The innovation trinity

As an industry, market research professionals have a history of being overly sceptical when it comes to assessing our capacity to innovate and evolve. 

Every wave of technological innovation to impact our industry, brings with it prophecies that the industry will suffer as a result. Yet, it continues to grow and thrive. The central reason for this is that businesses will always want to understand consumer behaviour to make better decisions – and this is what we as researchers do, day in, day out.

In fact, if we step back and take a wider view, there has already been a large amount of innovation in market research over the past few years. From the automation of survey design and data delivery, mobile survey design, to the use of passive data and thinking as well as more evolved approaches informed by neuroscience and behavioural economics.  All of which have challenged us as businesses, while empowering us as researchers.   

Despite this, the market research industry now finds itself at a crossroads. For 70 years the raison d’etre of market research was to collect ‘data’ that provided us with an understanding of human behaviour, because that data didn’t exist elsewhere. As we know, this need for market research to provide data has been eroding  with the relentless explosion of digital data. Furthermore, Gartner predicts that one in three jobs will be converted to software, robots and smart machines by 2025 and the market research industry will be affected by these forces, just like every other professional service industry.

Not only this, but clients are moving spend away from surveys and towards new sources of data, and rather than needing researchers to help them get information, they need us to help them interpret data to gain insights and identify actions to take.  Although no industry is better placed to do this, we don’t always have the data capabilities needed to work with this new technology – and this is where data scientist skills are key to ensuring we innovate in the way our clients need us to. The trick is integrating these skills into a traditional market research setting, while remaining innovative.

To do this, we could look through the lens of an innovation trinity – speed, prediction and connectivity.  Speed is about creating solutions that get data and insight to clients much quicker, but also closer to the moment decisions are made. For example understanding the purchase decision at the point of purchase, will give us a more accurate understanding of motivations, but also how brands can influence that decision more effectively. Prediction requires analytics such as predictive modelling and machine learning to gain foresight about future behaviour and events. Whereas connectivity is about linking the many forms of data we have available to us including location data, customer database information, passive device data and survey data to get a single view of the customer.

Delivering these three innovation needs requires market research companies to embrace new skill sets; combining the new world, with some of the more ‘traditional’ market research capabilities we have already mastered.

Data engineers for example can help bring structure to disparate unstructured data sets, while data scientists are required to analyse this data to extract the most relevant information, and what I call ‘data connectors’ are required to bring it this together in a way that identifies ‘insights’ that will help make an impact on a brands’ business strategy.  

This is why we recently established an ‘Innovation Hub’, which allows us to integrate these newer skills sets with the core skills of some the best market researchers in the country.  We can ensure we incorporate the right level of innovation and the requirements of speed, prediction and connectivity, while retaining our capability to bring insights alive and identify actions, through clear impactful storytelling.   

Phil Sutcliffe is board director for innovation, TNS UK