Artificial intelligence (AI) technology is poised to transform almost every sector of business and industry.
According to PwC, AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined.
Within the field of market research, there is huge scope to integrate AI solutions and machine learning (a subset of AI) into traditional research processes which are often time consuming and labour intensive.
In the 2019 GRIT Report, the leading survey of the market research industry, AI was the ‘clear winner’ in the Buzz Topics section of the report – underscoring that there is strong interest in AI applications and solutions within the global industry. Notably, however, the report also flagged the risk of ‘artificial stupidity’ and the potential for market research professionals to be led astray by this emerging field of technology.
“Although the use of AI within market research is a very young concept, it undoubtedly presents an opportunity to innovate and explore different ways of gathering and analysing consumer insights,” explains Caitlin Bauristhene, head of research at KLA, a South African intelligence and insights agency.
“In South Africa, we have to overcome specific challenges in order to leverage the many benefits of AI within market research, and it is important to emphasize that you cannot leave the human out of the process altogether … whether that is the human respondent or the human researcher/analyst.”
A unique local context
Locally, access to digital data collection presents somewhat of a roadblock for AI applications, because AI typically runs live on digital data collection platforms.
According to Bauristhene, the (confident) use of online-based data collection has been dependent on market research agencies convincing buyers that their target markets are accessible via online/mobile methodologies.
This has tracked along with increased smartphone penetration, however, there are some groups that still cannot be easily accessed digitally (such as the very lower end segments, the very affluent and B2B segments).
In addition, market research agencies have traditionally been set up to put the more technical skills (programming surveys/platforms, data processing and analytics) in the ‘back office’ – and even outsourced – while the client-facing analyst role is the typical ‘hero’ position within the field.
“As it stands, it is hard to find a researcher who has a combination of analytical, strategic and client-service skills – as well as technical data skills,” says Bauristhene. “Beyond the skills question, there is also the local challenge of capital investment into AI innovation.
“Often, global agencies are unable to convince local clients that what is done overseas can work here, and local agencies have limited capital for investment into R&D on their own.”
Yet investment is arguably critical for the local industry to be able to harness developments within AI technology – particularly given South Africa’s unique diversity. Indeed, the multitude of languages and cultures within SA poses a major challenge for NLP (natural language processing) engines, for example.
“Even beyond our multi-lingual consumers, the nuance and turn of phrase in our digitally written text language is hard for a human to interpret, never mind a computer,” explains Bauristhene. “In order for NLP engines to become mainstream, the systems would need intensive iterative training of the machine learning, and this takes both time and investment (which are seldom available today).”
Pioneering a way forward
Yet even in the face of such formidable challenges, there are still ways to integrate AI and machine learning systems into local solutions – something which KLA was able to achieve in partnership with GroupSolver, a US based survey research company.
When working on a project for a large FMCG company, KLA sought a way to incorporate AI and machine learning in such a way that it could overcome the fundamental challenge of South Africa’s diverse population.