Behavioral analytics

Not to be confused with Applied behavior analysis.

Behavioral analytics is a subset of business analytics that focuses on how and why users of eCommerce platforms, online games, & web applications behave. While business analytics has a more broad focus on the who, what, where and when of business intelligence, behavioral analytics narrows that scope, allowing one to take seemingly unrelated data points in order to extrapolate, predict and determine errors and future trends . It takes a more holistic and human view of data, connecting individual data points to tell us not only what is happening, but also how and why it is happening.

Behavioral analytics utilizes user data captured while the web application, game, or website is in use by analytic platforms like Google Analytics. Platform traffic data like navigation paths, clicks, social media interactions, purchasing decisions and marketing responsiveness is all recorded. Also, other more specific advertising metrics like click-to-conversion time, and comparisons between other metrics like the monetary value of an order and the amount of time spent on the site. These data points are then compiled and analyzed, whether by looking and the timeline progression from when a user first entered the platform until a sale was made, or what other products a user bought or looked at before this purchase. Behavioral analysis allows future actions and trends to be predicted based on all the data collected .

Examples & real world applications

Data shows that a large percentage of users using a certain eCommerce platform found it by searching for “Thai food” on Google. After landing on the homepage, most people spent some time on the “Asian Food” page and then logged off without placing an order. Looking at each of these events as separate data points does not represent what is really going on and why people did not make a purchase. However, viewing these data points as a representation of overall user behavior enables one to interpolate how and why users acted in this particular case.

Behavioral analytics looks at all site traffic and page views as a timeline of connected events that did not lead to orders. Since most users left after viewing the “Asian Food” page, there could be a disconnect between what they are searching for on Google and what the “Asian Food” page displays. Knowing this, a quick look at the “Asian Food” page reveals that it does not display Thai food prominently and thus people do not think it is actually offered, even though it is.

Behavioral analytics is becoming increasingly popular in commercial environments. Amazon.com is a leader 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.

Types of Behavioral Analytics

• Ecommerce & Retail- Product recommendations and predicting future sales trends
• Online Gaming- Predicting usage trends, load, and user preferences in future releases
• Application Development- Determining how users use and application to predict future usage and preferences.

History

(Direct Quote from business analytics) "Analytics have been used in business since the time management exercises that were initiated by Frederick Winslow Taylor in the late 19th century. Henry Ford measured pacing of assembly line. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have evolved with the development of enterprise resource planning (ERP) systems, data warehouses, and a wide variety of other hardware and software tools and applications.

With the recent explosion of big data and intuitive BI tools, data is more accessible to business professionals and managers than ever before. Thus there is a big opportunity to make better decisions using that data to drive incremental revenue, decrease cost and loss by building better products, improving customer experience, catching fraud before it happens, improving customer engagement through targeting and customization- all with the power of data."

Behavioral analytics is a recent and significant part of this “explosion of big data” that is becoming more common and affordable. Many companies like CoolaData and Omniture are beginning to offer behavioral analytics as a service in order to increase customer turnover and retention.

See also

• Big data
• Data mining
• Analytics
• Business Intelligence
• Test and Learn
• Business Process Discovery
• Statistics
• Customer dynamics

Further reading

Nagaitis, Mark. "Behavioral Analytics: The Why and How of E-Shopping - See more at: http://www.ecommercetimes.com/story/62061.html#sthash.z9P1HWrB.dpuf". eCommerce Times. {{cite web}}: External link in |title= (help)