The evolution of NPS 3.0

A lot has changed since Fred Reichheld invented and first wrote about this number in Harvard Business Review almost 20 years ago. He introduced “NPS - The One Number You Need to Grow,” and his conclusion was simple. The best predictor of top-line growth can usually be captured in a single survey question: Would you recommend this company to a friend? 

It created a new way of measuring how well an organization generates relationships worthy of loyalty. He called that metric the Net Promoter Score (NPS).

Over the past 20 years, the rise of customer experience (CX) as a crucial differentiator for modern businesses has paved the way to a new selection of success metrics abound customer experience management (CEM). Today’s contact centre leaders are less concerned about the call volume and more focused on first call resolution. Nowadays, NPS is determined by anything that influences your customer’s perception of your brand. The speed of your issue resolution, customer effort score, and the number of customer support channels you offer can all have an impact on the NPS metrics. There is a great deal of focus on the importance of the customer journey rather than just the survey data. Even today, NPS continues to be a core KPI within many organizations and it has evolved from a data and research-based approach into a more integrated measurement approach.

Today, a company’s product is no longer a differentiator. Instead, CX has become the trump card that enables brands to have a competitive edge. This trend has accelerated the growth of a new NPS (NPS 3.0) and how we look at this score from a multi-dimensional framework within the marketing ecosystem. 

NPS 3.0 unpacks the intentional strategic shifts that were introduced towards a data-driven methodology that focuses on understanding the customer experience and its relation to loyalty and growth. With NPS 3.0, a more holistic approach is used for handling customer satisfaction. Subsequently, the elements used as metrics in the NPS methodology have changed too. 

For example:

1. Measurement of customer service experience has evolved to include data at the interaction level by capturing more actionable metrics such as customer satisfaction (CSAT), customer effort score (CES) value enhancement score (VES), and customer lifetime value (CLV) to name a few. Rather than tracking a calculated score, metrics are more about adopting a customer-centric mindset across all levels of the organization.
    
2. There has been increased intentional focus on research that links responses with actual customer behaviour, purchasing patterns, referrals and company growth.
   
   
3. Leveraging technology to enhance customer journey has resulted in new approaches that enable AI-based learnings that directly impact brand reputation and NPS scores. Some of the ways that AI can improve NPS include:
   • Measuring EX and AX: Employee experience (EX) and agent experience (AX) impact NPS. AI solutions can empower staff members by streamlining access to valuable information and offering suggestions on how to solve consumer problems.
   • Measuring impact at interaction level for customer lifecycle management: Using AI as an impactful way to mine data and turn that into actionable insights helps organizations monitor and assess the holistic customer journey.
   • Quicker resolution: In the contact centre environment, AI can ensure that customers take the fastest route to problem resolution. After detecting sentiment analysis, an intelligent routing system can send a customer to the agent queue best equipped to ensure effective resolution.
   • Effective self-service environment: Solutions like chatbots and smart virtual agents can support a self-service environment for customers, thereby letting brands be present 24/7 for simple issue resolution. Companies can create AI tools that instantly answer customer questions at any time of day, and allow those consumers to make transactions or manage simple account changes.
4. Taking NPS a step further, brands are also measuring Net Advocacy Score (NAS). Coined by Alain Samson of the London School of Economics and Political Science, the NAS is calculated as the NPS, which measures intent, minus Negative Word of Mouth, or the percentage of customers making very negative comments in the past 12 months.
5. Voice of the Customer (VoC), a metric that captures real-time data, is quickly becoming a key focus. Shifting from lagging data capture to real-time capture also influences the NPS score in the following ways:
   • Direct feedback: Feedback that customers provide directly to the organization, either when asked to do so or when motivated by their experience. This feedback typically takes the form of a survey, with responses gathered through multiple channels, such as email, websites, paper, SMS, voice, video, in-app, kiosks and computer-assisted telephone interviewing (CATI).
   • Indirect feedback: Feedback is derived from instances when the customer talks about an organization without specifically intending to provide feedback to the organization. This feedback includes insights gathered from review sites, social media, and customer care interactions via phone, email and chat.
   • Inferred feedback: Operational and behavioural data associated with customer experiences or customer journeys, such as a website’s clickstream data, mobile app location data or contact centre operational data.

Data informed methodology that focuses on understanding CX and its relation to loyalty and growth helps brands prioritize investment and distribute actionable data across the organization to drive engagement. Behind every customer satisfaction metric, there is a series of factors that influence it. NPS 3.0 is not a quantifiable metric to measure against, but rather a qualitative metric that allows leaders to reflect, analyze and react.