What metrics can you use to track your team's client relationship building and maintenance?

the effectiveness of NPS depends on its usage. Combining NPS surveys from executive buyers with in-product feedback creates a strong renewal health indicator. Layering NPS with churn data enhances renewal prediction analytics. Segmenting NPS helps identify patterns in buyer behavior, allowing targeted improvements in areas with high detractor scores. Integrating more data with NPS deepens understanding of its implications for your business.

First step to build a record is to document data, so in order to analyse history and improve our service we all should keep a client's chart.

I would use NPS just to see trends in sentiment. Churn data has shown that NPS cannot be used for predicting anything. It will always be different in different cultures, NPS in north america is higher than europe, and europe will have it's own distinctions.

Track client relationships with key metrics like CLV, NPS, churn rate, engagement, CSAT, FCR, response time, social media sentiment, renewal rate, and employee satisfaction. This data can guide improvements and drive client success.

NPS is not just about the score itself but understanding it in context. Pair it with metrics like Net Revenue Retention (NRR), expansions, and, most crucially, whether client goals are being achieved. Moreover, the real power of NPS lies in actionable insights. When faced with a detractor score, swift action is essential. Reach out to the client promptly, assure them of your commitment, and outline tangible action points to address their concerns. This proactive approach not only resolves issues but demonstrates a dedication to continuous improvement and client satisfaction.

I would not use this for tracking how my team is building relationships. This is heavily influenced by so many aspects that has nothing to do with your teams performance.

Customer engagement is one of the metrics I would consider to measure a team's engagement with the client. Monitoring product usage, e-mail responses, regular cadence and feedback mechanism will provide a great insight into a customer's world. Their usage of the product / services and how relevant the features are to their requirements will be a key to gauge their satisfaction and sentiment.

Use CSAT after specific touchpoints. It will give you satisfaction evaluation of individual touchpoints. This will be useful when designing the customer journey and iterating on specific touchpoints and lifecycle.

CES is an important metric to measure satisfaction and loyalty, and is also relatively easy to implement across multiple feedback channels. It feeds into your customer support and marketing strategy and helps optimise the way information is presented and delivered to customers through these teams. It is important to note, however, that the true power of CES is unleashed when it is used along with other customer satisfaction metrics such as Customer Satisfaction and Net promoter score (NPS) to get a fuller, more accurate picture of the customer’s experience.

Incorporating AI rather than standard methods or survey based assessments can bring in HUGE insights. Instead of the limited self reported survey data, use AI software to analyze your existing client communications - emails, chats, zoom meetings or calls, etc - to evaluate the language they use and the positive/negative emotions and responses in the verbiage. This gives you far more actionable information and on a more granular level, and much better overall representation since it requires no extra participation from the client.

The traditional tools, such as CSAT, NPS, are used to measure the overall experience of a client, as quantitative tools, they may not be leveraged effectively for performance evaluations but rather they will be seen and acknowledged as an administrative survey. Often times, they will also mask the areas where the real dissatisfaction lies. AI-produced insights coming from the qualitative data (for example; comments, emails) entered through the digital touchpoints used by clients, can be more impactful, as such insights can point the service/product provider to the right root cause analysis for defining targeted performance improvements as well as they help to predict the client sentiment once the right improvements are made by the provider.