Data-Looping

Data Looping for a Better Customer Experience

By simply gathering data without closing the data loop, big data stays just that — big. Data looping puts the processes and the right people in place to extract meaningful insights around key every point in the customer’s journey.

Data looping is a strategy that’s used to help teams know which growth levers to push and pull in the organization. By offering deep insights into the motivations and behavioral patterns of both employees and customers, teams can pinpoint the exact areas where value is provided from an emotional and logical point of view.

In getting down to the root-cause analysis of what’s happening, brands are equipped to deepen their understanding around the contiguous customer journey and overarching purchase behaviors. This wider perspective allows companies to monetize initiatives with less risk and more reward.

Closing & Visualizing the Data Loop

Collecting data for the sake of data collection spells trouble. Rolling data back in and closing the data loop is key to gleaning in-depth insights. These insights must then be dispersed across the organization to keep teams moving together in harmony towards the same end goal with the same information.

Visualize data to extract actionable, humanized insights, ensures you’ll get some kind of return on that investment.
From gaining team buy-in to spotting patterns before they become costly for the organization, teams benefit from closing the data loop with visuals that can be democratized across the organization.