In 2016, Spanish banking group BBVA offered to its Spain-based customers a personal finance management app. One of the app’s tools used machine learning algorithms to sort customer transactions into common budgeting categories such as rent, food, and entertainment, and then it displayed a customer’s expenditures broken down as a simple chart. BBVA promoted the categorizer on its digital banking website as a way for customers to better manage their personal budgets. In just a year and a half, the tool became the most utilized feature on the BBVA website, second only to funds transfer.
The researchers have explored data wrapping as a distinct data monetization phenomenon since 2013, drawing on dozens of executive and project team interviews, hundreds of publicly available use cases, in-depth case studies of BBVA, Cochlear, and PepsiCo, and a global survey of 511 product managers responsible for generating revenues from products.
And in 2019, the global consumer packaged-goods company PepsiCo formally launched a suite of data analytics capabilities called Pep Worx that supported a variety of use cases — such as how to successfully launch and manage innovative marketing programs and how to optimize total store space — that helped retail customers increase product turns, profit realization, and net price realization (the latter because there was less of a need to discount products that weren’t selling). PepsiCo developed the capabilities over a four-year period as the company solved problems for select retail customers using data analytics-based shopper insights. PepsiCo has used Pep Worx to help transform the nature of its retail customer relationships from transactional to collaborative by creating a “three-audience win” whereby sales or marketing activities simultaneously deliver value for the shopper, the retailer, and PepsiCo.