The Future is Here – 3rd evolution of market research is underway

In typical business conversations today, one cannot miss to touch on the topic of the ever-changing consumer needs and of course, the discussion around the increasingly volatile, uncertain, complex and ambiguous business environment. In the meantime, as technology keeps evolving and getting more and more sophisticated, our lives, including what we do every day as work will keep getting disrupted. We are getting more and more connected digitally (online) whilst the traditional face to face connection declines – from the mobile phone alone, we can stay connected socially with friends and relatives, get news, stay entertained, get medical advice, shop and pay goods & services. There are claims that on average, we touch our mobile phones 150-300 times a day – the mobile phone, arguably, is a threat to natural human connection and in the wider scope of things, to how life is and will be in future – as technology and automation take centre stage in more and more aspects of our lives.

 We have all made different observations on the effects of technology – both positive and negative. I was reflecting on how the local market research industry has evolved – over the last 20 or so years. I came up with what I personally think could represent the different seasons in the industry. I believe that locally, we are in the third season, the 3rd evolution – with very familiar characteristics.

 The first season, the traditional research, that to me, lasted up to about 2010 was characterized by costly fieldwork budgets due to lengthy and inefficient data collection methods such as postal surveys, Pen & Paper interviewing, limited automation in data processing as data clerks had to code and key in data manually. The researchers during this season were less specialised – they were ‘generalists’ – they did budgets for projects, managed project teams in field, managed data processing, wrote reports and presented to clients – and for both qualitative and quantitative. The reports were huge – clients wanted every bit of the data in charts. The market and indeed the consumers were simple – and hence the insights were simple as well. No complex analytics were required.

The second season lasted about 6-7 years. We started seeing the signs in 2015 into 2016 – market research budget rationalization kicked in – the huge budgets for programs like brand health tracking got reviewed. Traditional data collection methods got challenged and adoption of new methods such as CAPI, mobile data collection and online surveys to some extent picked up. As the consumer landscape got more complex, need for more advanced analytics grew. The overall industry also grew as footprint of global market research agencies expanded in Kenya and the broader region as a whole. I would call the early years of this season, the early tech. This is when small shifts into automation started. The later years of this season – towards 2016, were more of mid tech characterised with more pressure for budget rationalization, demand for shorter, sharper and cheaper surveys. There were also increasing calls for predictive analytics/modelling. Specialization picked up – research teams became more and more practice area specialists – brand, advertising, communication, customer experience, innovation and so and so forth. Client questions became more complex and pointed to seeking answers to growth opportunities – as achieving growth became harder and harder – partly due to fast evolving market dynamics.

2017 onwards marked the start of the latest season – the one I am calling the Fast tech. In this season, data and information is in abundance – in fact, in some cases, clients are becoming owners of self-generated, internal data. This has meant pressure on data collection costs as value of data declines and shifts to expertise in making sense of the data in a way that can impact business in a positive way. In general, the industry continues to adopt and invest in automation and machine learning amidst prediction that entire industry may slow down as this disruption gets more intense. In Kenya specifically, the industry remained generally flat into last year according to Esomar data 2018.

 Even though we may not be at the same level as the developed market research markets in terms of adoption of artificial intelligence, machine learning and general automation, the effects of these mega shifts are already evident locally. DIY research is growing as focus on understanding quick business questions that do not need massive research budgets rises, speed is trumping quality – learning quickly at minimal cost and executing the insights is becoming part of the pressure in the insights teams. The word agile research is becoming almost mainstream as small, micro surveys become more common. Because of the growth of technology as a platform for market research, partnerships and acquisitions will be common as understanding of real time consumer behaviour becomes more critical to guiding business decisions.

 Sources of data and collection methods are also starting to shift, faster now – interest, discussion and application of passive methods of data collection is growing fast. Soon, active questioning might be a thing of the past. This means that social listening will be a must for marketing teams and by extension, for market research and insights teams. Overall, as more and more diverse sets of data accumulate – from brand communication to customer data, social media posts to macro-economic data, consumer sentiment and public affairs data, artificial intelligence will help bring some sense by trying to identify interconnections or patterns that can be used to advise business decisions or investments. However, such connections may lack the human touch – the exciting creation of stories that can explain the human motivations – or in simple terms, the WHY behind the observed behaviours and lead to new levels of segmentation – all the way to personalization of offers based on deep understanding of specific motivations.

 So, what is next for market research? From an operations point of view, increasing automation and growing availability of client owned and other data will mean less time will be spent collecting data – this means future operations will be leaner and designed for the fast tech season – digital, social listening, consumer panels management and data science teams will play a bigger role in collection, management and integration of data. Industry revenue growth will be driven by new research types and how fast players get into the fast tech space. From people and skills perspective, new skills will be required beyond the technical researcher of the years gone by – may be a hybrid of technical research knowledge and story telling? right brainers will start to rule in market research? or may be a full insights gurus who will look at connecting the revealed data patterns and inter-relations in the context of client strategy to help businesses grow amidst the reality of disruption?

 Whichever way, the future we thought was far off is already here – the 3rd evolution, very fast paced – we also need to evolve, very fast!