AI-Powered NPS Takes the Stage

Nicolas Marcoin at Odigo explains that Net Promotor Score, NPS, is well known but waning in popularity, and how, 20 years on, the growing application of AI-powered NPS is breathing new life into this traditional brand metric.

What organisation wouldn’t be interested in how their customers answer the question “How likely are you to recommend our brand/products/services to a friend or relative?”

With intense competition and high customer churn in many industries, loyal customers and personal recommendations are critically important, so why isn’t NPS?

The Metric Everyone Knows and Loves(?)

Calculating NPS is simple, % promotors – % detractors. Despite this, and the importance of loyalty and a solid customer base, 2023 CCH survey data places NPS 13th in a ranking of important contact centre metrics: less than half said it was very important and almost a quarter said it was not important.

Customer satisfaction score (CSAT) and customer effort scores (CES) are also simple single-question surveys, so why is CSAT 1st and CES 9th in the CCH data, while NPS is down in 13th place?

It’s a Brand Metric

NPS is often considered a ‘brand’ metric more than a customer experience metric. However, It’s Easy to Adapt for Individual Experiences or Services.

Lack of Sensitivity and Specificity

There are cultural differences, an 8 is considered a high score in some countries. As a result, the traditional NPS framework may not accurately reflect opinion. Adjustments Can Be Easy to Perform, Allowing for a More Exact Reflection of Customer Sentiment.

Limited Actionability

Armed with only the numeric score, there is insight but little to follow up on. Pairing NPS With Other Questions, Metrics or Data Sources Allows Deeper Analysis of the Results.

Survey Fatigue

This is a concern for organisations, and in the race to keep up with customer expectations, which are rising fast, more actionable data is prioritised. NPS Can Be Actionable When Using the Right Strategy.

Score Interpretation

As the scale runs from –100 to +100, interpretation is a little more complex and for perspective requires competitor, industry or historical data for comparison. Once Contact Centres Set Up NPS as Part of Their Performance Tracking Interpretation Becomes Simple.

NPS does have its merits and has been a valuable metric for many years. However, the evolving landscape of customer experience, shifting customer expectations and the desire for more actionable insights have led to the prioritisation of other metrics.

NPS won’t climb to the top spot, but there are opportunities to revitalise it and extract more value from this traditional brand metric.

AI-Powered NPS: A Game-Changer in Customer Experience

The popularity of quality and operational metrics like customer satisfaction, service level and FCR point to the dual pressures contact centres face: delighting customers and cost efficiency.

Ideally, contact centres transform themselves into profit centres by strengthening customer relationships and driving more value to customers.

That’s where AI-powered NPS comes in. With a few upgrades, NPS no longer simply sign-posts business success, it can help contribute to it.

In a World Driven by Data and Customer Centricity, Here Are Some Ways AI-powered NPS Transforms a Traditional Metric Into a Dynamic Tool for Understanding and Enhancing the customer experience.

Easy Answers to Open Questions

Today’s customers are more vocal than ever, and AI enables them to easily respond to open-style questions that accompany AI-powered NPS surveys.

By capitalising on vocal note capabilities, contact centres can now gather crucial details, painting a vivid picture of customer sentiment and preferences.

Speech and Text Analytics

AI has revolutionised how contact centres analyse customer interactions, from emails to call recordings and chatbot interactions.

When applied to open-ended NPS responses, AI-powered analytics swiftly sift through the data, identifying keywords and trends.

This accelerates the extraction of actionable insights and provides a more accurate understanding of the driving forces behind customer satisfaction.

Sentiment Analysis

By applying sentiment analysis to customer experiences preceding an AI-powered NPS survey, organisations gain a deeper understanding of the impact of poor-quality interactions.

Listening back to these interactions can unveil training or process pain points, enabling targeted improvements that resonate with customers.

Closing the Feedback Loop

Low scores can be a signal for immediate action. AI-driven systems can automatically trigger follow-up actions, repairing customer relationships, getting to the root of the problem, and curbing negative word-of-mouth.

This proactive approach turns AI-powered NPS into a catalyst for continuous improvement.

Unlocking the Power of AI-Enhanced NPS Data

The value of an increased volume of AI-generated data lies in its applicability, actionability and ability to generate transformative customer experience insights.

Root Cause Analysis

AI-powered NPS feedback is most powerful when viewed in conjunction with other operational data and customer contextual details.

Without data silos, AI can deep dive into an organisation’s data, helping to identify root causes and derive valuable insights to enhance customer experiences.

Customer Demographic Studies

Segmenting AI-powered NPS survey respondents based on factors like age, location, and loyalty status reveals correlations between scores and demographics.

This data fuels tailored marketing, proactive engagement, and service strategies, ensuring a more personalised customer experience.

Added Value Actions

High scores are not just accolades but potential goldmines of satisfaction drivers. AI-powered NPS can identify what delights these customers, allowing organisations to replicate these practices for the benefit of others and the business.

Product or Service Gaps

Consistently lower NPS scores in one customer segment may indicate a gap in product or service coverage.

By addressing these gaps, organisations tackle low scores but also attract new customers with an improved range of offerings.

Opportunities to Amplify Word-of-Mouth

Predictive analytics, using AI-powered NPS data, can anticipate the customers most likely to become promoters.

With this insight, organisations can deploy targeted engagement strategies and amplify positive word-of-mouth.

It’s the fusion of AI with NPS surveys that takes this metric beyond its traditional boundaries. It transforms NPS into an invaluable tool for understanding customer sentiment, identifying improvement opportunities, and driving business success.

As organisations embark on this AI-enhanced journey, they are poised to deliver exceptional customer experiences that leave a lasting impact on both their customers and bottom line.

This blog post has been re-published by kind permission of Odigo – View the Original Article

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Author: Odigo