consumer insights (CI)

Why Consumer Insights (CI) and Analytics Teams Should Merge

“Any data without context is useless, and CI can give you that context. What, when, how, and what next can be learnt through data, but why is answered only by CI.”

Editor’s Note:  This piece from Analytics India references issues specific to India’s consumer landscape but the thinking here is universal and applies to customer-facing organizations everywhere. 

Consumer insights (CI) refers to the practice of looking for patterns in customer behaviour and using the findings to inform a business’ marketing strategy. Organisations usually have dedicated CI teams to improve their product pipeline and push sales. Of late, companies have started leveraging data to gain insights into their potential consumers. Though analytics teams have become an integral part of the decision-making process, some companies still keep the CI teams siloed.

We spoke to a few industry experts to understand if it makes sense to combine both CI and analytics teams.

Tectonic Shift

CI teams crossed the Rubicon once data entered the scene. “CI teams were first set up in the 50s, but the importance of these teams then depended on the segment and the region,” said Mr Shardul Kadam, Senior Consulting Associate – Insights at Ideosphere Consulting.  “In the Western market, these teams were considered important from the very start. However, in traditional markets like Asia, they didn’t see its importance, because they were already connected with the consumers.”

Back then, the consumer insights (CI) teams conducted research by sending foot soldiers on the field to gather information; the process was both time-consuming and costly. This was before data became central to insights extraction across every sector and department.

“The overall process to just collate data used to take three months,” said Dr Ashish Ranjan, Customer Insights Manager at Sanofi, and an experienced management consultant in the pharmaceutical industry, “People had to actually step out for interviews, and a lot of their job was a qualitative market research exercise.

“However, now we are living in an extremely volatile market, especially after the pandemic, as the information exchange between people has largely become digital. This is here to stay even after the pandemic.”

Intents And Purposes

So we have asked Mr Kadm, are CI teams still relevant?  “Any data without context is useless, and CI can give you that context. What, when, how, and what next can be learnt through data, but why is answered only by CI,” said Mr Kadam. Moreover, good quality data is not always readily available in India.

“The data you get from different platforms are driven by their own algorithms and those algorithms are not matching across all platforms. Everyone has planned their output according to their ease of doing things,” said Dr Ranjan.

“Hence, as much as we want to believe that the data is sacrosanct, in the Indian setting, it is not. There are various problems in terms of how the data is collected and interpreted,” he added.

Blending CI & Analytics

It’s safe to assume that both CI and analytics teams are relevant, and organisations should harness their synergy to chart their future course. “Currently, both CI and analytics teams think their Key Result Areas (KRAs) are different. However, they are actually paid for the same purpose,” said Mr Kadam.  “Both the teams have to justify their own expense, and because of this, they fear merging and are competing with each other. They are always thinking of how we can add value better than the other team and are finding disadvantages of each other when they actually should be working together.” Thus, spending on two different teams with the same objective is redundant, cost-inefficient, and breeds ambiguity.

“If data analytics and CI teams don’t work together they will lose out on getting a more comprehensive picture of the market,” said Dr Ranjan, “Data will speak whatever the data wants to speak and we all know one can also manipulate it in many ways. But how do I ensure that this reflects the market?  “If you do not have both of these teams working together, then one is betted against the other. And if data and the market speak differently, a business leader will believe the version that fits their story.”

“The ideal situation would be that my data and CI team talk the same language, and hence we come to the same conclusion. The idea is to pivot all of the activities, be it by the analytics team or the CI team, and bring them on the same platform where one can influence, suggest, and convince each other more clearly.”

Going Forward

While it is very easy to want both the teams to collaborate, Dr Ranjan thinks it is easier said than done. “The first step you need to take is to put these teams together. As an organisation, one should start cross-pollination more and there should be more discussion on an on-going basis,” said Dr Ranjan.  “Once we do this, it will create a lot of friction between the two teams as everyone will come with their ideologies about their functioning and the importance of the information that they bring.

“However, once you cross this bridge and bring them together, you build a system where inputs from both these teams are taken together. There is a way of working with data, that the analytics team will be best at and then there is the consumer insights (CI) team which has all the information on customer preferences. Hence, it has to be a well-thought-out framework that distills information from both these sources,” he added.

This article originally appeared in Analytics India Magazine. Photo by Boxed Water Is Better on Unsplash.

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