Fred Reichheld is an advocate for the relationship between customer satisfaction and long-term growth. When the author and thought leader published The Ultimate Question, a book that introduced the world to the Net Promoter Score – a process that measured loyalty levels by simply asking consumers how likely they were to recommend the service they received on a scale of zero to ten – his thoughts about how to best measure the strength of customer relationships became a blueprint for businesses around the world.
But the world has seen a meteoric shift since Reichheld conceived the NPS in 2003. Although this widely-embraced method of assessment can help businesses tailor management and strategy around clear objectives, when it comes to collecting feedback that can guide smarter decisions it falls woefully short.
The fact that the NPS is a legacy of an era in which businesses lacked access to real-time data and tools to enable conversational analysis were expensive and inaccessible is a major part of the problem. Relying on a “claimed” data set that doesn’t address real-time conversation that unfold across touchpoints such as social media or understand the difference between what a customer tells you in a survey and the ways in which they really behave can lead to blind spots that threaten agility and risk competitive edge. Here are two compelling reasons to swap the NPS for a process that addresses your customer’s authentic voice.
Real-time data can outsmart a vague survey response
The NPS often relies on outbound surveys that target a small slice of your customer base – a fact that makes it a good indicator of your consumer sentiment but a poor diagnostic tool. Too often, customers will provide you with flimsy responses that draw on the kind of unstructured information that’s difficult to translate into actionable insight. But these days, marketers can listen to real-time customer conversations and parse the opinions of actual promoters and detractors, a method that leads to granular knowledge of what your consumer really wants. We’re currently seeing a suite of tools designed to capture and analyse natural language, a term that spans everything from voice data to social media posts, before using this digitised information to take customer intelligence to new heights.
Adopting test-and-learn methodology is a passport to customer-centricity
The issue with static customer assessment methods such as the NPS is the fact that responses rely heavily on time. Data collected periodically is subject to a serious time lag – when you receive the report four to six weeks after you’ve asked the questions, they’re often too out-of-date to generate relevant insights. Online giants such as Amazon demonstrate the ways in which a test-and-learn methodology can power a customer experience based on a moment of truth. By running hundreds of test concurrently and using these findings to build a customer experience based on an intimate knowledge of browsing history, preferences and buying habits, it leaves rivals in the dust.
However, operating tight feedback loops based on real-time customer behaviour and implementing changes across a series of iterations can help businesses take a page out of Amazon’s book. If you’re able to build a tighter relationship between the product and the market, you stand a higher chance of using customer feedback to better your offering.
Investing in tools to draw meaningful conclusions from real-time analysis and honing in on the conversations unfolding between your actual promoters and detractors – rather than an approximation of your ideal customer – can lead to granular insights that can help your business grow in leaps and bounds. All it takes is the kind of mindset that’s committed to modern-day customer relationships rather than a practice that, however helpful, belongs firmly in the past.
This article is by Jason Juma-Ross, former Digital Intelligence Lead for PwC.