Consumer Insights and Data Analytics: The ying and yang of how and what

What is  Consumer Insight and why is it important for organizations?

Being metaphorical, the function of consumer insights is 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. I try to understand our existing and potential customer’s needs, motivations and challenges in order to understand how we can appeal to their needs. 

Consumer Insights designs market research to fit the business question. One example of such a research project for a language school can be a quantitative study to understand how people approach language learning, why they want to learn, and what they want to achieve. When we know their language learning motivations, we can more easily understand how they can become students and keep learning.  

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 internal vs. external. Each company is different, but these are the main differences I have seen in my career.

Data analysts usually deal with the data retrieved from internal data sources as a result 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 distill all the learnings and takeaways of a specific study. 

Another example of collaboration between data analysts and consumer insights was when I was working in consumer goods, we were gathering data about FMCG (fast-moving consumer goods) purchases of consumers. Data from the sample was projected country wide by statisticians and operations colleagues, so that we got to interpret category and market trends along with observing competitor performance. We were discussing the business questions with data analysts, who were then playing around with this vast data set via different filtering and regrouping approaches to shed light on specific questions.  

When collaboration with data analysts brings high value

We can get better results when we combine the capabilities of different insights domains.

Back when I was working at the world’s leading market research companies, the data teams were able to take data that Consumer Insights had gathered from the survey and filter according to specific dimensions. For example, they were able to filter out why people bought our product for a while and then switched to a competitor’s product. We in consumer insights would reach out and ask why those consumers quit using our brand. Thanks to the collaboration between Consumer Insights and Data Analytics, we were able to follow up with a qualitative deeper dive into specific questions that made our insights more tangible and more valuable to the company.

If I would have asked 100 people randomly, the chances would have been slim that I would find such churners, leveraging reach and filtering capacities, we were able to start from an advanced point, because we have a hyper-relevant audience to begin with. 

Key ingredients of successful collaboration between Customer Insight and Data Analytics

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 gray 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. They can merge findings and come up with conclusive findings and recommendations.

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. 

Who is Tuğçe Hamzalıoğlu?

Tuğçe has ~10 years of progressive experience in various expertise like market research, insight generation, data analysis, digital marketing, and B2B & B2C sales.

Her track record of translating data into intelligence has its roots in 7 years of work experience at the world’s 1st (Nielsen) and 3rd (Ipsos) ranking market research companies. She has accelerated a wide spectrum of businesses from Fortune 500 companies, to start-ups on their pursuits through analytics-driven consumer insights and strategies.

She has a Digital Marketing master’s degree from Trinity College Dublin.

Note from Elizabeth about related Content:

Data-as-Service Lessons from the Company that was Right about Trump: The importance of sentiment analysis and strength of sentiment in insights. 

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