At a certain point NPS and other customer experience data reaches its expiration date. It has lost its value in terms of relevance and the opportunity to act upon. A challenge for CX programs is ensuring the customer data disseminated to your organization is as fresh as possible.

When it comes to relationship feedback, sending surveys once or twice a year in “waves” is no longer adequate in terms of frequency. It also gives the impression to your employees that attention to NPS is only required once or twice a year, rather than an ongoing engagement with customers integrated into business operations. We recommend a “waveless” approach with surveys going out on a continual basis. It should be noted that this can be easily accomplished without impacting survey toxicity rules, which should remain in effect.

Where continuous surveying is not feasible, we have seen a batched approach work well. A subscription-based software company for example can use account batching with survey timing based on renewal date. The advantage is that feedback is available to account stakeholders 6 months in advance of renewal date. This gives teams time to intervene with at risk accounts in time to “save” the renewal. We recommend having your survey tool integrated with your CRM to seamlessly automate survey timing based on renewal date.

Below is an example from a software company who chose survey outcast 9 months in advance of renewal to provide sales teams with key information to guide their renewal strategies.

For transactional feedback there are two approaches to keep data flowing. Better in terms of real time feedback is the Always On option. This could be via a mobile app or a kiosk always ready to receive your customer’s feedback in the moment they are experiencing your product or service. The other is a triggered invitation to provide feedback at the conclusion of an event or interaction. The delivery mechanism could be text or email, keeping in mind that it needs to be sent soon after the event so the experience is still fresh in the customer’s memory.

The optimal scenario for fresh data is the Spectrum AI model where machine learning is applied to multiple attitudinal and operational data inputs to continuously deliver the most powerful CX metric, Spectrum NPS.

Far too many programs stop at the foundational step of collecting NPS scores through surveys. Even those programs that follow the demonstrated best practices in this guide by building out additional sources of attitudinal data usually stop before they take the transformative step of including operational data, which is a critical building block for predictive scoring. A complete, connected, and continuous set of data is a prerequisite for predictive scoring and a visionary NPS program. To get there, download our guide, take our comprehensive training course, or read about the future of NPS.