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The System

Robust Operational and Analytic Infrastructure

Robust Operational and Analytic Infrastructure

An effective Net Promoter System requires organizational advocacy, significant IT investments and analytics capabilities. 

At the heart of the Net Promoter System is fast-cycle closed-loop feedback. This requires support from a robust operational infrastructure that can trigger feedback requests, capture the responses, send them to the right employees, track follow-up, and support data-mining and insight generation.

Building a Robust Infrastructure

Building a Robust Infrastructure

Loyalty leaders support the Net Promoter System by focusing investments in three areas. 

Advocacy organization

The best Net Promoter® companies typically have a team leading the effort, spearheaded by a customer advocacy officer (CAO). This team is responsible for maintaining the rigor and consistency of the Net Promoter process, as well as improving the company’s relationships with its customers. It rallies disparate departments around the mission of serving customers and bringing the voice of the customer into decision making. Just as you wouldn’t want each business unit or team to create its own accounting procedures and serve as its own financial controller, you don’t want individual units wholly responsible for collecting and evaluating customer feedback.

The CAO is typically a seasoned, savvy executive who can lead an effective charge and build support for the system over time. This executive must overcome the inevitable resistance, inspire the troops and get things moving in the right direction.

IT systems

Large, complex organizations that run on enterprise software require significant IT investments to integrate Net Promoter into their broader operating systems. Several specialized software providers offer services that can help support a high quality Net Promoter System. These include Satmetrix, Medallia and CustomerGauge, for support of the data collection, reporting and auctioning, as well as Clarabridge, which support the text analytics needs associated with open-ended feedback and follow-up call comment capture. (For more providers, see the Net Promoter System vendor page.)

Net Promoter System requirements can be complex. An insurance firm that wants to conduct transaction surveys, for instance, must have a system capable of combing the transaction database to create an appropriate sample of customers who dealt with the company following important interactions. The sample needs to be large enough to yield an appropriate number of responses for each department, or possibly even each representative, yet must avoid over-surveying any individual customer. Once the Net Promoter System has sent surveys to those customers, it must route customer responses to the desktop of the appropriate rep and his or her supervisor, along with details about the transaction, the NPS survey response (scores and verbatim) and other basic customer information.

The system must also flag those customers who need a follow-up interaction, routing the follow-up request and all the relevant information to the appropriate person. It must track the time between the request and actual customer contact (or failed contact), along with the data generated during the contact, including actions taken and call outcomes.

Analytic capabilities

Analytics are very important for informing actions to improve the customer experience or the product design. Say, for example, the claims department wants to determine how the amount of time it takes to process a claim affects its Net Promoter Score®. It must be able to sort through a database of claims interactions for which surveys were completed, sorting by time to resolution. It must be able to sort further by product, customer segment, claims type, claims outcome and several other factors. Moreover, among those assigning low scores to the experience, the claims leadership needs to be able to dig into comments and follow-up call records for those customers who gave low scores so that they can discover what impact time-to-resolution had versus other factors, such as rep treatment. The same goes for any other types of analysis a company would likely need, cutting the data by geography, customer tenure, share of wallet and other variables to help determine how to improve the process in the future.

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