Behavioral analytics – an introduction
Behavioral analytics, as Wikipedia says, is a recent advancement in business analytics that reveals new insights into the behavior of consumers on eCommerce platforms, online games, web and mobile applications, and IoT. Behavioral analytics establish the foundation of customer knowledge and focuses on understanding how consumers act and why, enabling accurate predictions about how they are likely to act in the future. It enables marketers to make the right offers to the right consumer segments at the right time.
Customers can either be consumers, businesses, or individuals within a business, but Behavioral Data can always be tied back to a single person. this person can be a known individual or anonymous. This data is typically created and stored in the form of an ‘event’, e.g. an action that was taken. Think of events as the ‘what’ and the properties as the ‘who, what, when, and where.’ This data creates a complete description of behavior – just without one answer “WHY”. Behavioral Analytics comes in to understand the WHY of customer behavior. Understanding why customers do things allows us to optimize our full acquisition, conversion, and retention lifecycle, and generate critical insights day-to-day in different sector.
Present applications in various industries
Financial services organizations leverage behavioral analytics to identify suspicious and anomalous behavioral patterns as a means to strengthen anti-fraud capabilities. They link demographic data and traffic patterns to customer profiles to figure out where to locate branches and other service outsets.
Retailers closely track customer pathing across channels; when, where, how frequently and for which transaction types do customers use various channels or how they respond to email campaigns, mobile couponing or even television ads.
Communications providers enrich customer information with external sources and network usage patterns to gain better views of subscriber behavior.
Behavioral analytics is becoming increasingly popular in commercial environments. Amazon or Flipkart are leaders in using behavioral analytics to recommend additional products that customers are likely to buy based on their previous purchasing patterns on the site. Behavioral analytics is also used by Target to suggest products to customers in their retail stores, while political campaigns use it to determine how potential voters should be approached. In addition to retail and political applications, behavioral analytics is also used by banks and manufacturing firms to prioritize leads generated by their websites. Behavioral analytics also allow developers to manage users in online-gaming and web applications.
Prospect in India
Early adopters and top performers are already driving forward on all these big data fronts. They have created urgency to shape the future. Here again, the future is now – the future of big data will arrive faster for some organizations than for others.
Behavioral analytics has real applications beyond the realm of marketing and customer intelligence. There is sensor data that can track traffic patterns. It’s possible to know if cold storage chains have been broken or medications have been compromised during shipments. Such detailed and up-to-the-second views of goods moving across global supply chains are ultimately another flavor of behavioral analytics.
