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Net promotor score, NPS, is well known but waning in popularity. Discover how, 20 years on, the growing application of AI-powered NPS is breathing new life into this traditional brand metric.
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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?
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?
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.
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.
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.
Odigo is a leading Contact Centre as a Service (CCaaS) solution provider. Natively omnichannel, every touchpoint contributes to rich customer histories, fuelling deeper insights. Odigo’s solution also integrates with leading CRM and AI breaking down silos and widening the pool of data available for data-driven CX decision making. In addition to AI-powered NPS, supervisors can create personalised visual dashboards and alerts for the KPIs which matter empowering them to monitor and intervene in real time.
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