Consumer analytics involves the techniques through which customer’s behavior is recorded and business decisions are taken with the help of analytical tools and techniques. One of the important objectives of consumer analytics is to cope up with the ever changing consumer behavior. This is the digital age where consumers look out for more and more choices, meeting those becomes extremely difficult with the help of conventional marketing tools and techniques. This is where big data analytics helps businesses track the consumer behavior, with the help of various data mining and predictive modeling tools.
One of the applications of consumer analytics is the in-store analytics, which involves mapping the consumer purchase pattern, consumer demographics, what the customer bought, why did the customer buy, why did not the customer buy a product, etc. In-store analytics is applied to the retail business, where technologies like smart carts, RFID are used tags to map the location of products to determine the movement of those. This technology helps in finding what products to consumers prefer the most, which product doesn’t sell anymore, etc. The fashion retail industry is one of the industries where consumer analytics is used intensively, since the trends changes in fashion industry even within a span of 3 months. So it is important to track the consumer behavior closely in this industry.
Another important application of consumer analytics in retail space is in hypermarkets, like Walmart, Tesco, etc. Here buying behavior of each and every customer is captured and promotions, offers are given to the customer based on their purchase pattern. Hypermarkets also use various predictive techniques to estimate demand for a particular product in future. A typical example is where pregnant ladies are identified through their purchase pattern and with the help of this data the demand for baby products like diapers, baby oil, baby clothes, etc are predicted.
Sentimental analysis is another powerful tool where the feelings of the customers are studied for a certain product or a service. One instance where a mobile phone manufacturer wanted to know what people felt about 4G technology, the result of the analysis was that people viewed 4G as a feature of a smartphone. Thus the company positioned its mobile phone as “The best 4G phone”. Consumer analytics not only serves as a tool to predict the consumer buying behavior but also enables companies to design ads that cater to the customer’s needs.
With the help of web analytics it is possible to track how much time that the customer spends on a company’s website, what product does he/she buy often, what category is he/she interested in, etc. These data put together helps the company to provide ads and offers to that particular product category, which is more relevant and cost effective.
Today the trend is shifting from segment-based marketing to individual based marketing. Mass marketing is no longer valid in today’s competitive environment and ever-changing consumer expectations, so individual based marketing is what will make a brand sustain in the market. A typical example of individual marketing is in the fashion industry where the customer can choose their own outfit through a mobile application; customize the outfit according to the need. Once the customization is done, the customer can then visit the store at the desired time to try on the outfit. This customized offering of products helps consumers to enjoy products tailored to meet their own need, rather than choosing from a set of available products. Individual customization would be impossible without the use of big data and predictive modeling, where millions of data from millions of customers are tracked to predict what the customer will buy.
Consumer analytics starts right from customer profiling to what the customer is likely to buy. Consumer analytics has a wide range of applications from retails stores, hypermarkets, e-tailing and much more, and its role is becoming larger and larger very day. Thus consumer analytics plays an important role both in major and minor decisions taken by a business.