In our AI-driven world, words take on new meanings.
AI, our new team member, sees the world in its unique way. Understanding its perspective will contribute to a better human-non-human partnership.
Let’s explore what Net Promoter Score (NPS) means in our new working environment from both sides: the conventional perspective representing human concepts and AI’s take on it, for fostering a collaborative partnership between humans and non-humans.
Net Promoter Score (NPS) The Conventional Definition
by conventional definiion Net Promoter Score (NPS) is that it is a widely used metric and methodology for measuring customer loyalty and gauging overall customer satisfaction with a company, brand, product, or service. NPS as a term was first introduced by Fred Reichheld in a 2003 Harvard Business Review article titled “The One Number You Need to Grow.”
NPS is based on a single question that asks customers to rate, on a scale from 0 to 10, how likely they are to recommend the company’s product or service to others.
The question typically takes the following form:
“On a scale of 0 to 10, how likely are you to recommend [Company/Product/Service] to a friend or colleague?”
Based on their responses, customers are categorized into three groups:
Promoters (Score 9-10): These are highly satisfied customers who are likely to promote and recommend the company. They are enthusiastic and loyal.
Passives (Score 7-8): Passives are generally satisfied but not enthusiastic. They may not actively promote the company but are unlikely to speak negatively about it either.
Detractors (Score 0-6): Detractors are unsatisfied customers who may have had a negative experience with the company. They are unlikely to recommend it and may share negative feedback.
The Net Promoter Score is calculated by subtracting the percentage of Detractors from the percentage of Promoters. The resulting score can range from -100 (if all respondents are Detractors) to +100 (if all respondents are Promoters). A higher NPS is generally considered better and indicates stronger customer loyalty and satisfaction.
NPS is valued for its simplicity and ability to provide a clear, quantitative measure of customer sentiment. Companies often use NPS to:
- Evaluate customer satisfaction and loyalty over time.
- Identify areas for improvement based on customer feedback.
- Compare their NPS to industry benchmarks and competitors.
- Make data-driven decisions to enhance customer experiences and drive growth.
A recap of the current view in short of what is an NPS.
NPS surveys can be conducted periodically, such as quarterly or annually, to track changes in customer sentiment and assess the impact of improvements made by the company. It is a valuable tool for businesses to understand and measure customer loyalty and make strategic decisions to improve their products, services, and overall customer satisfaction.
What is AI’s perspective on Net Promoter Score (NPS)?
From an AI perspective, NPS represents a valuable source of data that can be leveraged to enhance customer experience and inform strategic decision-making.
Key aspects of how AI can is this data :
Data-Driven Insights:
- AI excels at analyzing large datasets, including NPS feedback, to extract meaningful insights. It can identify patterns, trends, and sentiments within the responses, providing a more nuanced understanding of customer sentiments.
Sentiment Analysis:
- AI’s natural language processing capabilities allow it to conduct sentiment analysis on open-ended NPS comments. This goes beyond the numerical score, offering insights into the specific aspects of the customer experience that contribute to positive or negative sentiments.
Predictive Analytics:
- By incorporating historical NPS data, AI can engage in predictive analytics to forecast future customer satisfaction trends. This enables businesses to proactively address potential issues and capitalize on strengths.
Automation for Actionable Insights:
- AI can automate the process of categorizing and prioritizing NPS feedback. This automation ensures that relevant insights are delivered promptly to the teams responsible for customer experience, enabling timely responses and improvements.
Continuous Learning:
- AI systems learn and adapt over time, evolving their understanding of what factors contribute to positive or negative NPS scores. This continuous learning ensures that strategies for improving NPS remain agile and responsive to changing customer expectations.
Integration with Customer Journey:
- AI can integrate NPS data into a broader understanding of the customer journey. By correlating NPS scores with specific touchpoints, AI helps organizations identify critical moments that significantly impact customer satisfaction.
Personalized Customer Interactions:
- Leveraging NPS data, AI can contribute to personalized customer interactions. It can recommend tailored approaches based on individual customer feedback, fostering a more personalized and positive experience.
In summary, from an AI perspective, NPS is not just a numerical score but a rich source of data that, when harnessed effectively, can drive actionable insights, enhance customer satisfaction, and contribute to the overall success of a business.
My Thoughts:
Utilizing Net Promoter Score (NPS) as a method for analyzing customer feedback holds significant value due to its measurability and action-oriented approach to assessing customer satisfaction.
The introduction of AI, our non-human employee, provides a unique opportunity to integrate this methodology into various touchpoints within our customer journey. The straightforward formula inherent in NPS makes it easily adaptable for implementation by AI and automation.
AI, with its capacity to accumulate vast amounts of data, can proactively respond to customer feedback. For instance, in cases where customers indicate dissatisfaction, AI can trigger actions such as sending emails or initiating tasks for a human employee to follow.
This technological opportunity for intervention enhances our communication with customers, allowing for real-time feedback and tailored responses to their needs.
While encountering unhappy customers is inevitable, the distinction lies in how a brand responds and engages with them.
AI facilitates a dynamic and responsive approach, setting brands apart by addressing concerns promptly and uniquely.
A notable advantage of expanding NPS implementation across our customer journey is the generation of fresh data for our non-human employees, contributing to its continuous learning and evolution. By leveraging an easily repeatable framework, we can amass valuable data, further enriching AI’s understanding of our business.
In the realm of our non-human employees, data is paramount—it serves as the catalyst for evolution and growth.
This should align with our overarching AI strategy, emphasizing our commitment to customer engagement and satisfaction, and supporting the growth and evolution of our non-human employees.
