The last 15 years have shown the increase in popularity for adopting Net Promoter Score (NPS) as a leading and benchmarking way of determining customer loyalty and satisfaction. At a recent event for customer experience (CX) professionals, we took a straw poll of 50 CX leaders regarding the adoption of NPS and then its validity as a reliable measure of customer satisfaction.
Dramatically, there was a 100% response for NPS being adopted in some form by the companies represented and a 0% response for NPS as reliable. While it is perhaps not surprising that the measure of something as intangible as customer advocacy presents challenges, the gulf between adoption and trust of a system upon which so many decisions (and often bonuses) are based is a herd of elephants in the room.
This is supported by other published research. In 2016, Circle Research took several years of NPS data gathered for multiple companies and ran a correlation analysis to establish if an improvement in NPS was indeed linked to improved financial performance. The result was mixed. In some cases, the correlation was strong, but, in an equal number of cases, it was weak. Remarkably, as the example below illustrates, sometimes the correlation was actually negative with a decrease in NPS being linked to an improvement in financial performance. Even way back in 2007, Harvard Business Review published a paper by Keiningham et al stating that the construction of the NPS metric itself does not satisfy the claims that it is the single best predictor of sales growth.
The problems with NPS are many. Firstly, it is a declared statement of an emotive state at a particular point (RNPS) or at points (TNPS) in time. If it is taken after a negative or positive event, it may correlate according to that event, but otherwise be meaningless in terms of predicting advocacy and subsequent purchase behaviour. Different people and cultures will also score things differently. There has been no scientific demonstration of a link between NPS and actual advocacy or, indeed, even loyalty. And there have even been some studies to challenge it.
With all its faults, however, it is still the most widely-used (and indeed embedded) method of measuring customer satisfaction.
Introducing automated predictive analytics and the New Prescriptive Score
Instead of taking metrics in the past or even near-present, businesses need to know what the predictive indicators of customer loyalty and advocacy are and how they relate to future measurable business outcomes in the form of retained, incremental or lost revenue. A new breed of automated predictive analysis is in the ascendency which can make sense of the “white noise” of unstructured ”voice of customer” data not otherwise adequately captured, let alone understood. Examples include complaints, reviews, web behaviour, social media and call centre data not captured by formal/structured research techniques. The software then links this to purchase behaviour and identifies which customer signals are driving this. As a result, far more meaningful and actionable KPIs are generated.
This can result in some surprising insights. For example, one project for a luxury automotive company found that some serious failure issues had surprisingly little impact on loyalty and advocacy, whereas seemingly minor ones did. For example, a faulty fuel cap actuator created a general and disproportionate impression of poor attention to detail and quality, at odds with customers’ brand expectations. This is just one of many examples of luxury brands, commanding high emotional brand engagement and self-identification from their customers, being able to maintain loyalty and brand advocacy for some time, despite poor quality and/or service experiences which, when judged objectively, would be expected to damage the brand in a more immediate timeframe.
How can I capitalise on New Prescriptive Scores?
For executives who truly want to improve customer experience and drive demonstrable results more cost-effectively, there are new technologies and offerings out there to pilot and adopt. One such example is PrediCX from Warwick Analytics which is based on technology spun out of The University of Warwick. Its proprietary algorithms are able to take heterogeneous and unstructured data, such as voice of customer data, without cleansing and then automatically generate and continuously update the KPIs which drive real results.
This provides either an aggregated view (ie, identifying the overall topics, issues and actions) which drive performance, or a customer/customer segment point of view, ie, providing customer service agents, communication engines and websites with an automated personalised view and next best action recommendations. From the customers’ point of view, they are being dealt with in a way which enhances their individual CX in the most personally relevant way. This in turn can reduce process friction and cost to serve, enabling CX to be improved while also reducing customer service costs.
Adopting the latest technology enables CX professionals to progress from the simplistic use of NPS and failing paradigms to the ability to focus on those issues and KPIs which truly generate real lifetime value. David Hicks, founder of CX specialists TribeCX, says: “Customers’ expectations are growing. Never has it been easier to research alternatives and choose the experiences they want to have based on the recommendations and reviews of other customers.”
“This means barriers to switching to another brand are declining. Organisations can now use digital channels to ‘listen’ to customers and then drive changes to customer experience in a highly-relevant and targeted way with the help of automated predictive analytics. To be able to automate up to 80% of the analytical process means organisations can be even more proactive in enhancing customer experience - modifying or designing new products/services, while at the same time reducing both operational and ‘cost to serve’ overhead,” he said.
Nigel Howlett, chairman of Warwick Analytics added: “In its day, NPS represented a breakthrough in creating a strategic focus on the critical importance of customer satisfaction and advocacy as a driver of business performance, coupled with a simple methodology for measuring this. This used structured questionnaires, soliciting response from customers through the lens of the organisation, ie, the issues the organisation sought to pursue/explore and at the time of their choosing.”
He noted: “Today, in a digital world, we live in a dramatically more customer-empowered world, enabling them easily to voice their concerns, ideas and points of view (with friends, organisations or even the world at large) in the way they want to express them and at the time of their choosing. The ability of organisations to make sense of this plethora of unstructured voice of customer data and then understand how this directly impacts business performance, using prescriptive analytics, will undoubtedly be one of the key hallmarks of successful, customer-centric organisations over the coming years.”