Technology advancements like AI and machine learning will shape the market research industry more than any other innovation has within the past half century. And the rate of acceleration and change is unlike anything we’ve ever seen before. At the 2018 Insights Leadership Conference, a panel moderated by Bonnie L. Breslauer, Chief Customer Officer of DISQO, examined whether the market research industry can adapt to this rapid penetration, or if it will hold onto legacy practices, with the good intentions of protecting traditional research methods and the “purist” approach they represent.
Or as Breslauer summarized, “As automation and technology advancements forge ahead, will the MR industry transform or be left behind, chasing the ever elusive “seat at the table?”
To understand the impact that such technology advancements will have on market research, below are highlights from the Q&A session with our President and Chief Innovation Officer, Steve Mast; Isaac Rogers, CEO, 20|20 Research; Kristi Zuhlke, CEO, KnowledgeHound.
We’ve talked for decades about researchers fighting for a seat at the table and it’s something Kristi touches on in her response. What’s your take on the research industry and where we are headed? What dynamics are at play that will impact our landscape and the industry’s ability to be relevant?
Steve Mast: Today’s proliferation of digital platforms allows everyone to become a researcher and gather customer data. New technology such as chatbots is playing a key role in blurring the lines between traditional qualitative and quantitative research and overall, we’re seeing a shift away from ‘point in time’ research to an ‘always on’ research model. The question now becomes how does the market research industry transform its role to become more strategic and central to business success.
There are three important trends that’ll be led by the MR industry during this transformation.
- Integration: Research-based technology tools and platforms such as video-based Voxpopme or automated research platforms like Methodify will be integrated into marketing workflow processes and tie directly into martech platforms like Adobe or Salesforce.
- Reimaging: The research department will be reimaged. We’ll see an increase in human-centric teams with research professionals at the heart, charged with bringing the voice of the customer to every aspect of product creation, marketing and operations. Also, we will see sampling in market research reimaged due to blockchain technology and possibly the rise of virtual personas or ‘digital twins’ that will represent real consumers.
- Decentralization: Automation will decentralize the role of the researcher. Everyone in the company will have access to powerful proven research methods and tools, which means that it will no longer be the sole responsibility of the researcher. Thus, their role can evolve to that of a strategic insights partner for the team.
How are you using AI? What problems are you trying to solve with it?
Kristi Zuhlke: The power of AI is in expediting data crunching and pattern recognition—patterns that humans either can’t see or simply take us too long to discover. For example, Remesh, an AI platform for quantitative focus groups, allows a moderator to recognize patterns in responses and ask on-the-fly probing questions. There are obvious merits to AI, yet many remain threatened that it will eliminate our jobs. However, if we view AI as an aid in surfacing the data we need faster, we can then use it to our advantage, quickly turning that data into insights that will drive revenue for our companies. Ultimately, AI will give market researchers and insights professional a crucial seat at the table.
How can companies successfully embrace automation?
Isaac Rogers: Embracing automation, to me, aligns closely with embracing change in general. There tends to be a lot of wait-and-see that occurs when a new technology comes on the scene in our space, with MR agencies reluctant to take risks on new methods and technology suppliers unable to field test and improve their emerging methods without real-world use cases.
That said, I have witnessed at least one successful strategy that helped bridge this gap; dedicated R&D budgets from MR agencies and end-clients. When an organization dedicates time and money to partnering with emerging technologies, not only do they benefit from being able to shape the way the innovation occurs, but they are also going to be the first to reap the rewards of the newly developed approach.
I’m talking about carving off real, spendable dollars towards pilot projects and real-world experimentation, not just using this R&D budget to attend webinars and conferences hoping to stay ahead of trends through osmosis. For example, a firm might choose to run side-by-side tests of real projects, with half the work done “traditionally” and the other half leveraging new automation methods, working in collaboration with the tech vendor to ensure both are learning from the exercise. Firms have also used this budget to pre-fund work with the technology developer in exchange for deep involvement in how the product progresses and having the opportunity to weigh in on the direction of the development.
I often get the question “so how big should the budget be?” I don’t pretend to have the right answer, but after spending some time looking at our own processes at 20|20 and asking a few firms who have had success with this approach, budgets tend to be somewhere around 2-5% of revenue. It may sound like a large investment, but with the external pressures facing our industry to modernize and innovate our entire value chain, maybe the better question is how we plan to compete if we’re not making major investments and betting on our own future.