The Metrics of Customer Success
The Metrics of Customer Success
Do we need to rethink how we measure success within our organization if we move towards a servitized or customer success focused model? This is something of a complex question, and in many ways, the answer is both yes and no.
From an operational perspective, as we put forward earlier in this paper, broadly what defines operational success in a transactional break-fix service offering largely remains the same definition of success that we would see in a servitized model.
To reiterate, in the traditional break-fix setup, metrics like mean-time-to-repair, first-time-fix-rate, and technician utilization are all indicators of how efficiently the service organization can meet the customer’s external demands and expectations.
In a servitized offering, those same metrics remain vital for ensuring that the field service operation is running at a level of efficiency that makes it both feasible and financially rewarding for the service provider to offer such as solution.
Yet as the Field Service News Research study from late 2019, Understanding the metrics that matter in a rapidly changing field service sector, revealed, of those organizations that had introduced some level of servitization into their service portfolio, over 80% of them had made changes to the KPIs they measure.
Also, remember the statistic we referenced earlier in this paper from that same report- over half (51%) of all field service organizations now placed equal importance on CSAT metrics as they did operational metrics – a statistic that has steadily risen year on year since Field Service News Research began hosting benchmarking studies in this area back in 2013.
Yet, when we think of customer satisfaction metrics, are these suitable to identify a measure of success in a servitized or customer success-based service design model?
Rudimentary statistics such as Net Promoter Score can offer a broad overview of service standards. More detailed tools like customer surveys allow more specific insights to come to the fore, and modern tools such as sentiment analysis can fill in the gaps between the two.
However, all CSAT metrics are the equivalent of driving while looking in the rearview mirror and while valuable indicators, are perhaps not focused enough for the end-goal of defining customer success.
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“CSAT metrics are the equivalentof driving while looking in the rearview mirror and while valuable indicators are perhaps not focused enough for the end-goal of defining customer success...”
In earlier sections of this paper, we have touched on how co-creation often lies at the heart of many successful servitization case studies and the potential importance of an onboarding team.
When it comes to defining the core metrics for a customer success-based service model, a critical role of the onboarding team (and also of pre-sales and/or account management) should be to work with the customer to identify a shared set of metrics that will shape how success is defined.
This may require data sets from both organizations to combine a new set of KPIs that allow the service provider to ensure they meet the requirements. Should these KPIs indicate an issue, then traditional operational KPIs can provide an insight as to why. Meanwhile, broader CSAT metrics can offer an indication of the overall temperature of the service organisations success.
This more complex understanding not only of what success looks like for each customer but also leveraging existing KPIs to ensure that is happening at the macro and granular level, serves once more to re-enforce the importance of not only having the tools to empower effective service delivery but also the critical importance of reporting tools that allow the service provider to quickly and easily keep their finger on the pulse of how the service operation is performing.
In addition, such reporting tools allow the service provider to offer a layer of transparency that is crucial in communicating with the customer. This transparency leads to a relationship founded on trust. In summary, new metrics will evolve, but the old metrics remain vital and access to data is key in all areas.
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