By Mike Poyser of CMA's Customer Insights & Analytics Council
Over the last decade, companies in all industries and countries have been realising the power of their data. There is not a business today in Canada which does not place importance on the data that they collect; although companies are at different stages in their ability to mine and create value from their data.
This has had a profound impact on how companies understand their customers and how they make decisions on how best to run their business. It has led to the creation or growth of Analytics departments, tasked with "owning the data" and "monetising" value from the data. It has also had a profound impact on the traditional function that provides insight into the customer: the research department.
In many instances, the research department has been left in the shade, as data-led functions have received increased investment and are seen either as the more accurate, more rapid or more modern way to answer key business questions. However, there are a number of companies who have recognised that this is short-sighted.
One of these is the UK supermarket chain Sainsbury's. At Sainsbury's they talk frequently about the "voice of the customer", with a strong emphasis on listening to their customers at every opportunity. This is through the interaction between their 'frontline' staff in their stores and their customers – at the checkout, in the carpark or while stacking the shelves. It is also in their daily, weekly and monthly market research, whether carried out in store, on-line, by phone or in focus groups. Sainsbury's was quick to realise that they also had another major source of listening to their customers: their data. While they can speak to thousands of customers per week in their research studies, they collect data on their 12+ million shoppers. And they view their data and the mining of the data as an extension of the "voice of the customer". Questions on how they should change an assortment, or how the latest marketing campaign is performing are therefore answered by a combination of research and data analytics.
Smart companies are therefore viewing research and analytics as very much complementary. Even smarter companies are taking this a step further and integrating these functions into one department. One such example of this is Aimia, where the research and data insight functions are combined into one team, under an Analytics banner. The centralisation of these functions create synergies. Business questions are triaged in the same intake process, by colleagues who work on the same team. This enables two things: firstly, the best way to answer the question is quickly determined. Sometimes this might lead to a data analytics project and other times it might lead to a piece of research. Secondly, it also enables the data analytics and research functions to work more hand-in-hand. Particularly for longer projects, there may be a need for a combination of research and data analytics. These are best done in combination to ensure that learnings are more efficient and more effective.
The roles of the research and analytics teams are still evolving and companies will go down different paths in how they address these functions. However, one thing is for sure: analytics and research both are critical functions to running a business, and neither is able to do the entire job of the other. They should therefore be used in combination to ensure that there are synergies and efficiencies in how businesses "listen" to their customers and make key business decisions.