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Wale Omiyale
SVP of Market Research, Confirmit
It is now indisputable that most industries, including market research, will not be able to escape the technological disruption of automation and artificial intelligence (AI) occurring around the world. As we have seen, automation is already happening before our eyes and the expectation of clients is only growing as AI and other game-changing technologies have had a positive impact on so many other aspects of their lives. But with real-time information and instant analytics gratification now taken for granted and even becoming expected, traditional market researchers are under immense pressure to deliver their results faster and cheaper.
Like many industries in this new economic reality, market research organizations must now uncover higher-quality insights almost instantly and at a lower cost, which makes automating some of their processes not only inevitable but necessary. Already two of the three major elements of research – operational and cognitive – are well on the way to part or full automation with only creativity still separating us from the machines.
Operationally, market research already has a long history of automating simple processes: questionnaire scanning was itself revolutionary in speeding up the data capture process and was created to meet the need for faster results. As time progresses, we’re seeing more day-to-day tasks being automated.
The difference? There are a few:
AI now spans the entire MR lifecycle. As well as helping to automate survey design, sampling, data collection and reporting, automation tools are becoming available for much more advanced cognitive techniques, from emotional response recognition to multimedia feedback, social media analysis and more.
Researchers can focus attention elsewhere. By automating many of the repetitive tasks associated with data collection and analysis, researchers can focus their efforts on the more in-depth analytical and creative processes, such as the design of new surveys and methodologies that truly require human interpretation. However, it’s important to remember that this automation should be viewed as a benefit to help and assist humans, not replace them. One phrase I like is, “Data is stupid – it only knows what it knows.” This is true; it is people that are key in the integration and interpretation of such data and processes.
Researchers can become specialized. As automation tools take over administrative tasks, it also frees up research teams to concentrate on evolving into specialist hubs. This becomes an even bigger asset to organizations as researchers can now become data scientists and ordinary reports turn into strategic business guidance for C-level executives. Automation equally increases the need for broadly-skilled project managers who no longer require in-depth subject knowledge but a wider understanding of the many automated steps of the research process. This certainly impacts the role of the research subject matter expert but allows research organizations to be more flexible in recruitment and service delivery.
AI helps to break down silos. Despite some skeptics warning of the demise of people-based organizations, there is growing evidence that automation can break down damaging departmental silos and promote collaboration, both across survey teams and with external partners and customers. AI is imposing research content and knowledge into tools that sit in teams through an organization. These teams and departments may traditionally not have owned the insight process and as a result they are now empowered to make immediate and positive impacts throughout their organizations. This represents a real opportunity.
So where do future opportunities lie for “real” researchers?
Although AI and automation have come leaps and bounds from where they were a few years ago, we still have a long way to go before these machines “take over” – and the human touch is still critical to success in the MR world. Market researchers are still extremely valuable with the following skills:
Creating something new. With the help of machine learning, surveys will one day be created automatically once enough scenarios are fed through an algorithm. In other words, it can’t create something completely new. Because of this, the ability to create new methodologies and research processes and react to market dynamics will still be very much a human task for some time to come. New methodologies, research processes and reacting to new/changing market dynamics requires people.
Listening to instincts. AI also lacks the “gut feeling” we get that instinctively tells human researchers that something is not right. There will long be a requirement for people to oversee data quality assurance. That might not be a statistical exercise so much as it is an experienced researcher looking at data and just knowing something is amiss.
Forming a relationship. Human clients will always prefer a human relationship with their research partners. We are already seeing that MR clients want to work with researchers as partners and trusted advisors, not vendors of data. Clients don’t want to get answers to their business issues from a machine, as dashboards of data will only take them so far. They want a person they know to answer their questions and provide that trust. And, let’s be honest, they can’t hold an algorithm accountable!
Offering self-service. For some clients, MR organizations will be able to provide a whole new level of ownership, delivering them self-service research programs. This model is proving increasingly popular with clients who need to gather high-level insight quickly. Clients can use self-service to select the most appropriate tools for their project, select the audience or sample and then select the type of reporting they need to produce, all from a single source. Not only does this shorten timelines but it can also simplify results-sharing and analysis through easy-access dashboards. This may ring alarm bells for MR companies worried about the diminishing need for the skills of the research agency. But I would argue otherwise. What many clients now need is quick insight. This means that sometimes they only want to focus on those questions that get to the heart of their enquiry most quickly. With automation tools to support this way of working, they may still get 80 percent of the information they need in 25 percent of the time. And that makes a justifiable business case for self-service. There will still be the need for in-depth research programs. This self-serve approach is, in fact, a new layer that sits on top of substantial analysis and insight.
Prioritizing the consumer. The rise of AI and automation is creating a groundswell of focus on the consumer, as businesses now increasingly place the consumer at the heart of the decision-making process. Automation is placing research insights into the hands of individuals that can build business cases around the needs of the consumer faster and more effectively than traditional means.
The developments in automation are driving the industry toward a custom, white-glove model of research, where the needs of clients are met for whatever level of program they require – and can be delivered in the time frames and formats most suited to each need. But it’s not only clients who can benefit from a fast turnaround: automation also benefits agencies through repeatability. The more processes that can be set up and repeated, the more efficient an organization becomes, which boosts productivity and increases the usability of automation tools. Furthermore, when automation is applied to multiple processes across the organization, both time and cost savings are magnified. This ease and speed of delivery becomes a differentiating factor against competitors.
While research will continue without traditional “researchers,” the future for creative research professionals to think more high-level and holistically is bright. These new professionals will be overseeing elements, designing new methodologies, advising and working with clients as a partner, not a data source.
So, while things are certainly changing in the world of MR – specifically the role of the market researcher – we all need to remember that this is a case for evolution, not extinction!
