Importance of data analytics in understanding consumer behavior


  • By Mr. Vikram Kumar, Co-Founder and Managing Director, SRV Media Pvt. Ltd


To understand data analytics and why it is crucial, we need to first understand what data is and why there is a need to analyze it. Data, in common terms, is the representation of information. It can be qualitative or quantitative, coded or formatted depending on the use of that information. Data analysis, on the other hand, means deriving the meaning of the information for which the data has been collected. It is the logical method of evaluating the data and determining the most accurate and appropriate interpretation of it so that the knowledge extracted can be put to good use. Without the analysis of data, we would not have a clear understanding of what the market needs and what can help the market grow. There would be a huge gap between personalized demand and standard supply. Data analysis is the bridge that connects the creator with the consumer.

There was a time when chips were available only in one flavor, there was no women health drink and child care was not a market. Now we have a variety of choices when it comes to the flavor of chips, there are companies specifically focusing on women’s health and child care is the most lucrative market. This is the wonder of good data analytics. In the current market scenario where consumers are more expressive and want personalized choices, data analysis is the key to decipher consumer data and open up new product avenues and market segments. Consumer behavior and needs have always been the inspiration for customization and introducing new products in the market. With time, consumers have proved to be the best R&D for a company; on that account, companies have taken the effort to understand their consumers better, where data has always played a significant role. 

In the present market scenario, it is not only about the consumer anymore, but also about the competitor and other players in the market. Numerous companies are making the same product and the consumers are spoilt for choice. Apart from just the product, various other factors play a part in the consumer’s buying decision. In this era of digital overexposure and easy availability of information, the journey of converting a potential buyer into a loyal customer is complex and takes a deeper understanding of the consumer’s motivation, background, financial condition, preferences, choices and purchasing patterns. Tracing a customer’s digital footprint is also one of the most thriving marketing strategies these days. Now whatever we gain from all of these activities is data; the only thing that makes a difference at this stage is how a company interprets that data. Creating a product is not enough. Using the data in hand as the fuel, companies have now started working on how to market and sell a good product. 

Data analytics has become more elaborate in the form of its use to obtain meaningful and tailored marketing messages and patterns. The most popular way of interpreting data these days is predictive analytics where you predict the sales and revenue of a product or service based on collected data points by segmenting customers and deciding the factors that will affect sales of the product like price, packaging, and message the product conveys. Businesses want to be prepared for their customers, rather than the other way around. When a customer walks into a shoe store, he or she expects to find a variety of options; it can be flats, heels, wedges, slippers, shoes, floaters, but if the businessman does not have these options handy he might send a customer home disappointed and face the reality of losing that customer forever. On the other hand, if he takes the help of data and gains insight into what his customers might want to buy and keep those options available, he might end up selling two footwear instead of one. In a similar pattern, companies producing the same product, use data as a catalyst to introduce offers, deals, benefits, and features in their product to make it stand out and hence influence the customer to choose their product over the others.

The market is moving towards becoming consumer-friendly where the companies care about their customer satisfaction and retention. Data analytics is the most proficient way of gaining customer loyalty as well. Finding out what the customer likes and dislikes and what the customer believes in with the help of conjoint analysis helps the company put their best foot forward. We are looking forward to a time where, with the help of data analytics, companies can maximize their ROI by efficiently implementing data available to them.

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