Actioned Analytics Pave the Way to New Customer Value

The typical modern company is swimming in data. Whether in the form of inventory flows, manufacturing decisions, customer inquiries, or app and website clicks, there are vast quantities of data created and consumed every day. Yet managers continue to find it challenging to use this data to create new value for customers.

We blame this data paradox on the classic data-insight-action framework. The familiar process lulls managers into thinking that producing “valuable” data or surfacing insights for their customers is enough. This encourages passivity, and companies become much too trusting that customers will actually use and act upon the information provided. As a result, companies deploy analytics-based features and experiences that customers don’t use. And, because there is no action, there also is no value creation, and certainly no value capture, by the company.

Consider consumer banking. When banks initially established mobile banking apps, they focused on providing customers with data (for example, transaction histories) and insights (such as spend patterns, often in the form of a pie chart broken out into categories like rent, utilities, and food). Banks proficient at delighting customers, however, went a step further. Global bank group BBVA, for example, bundled spend insights with customer stories, tutorial videos, and recommended next steps intended to motivate customers to benefit from their information. Over time, BBVA introduced features into its mobile app that integrated predicted outflows into a customer’s digital calendar, automatically saved money toward a desired savings goal, and connected the customer with a BBVA financial adviser to execute a suggested investment opportunity.

Our research (see “The Research”) indicates that analytics-based experiences and product features for customers pay off only when combined with aggressive tactics that all but guarantee that customer value materializes. Companies that do this well rely less on a sequential data-insight-action process and focus instead on interweaving insights and action activities to deliver actioned analytics to their customers.