GreenBook’s GRIT report for Q1-Q2 2016 showed the accelerating pace of change in the market research industry. With automation, mobile surveys, and tech-driven innovation raised as key themes, we spoke with industry experts Ray Poynter and Stephen Phillips in order to uncover their opinion on the findings.
The key to a company standing out for innovation, according to Stephen, is in maintaining a strong belief structure. Examples of this can be seen with Millward Brown‘s focus on the power of branding and with Brainjuicer‘s system one and two decision making. When these beliefs are communicated clearly, they feed into their marketing and align their messaging throughout the organisation. Stakeholders are given a clear sense of purpose, too.
Ray agrees. InSites, and Vision Critical are all following John Kearon’s advice, (BrainJuicer’s CEO): they publish a lot, they speak at events, and they produce high-quality thinking backed up with high-quality materials. When they have something interesting to say, they say it several times, and in several places via several speakers. Building strong online communities is an advantage here, offering a customer focused approach and a closer relationship between suppliers and brands.
As quick results become the norm, Stephen thinks mobile survey design will need to follow the trend so that these audiences remain engaged. New technology is now a core component in gaining this competitive advantage and it is automation that currently leads discussions surrounding innovation. We have already seen some of Kantar’s companies bring technological innovation to the heart of their operation. Millward Brown, in particular, has leveraged tech such as Affectiva and ZappiStore, to help ensure its offering remains in sync with clients’ appetite for innovation.
Ray’s message is this: Most innovation depends on tech, but most new tech does not lead to disruptive innovation. The most powerful tech is something that allows companies to either replace a current task with something faster and cheaper, or something that meets a known but unmet need. Ray points out that Google Glass was an example of tech that failed to disrupt market research, and most other industries, because it did not come with tools ready to turn tech into insight. For a good example, look at how many qualitative researchers have used smartphones to gather ethnographic data and information.
His view is that market research has been good at using automation over the last 50 years and he forecasts that it will continue to make processes faster, cheaper, and more reliable. Stephen’s predictions align: within the next two to three years it is likely that AI will become more widely accepted, and the winners in market research will be those who are integrating this technology into their methodologies. They will benefit from the efficiencies that come as a result.
But are all companies willing to innovate? Stephen says it is not a matter of choice, but one of necessity. Projects need to be delivered faster and under tighter budgets, therefore a desire for immediacy is an undeniable reality that all companies need to account for. Market research is catering to this behaviour.
While agency innovation is less frequent outside of survey methodology, some companies are clearly utilising technology to its fullest. Affectiva’s facial tracking is a good example. Speakers from companies such as Nestle highlighted to Ray, earlier this year at IIeX in Amsterdam, that most insight managers are obliged to be risk averse because everything they do is expected to deliver value. That said, clients like Campbell’s and Unilever are prepared to devote money and time to newer, riskier projects. It is once these new techniques become established that other clients are more willing to adopt it.
Ray is keen to highlight parallels in smartphone research, insight communities, and the use of ZappiStore products (such as the modified Link test). The Rogers Diffusion of Innovations curve, with 2.5% Innovators and 13.5% Early Adopters, is probably right for both agencies and clients, but he is unsure if there is any particularly pronounced difference between the two in terms of the ratio of innovators to laggards.
Looking to the future, and to GRIT in 2017, Stephen predicts that machine learning and AI will be the next big trend as the technology is applied across all aspects of research (such as text analysis sampling and data presentation). Ray thinks there will be significant changes in 2017, and he is expecting to see the top ten innovative companies reap the benefits of automation, growth in social media, text analytics, and qualitative research.
Which, of all the possibilities, are you most anticipating?
You can also check out 2016 IIeX highlights of the year: here.