As a multitude of technologies become available to progress market research goals in the 21st century, researchers might become a bit fatigued trying to keep track of the next greatest innovation and the latest game-changing approach. However, while the perception persists that researchers are snapping up cutting-edge ideas left and right, the reality is that only a few are being commonly accepted and considered by a significant number of industry professionals.


A sneak peek into the results from the most recent GRIT study notes that the top five emerging methods have remained constant over the last several waves of research. Online communities, mobile surveys, social media analytics, text analytics, and big data analytics were reported to be more than 30 per cent in use by respondents, with an equally high proportion considering their use in the near future. At the top of the list, online panel communities were said to be in use by 49 per cent of respondents and under consideration by 33 per cent.


As these emerging methods achieve mainstream adoption levels, what will be next on the horizon? Here are six up-and-coming technologies and techniques generating considerable interest for their potential to feed into and enrich current practices, as well as create completely new approaches in their own right.


Mobile ethnography

Mobile research is certainly here to stay. Recent estimations by the Kantar Group predict that 20 to 30 per cent of all data collection will be mobile within two to three years. Echoing the position of the group, TNS is investing considerably in mobile, envisioning its strengths as overcoming the limitations of memory to provide more accurate information via direct responses, touch-point interaction, and journey mapping.


Blending qualitative and quantitative methodologies, mobile ethnography methods such as real-time experience tracking (RET), pioneered by companies like MESH, give researchers unparalleled access to the impressions brands make on individuals as they go through their day keeping an online diary (often synced with desktop for greater flexibility and depth) within a structured approach that prompts them to input detailed information, upload images, and stream video. RET attempts to eliminate the potential cloudiness caused by time and the disconnect of trying to imagine a situation while seated at a desktop computer by obtaining the insights from participants as they interact in the real world, offering what many say is a more honest and reliable assessment of their journey as consumers – helping identify the touch points and their effectiveness along the way.


Sensor data

Connecting the physical and virtual worlds, new products ingrained with sensor technology not only provide valuable data to users, but also to companies. Wearable technology is a booming business, led by innovations such as Nike+ products or Disney’s new MyMagic+ system, which offers theme park visitors a wristband they can use to enter the park, purchase concessions, pay for rides, access hotel rooms, and more. While offering these conveniences, it also tracks all of these activities to give Disney detailed insights into visitor behaviour and preferences to analyse the performance of various marketing and product development initiatives, and highlight needs for further customisation. These insights can be used to improve the service at all stages.


Nike also draws from the considerable wealth of user data generated by products such as its FuelBand to inform future products and identify areas of opportunity. Additionally, the company has partnered with app developers through the Nike+ Accelerator project to create lateral offerings drawing upon this data – such as rewards in the form of coupons and discounts for achieving personal bests. The data harnessing capabilities of sensors embedded in products extends from wearable devices to home monitoring systems, such as those created by the start-up Nest, which was one of Google’s recent high-profile purchases.


Automatic content recognition

In a multiscreen world, automatic content recognition (ACR) technology may play a pivotal role in connecting experiences across devices. By recognising the audio or visual “fingerprint” of content, a mobile device can identify the television programme, online video, or song an individual is being exposed to at that precise moment. Most commonly, this technology is seen in apps like Shazam, but it is also being incorporated directly into devices.


While this clearly has implications for creating a targeted convergence of online and television advertisements, it also opens doors for market researchers to identify and deploy surveys to users immediately based on the content they are consuming in the moment. Alternately, ACR could be used to customise a questionnaire in the moment by picking up on cues in the survey respondent’s environment to ask questions tailored to that particular content.



By drawing upon location data created by mobile applications and devices on a large scale, researchers can develop a metered understanding of the consumer journey in the physical world. On the hyper-local end of this spectrum is geofencing, a location-based data collection and interaction technique gaining considerable traction this year. By creating virtual fences around specific locations via dedicated apps, behavioural information can be collected on those app users during the time they spend in the designated area. For example, a department store could identify a VIP customer when that individual enters the store and send them a personalised message via their proprietary app. Customised offers and specials, as well as tailored surveys, can be sent to the mobile devices of app users, and then the uptake and responses can be analysed in conjunction with time spent in the target area to provide further insights.


Natural language questioning and processing

Made famous by Siri, natural language processing and understanding has made considerable advances in the last few years, and is seeing an increased level of integration within market research tools. As natural language processing becomes more sophisticated, so do the insights it can glean from analysing the vast amounts of social sentiment data being created by the proliferation of social media activities. These technologies will also play a growing role in the development of mobile apps for market research, increasing completion speed and convenience for survey respondents by avoiding the need for extensive text input.


Biometric data

As camera technology in computing and mobile devices has advanced along with image processing algorithms, developers have been able to capture and analyse details about human-machine interactions on an unprecedented level. Leading the charge are technologies that track eye moments and facial expressions to offer deeper insights into perceptions and behaviour. For example, Realeyes aims to help advertisers gauge the emotional impact of their campaigns by analysing the facial expressions of individuals via webcam as they respond to their advertisements – and this data can be collected, analysed and delivered in real time.


Author bio

Bo Mattsson is the chief executive of Cint, a global provider of market research tool for creating online panels and obtaining market insights from survey respondents via its OpinionHUB global exchange platform. Bo founded Cint in 1998 when he decided to apply his experience of trading online to the market research industry. He then took over as CEO in 2003 to revamp the core technology behind the market research tools into an exchange-based offering for transparent respondent access. For further information, please visit

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