Consumer Insights & Data Analytics: The Ying and Yang of HOW and WHAT!

Consumer Insights & Data Analytics are often thought as same or derivatives of each other, however that is a myth.

Data Analysts address the ‘what is happening’, Consumer Insights illuminates ‘how’. Combination of both, Data Analytics (WHAT) & Consumer Insights (HOW) is key to make consumer focused business decisions – for Marketing, Product, Sales, Experience – overall business!

What is Consumer Insight and why is it important?

Being metaphorical, the function of consumer insights is like a lantern in a dark forest; that lets you see what’s around you. With the help of this lantern, you can see the different paths you can take and pick the best one.

Like the lantern, Customer Insights, helps us to understand our existing and potential customer’s needs, motivations, and challenges; to understand how we can appeal to their needs. Consumer Insight designs market research, which is the source of truth.

One simple example of such a research project for a bank can be a quantitative study to understand how people approach savings. Designed to understand how people approach anything related to money, why do they save, how do they prioritize, what they want to achieve & what do they want to do with the savings. And as a business, when we know their motivations, we can more easily understand how they decide, and using that make business & marketing decisions.

The difference between Consumer Insights and Insights from Data Analysts (usually)

The main differentiation between data analysts in many analytics teams and a consumer insights professional is usually data being internal vs. external. Each company is different, but these are the main differences.

Data analysts usually deal with the data retrieved from internal data sources because of actual actions, while consumer insights are in the context and reasoning of actions, trying to understand the assessment of people about a specific business question outside of the company.

To shed light on the given topic, consumer insights people design studies which can be quantitative surveys, qualitative interviews, or a combination of both. By using the data collected in these surveys and sentiments of people, you can distil all the learnings and takeaways of a specific study.

Example of collaboration between data analysts and consumer insights: FMCG (fast-moving consumer goods) companies gather data of purchases by their consumers. Data from this sample is projected country wide by statisticians and operations colleagues, so to interpret category and market trends along with observing competitor performance. Data analysts use this large pool of data, filtering, regrouping approaches to shed light on specific business questions.

When collaboration with data analysts brings high value!

We can get better results when we combine the capabilities of different insights domains. The Data Analyst team can take data that Consumer Insights have gathered from running surveys and filter according to specific needs.

For example, to filter out why people bought our product for a while and then switched to a competitor’s product. Data analysts can identity these customers, who have switched & consumer insighters would reach out to a sample and similar customer (persona wise) and ask why.

In the above example, data analyst help in being specific to ‘what/whom’ to ask, while consumer insighters define the ‘how’, ‘why’ & ‘what’. Otherwise, everyone would round, asking 100’s of random people questions, without any solid answer, or vis-a-versa.

Collaboration between both, gives an advanced point: a hyper-relevant audience. Combining the learnings from the consumer insights with specific answers from Data Analysts, would enable Consumer-Driven Solutions, which is based on data & consumer understanding, will the business TRUE TO ITS CORE – RELEVANT & CONSUMER ORIENTED.

So rounding up, collaboration between consumers insighters and data analyst enables a qualitative deeper dive into ‘what’, ‘how’ and ‘why’ of the consumer, leading to make solutions consumer-driven and not purely data, making business more consumer/customer oriented.

Key ingredients of successful collaboration between Customer Insight and Data Analytics

In growing organizations, there are many team while deal with insights and data, and there are two key ingredient of collaboration and success.

Firstly, if each insights team has a clear understanding of responsibilities and expertise, that’s a good starting point. If there is too much overlap, then there can be too much grey area that can be hard to manage. The big tip I have is to give a great deal of consideration to how to avoid or manage that gray zone. The business question can enjoy full focus once the roles and responsibilities have been clarified. Each team can then decide on how they can contribute and work in their own way.

Secondly, have a common link between them, which can be in form of a strategist or core team, which focuses on ‘solving business problems. These can the hub points, which contextualize the business questions while merging findings, to come up with conclusive recommendations & proactive way forward.

Business wins when insights teams collaborate

Relevant insights are core requirements for businesses to thrive in an efficient way. Consumer insights generate context to the insights that data analysts can retrieve from internal data — and vice versa!