitative practices.

The two charts (in use and consideration) together confirm the importance of mobile (not just mobile surveys, but also techniques such as qual and ethnography). The tables also suggest that several approaches are, currently, firmly seen as niche, such as virtual reality and neuromarketing, since they are near the bottom of both the in use and considering tables.

Other emerging approaches

After asking respondents to rate the list of key techniques and approaches, we asked “Are there any other emerging technologies or new research approaches we have not listed you are considering trying out?”

There were about 150 responses to this open-ended question. However, most of these verbatim comments related to items which were already included in the questionnaire, such as virtual reality, social media, biometrics, and big data. However, in many of these cases the wording used in the open-ended response was slightly different, for example “Biometrics” compared with the questionnaire which said “Biometric Response”, or “Social media listening” compared with the questionnaire which said “Social Media Analytics”.

Open-ended responses that were mentioned fairly often and which were not in the list provided by the questionnaire included:

  • Geo/location issues, such as geofencing, location tracking, GPS etc.
  • Working with text and images in ways other than text analytics and social media analytics, such as semiotics and discourse analysis.
  • Variations on ‘mobile’, beyond just “mobile surveys”, “mobile ethnography” and “mobile qual”.
  • A more generalised expression of passive and observational data and analysis.
  • A variety of ‘neuro’ related approaches that people did not feel were captured by the term “Neuromarketing”, for example implicit association and voice analytics (which might also be biometrics).

In the next wave of GRIT we’ll continue to refine this overall section with answer options, and perhaps add some definitions in order to help reduce potential wording confusion.

These responses were not coded and added to the totals since it would not materially impact their relative rankings and would only marginally change the percentages. Overall this modified “other” response is a good way for us to “keep our ear to the ground” as it relates to new models emerging that we might not be paying sufficient attention to.

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17 responses to “The Top 20 Emerging Methods In Market Research – A GRIT Sneak Peek

  1. Hi Ray and Jeffrey, thanks for this analysis. It would be helpful to better understand the sample profile, specially geographical distribution around the world. When you say “It’s official! Mobile surveys and market research online communities are no longer emerging techniques; both are used by a majority of researchers:”, I wonder in which parts of the world that is true… US, Europe, other countries, since in emerging markets such as some countries in Latin America, their adoption is still in very early stag for sure. I look forward to your comments and more GRIT sneak peeks! Thanks!

    1. Hi Adriana, when the full report is published everyone will have access to a dashboard that will allow for deeper dives into the data to explore these questions. Overall the sample composition is heavily North America and Europe, so you do bring up a good point and we are referring to trends globally, not in specific countries. The base sizes in other regions are small and therefore unreliable as a quantitative measure. Since Europe and US represent the bulk of research spend, it may be better to think of this as indicative of how research spend is shifting to these methods.

      Daniel, We do think of these as different approaches based on their uses cases. Big Data encompasses most any data source and is defined by the 3Vs, and the outcome tends to be predictive models. Any type of social media analytics is defined by the name: the input is social media generated data, regardless of it’s volume and the analysis tends to be focused on different issues related to understanding virality, perception, intent, etc… Text Analytics is a specific approach to analyze unstructured data regardless of source and categorize and cluster it for additional analysis. Yes, all of these things can and do overlap, but in general today they do mean very distinct things.

  2. Hi Ray and Jeff,

    Thanks for this really interesting review of supporting and complementing methodologies; I can agree with and first hand confirm your observations, but have one follow up question, how do you distinguish between big data, social analytics and text mining? We do all of these things to gain on top of social media to create meaningful discourse analysis, where would you plug social media intelligence in?
    [email protected]

  3. Hi Ray and Jeff,

    thanks for this – great to see that mobile is advancing! There is still a lot of confusion on how to do mobile research right, eg optimal survey length (15 questions or 15 minutes?), user workflow, question types/formats, response/completion rates etc.

    Our experience is that the share of surveys that are truly device agnostic and were drafted with a mobile user in mind are still in the single digits. So much work ahead:-)

    Best, Nico

  4. Lenny, thanks for the clarification. I look forward to accessing the dashboard and explore deeper these questions. BTW, interesting to see “Research Gamification” as an emerging technique with 36% “under consideration” rate and 8 points more in terms of adoption when compared to GRIT 2013 (15% X 23%). Sounds like a great opportunity here! 🙂

  5. Ray & Jeff,

    How are you distinguishing between client-side & supplier-side in this context? Client-side researchers HIRE supplier-side researchers to conduct work for them. Thus, is the data overlapping or completely distinct?

    1. We ask participants to classify themselves in the beginning of the survey whether they are suppliers of research products/services or buyers of research products/services. That is the basic break used here. It is should be considered completely distinct.

  6. This sure made a nice read and a deep insight into the research marketing realm. I am new in marketing research ; i am developing a strong interest in it. i am reading all i can to understand it better as i have done a couple of field researching jobs here in Nigeria. I feel i might build a career for myself here. kudos to you guys and i hope to read more of your work.

  7. Hey nice post. Market researches are increasing nowadays before launching a new business. Your post has opened new approaches for trends and adoption for market research. Will cshare it with our subscribers at our site .If you require any poll maker service, feel free to visit our site. We are online poll creators with an additional functionality of proving maps of your voters.

  8. I’m an old school and well seasoned psychometrician, clinician, and social and mental epidemiologist. I’ve work on small projects and quite grand ones as well. I get the most satisfaction from the work I’ve done, when I find just the right learning environment for those struggling Masters, and PhD students find that they actually have what it takes to be excel as scholars. I love the one’s who find it easy too, but that’s nothing I can boast about as a scholar and educator. Recently I was asked to give my professional opinion on the scholarly rigour of research methodologies used by big advertising agents, and research competency of professionals working alongside successful Creatives. I have to say that I’m a bit discouraged, Your article here is an example of absolute poppycock psychobabble. I give you 10 out of 10 for getting me interested in your review, but I think your gathering of , and analysis of data, “new” research methodologies, might be the product of same groundbreaking coding we now associate with Das Auto? Maybe if I dropped acid your work here would make better sense

    1. Hi Dr. Dixson and thanks fro sharing. I’m curious what your issue is here? It’s a straightforward survey of market research clients and suppliers globally with a large sample that is roughly analogous of the largest markets by spend, and one of the questions which we report here is a simple question on whether specific newer methods (not traditional surveys or focus groups) are currently in use, under consideration for use, or not in consideration for use. The results are clear and stable wave on wave. I certainly wouldn’t think psychedelics are needed to understand a relatively simple and transparent exercise. Remember, this is about commercial adoption at scale to arrive at a proximal landscape of the research method marketplace, and I stand 1000% behind the data being useful, insightful, and impactful; what more could you possibly ask for?

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