Unlike the
other models described in this book, customer analytics analyzes, predicts, and
prescribes at the very individual level. The main idea is that a company has at
its disposal “customer equity,” which is the sum of the values of each
customer. This value is determined by several clients’ behavior, such as the
amount spent, purchase frequency, level of recommendation, and so on.
Customer analytics
allows companies to segment their customer base properly and personalize
products and services for each group of clients or even each individual client.
Personalization enables them to retain their most valuable customers and
increase customers’ value by properly implementing commercial techniques, such
as upselling, cross-selling, recommendation programs, and so on.
Data at the
individual level are more complicated to obtain and more complex to analyze
than aggregated data. The majority of this information comes from historical
market data (a company’s data concerning purchases, customers’ actions, and
profiling data), but they are usually complemented with survey data.