How to Improve Your Net Promoter Score (NPS) Using AI

Navigating the complex landscape of customer feedback is a critical task for modern businesses. As they seek to measure and enhance their performance, Key Performance Indicators (KPIs) like Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), Star Ratings, and App Store Ratings emerge as essential metrics. These indicators shed light on customer and product performance, guiding companies toward informed decisions. So how can a business assess the impact of qualitative customer feedback on these quantitative KPIs? Keep reading to find out!

Deciphering Key Performance Indicators

• Net Promoter Score (NPS): NPS serves as a barometer for customer loyalty and satisfaction. It's derived from asking customers about their likelihood to recommend a product or service. Scores range from -100 to 100, with higher scores signifying stronger customer loyalty.
• Customer Satisfaction Score (CSAT): CSAT measures customer contentment with a specific product, service, or interaction. It's typically assessed through a short survey, asking customers to rate their satisfaction on a scale.
• ‍Star Rating: Reflects overall customer satisfaction with a product or service on e-commerce platforms like Amazon or review sites like G2.‍
• App Store Rating: This metric is pivotal for mobile apps, representing the average rating by users on platforms like the Apple App Store or Google Play. It acts as an indicator of user satisfaction and overall app quality.

Viable's platform is adept at evaluating the influence of customer feedback across all of these metrics, pinpointing trends and issues impacting these scores, and offering actionable insights for improvement. For the purposes of today's blog post, we'll dive deeper specifically into NPS.

Understanding Net Promoter Scores (NPS) and Its Significance

For over two decades, Net Promoter Score (NPS) has served as a key metric in gauging customer loyalty and its contribution to company growth. Developed by Fred Reichheld at Bain & Company and Satmetrix in 2003, NPS offers a straightforward approach to measuring a complex phenomenon. It has since become a widely accepted tool across industries for assessing customer loyalty.

NPS measures the likelihood of customers recommending a company's products or services to others, offering insights into customer loyalty and advocacy. The score ranges from -100 to 100 and serves as a robust predictor of business growth, reflecting the overall perception of a brand.

NPS is calculated by asking customers one simple question: “On a scale of 0-10, how likely are you to recommend our company/product/service to a friend or colleague?” Based on their responses, customers are categorized as Promoters (9-10), Passives (7-8), or Detractors (0-6). The final score is derived by subtracting the percentage of Detractors from the percentage of Promoters.

Measuring NPS and Its Impact

NPS is typically assessed after key customer touchpoints, such as post-purchase, following a customer service interaction, or after using a product. To gain a comprehensive view of customer loyalty, NPS is measured regularly, tracking trends over time. This allows businesses to evaluate the effects of changes in products, services, or customer engagement strategies.

NPS is valuable or professionals in marketing, sales, and customer experience. It provides insights for Customer Success Managers, Marketing Managers, Sales Managers, and Chief Experience Officers, helping them measure loyalty and make informed decisions. NPS feedback influences individual contributors, teams, and the company as a whole, guiding strategy and highlighting areas for improvement.

NPS benchmarks vary by industry, with an NPS of 0 considered average, above 20 good, above 50 excellent, and above 80 world-class. For example, Tesla's NPS of 96 in 2020 demonstrated exceptional customer loyalty, with almost 71% of Tesla owners repurchasing a Tesla vehicle, according to Experian.

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The Manual Analysis Challenge

The traditional route of manually analyzing customer feedback to gauge its effect on KPIs like NPS is a formidable task, particularly with vast data volumes. The process is multifaceted and involves several key steps:

1. Feedback Collection: Aggregating customer feedback from diverse sources such as surveys, social media, support tickets, and reviews. This step requires compiling data from multiple platforms to ensure a comprehensive view.
2. Cleaning Data: This involves removing noise such as irrelevant data, spam, and duplicates. It's crucial to filter out any information that does not contribute to the analysis to ensure accuracy in the subsequent steps.
3. Tagging: Categorizing feedback based on intent (e.g., compliment, complaint) and content (e.g., app crashing, checkout experience). This step helps in organizing the data for more detailed analysis, enabling the identification of specific areas for improvement.
4. Clustering: Grouping similar themes and tallying each cluster. This involves identifying patterns and commonalities in the feedback to understand the prevalent issues or positive aspects that customers are mentioning.
5. Metadata Tracking: Linking qualitative feedback with metadata such as quantitative scores (like NPS) and demographics (like region, customer segment, and more). This step is crucial for contextualizing the feedback and understanding how different factors influence customer sentiment.
6. Impact Calculation: Calculating the delta in the NPS ratings with and without each feedback cluster to determine the impact of any given theme on NPS. This involves comparing the overall NPS with the NPS for each cluster to quantify the effect of specific issues or positive aspects on customer loyalty.

For instance, if a cluster of complaints about app crashes has an average NPS of 30, while the overall NPS stands at 50, addressing this issue could potentially elevate the NPS by 20 points. This example highlights the importance of identifying and addressing key themes in customer feedback to improve NPS and, consequently, customer loyalty.

While the resulting insights are extremely valuable, this process is extremely time-consuming and laborious, making it nearly impossible to execute at scale without significant resources—which is exactly why very few companies even attempt the process.

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Improving NPS with Generative AI Analysis

Viable revolutionizes this labor-intensive process, offering a seamless, automated experience. With Viable, businesses can:

• Automate Feedback Analysis: Viable's AI-driven platform autonomously tags, clusters, and analyzes customer feedback, conserving time and effort.‍
• Prioritize Feedback with KPI Impact Analyzer: Understand the quantifiable impact on crucial performance metrics such as NPS, CSAT, and more. Make data-driven decisions to focus on improvements that will have the most significant effect on business metrics.‍
• Deep Dive with Follow-Up Questions: Go beyond surface-level analysis by asking our AI follow-up questions directly within the platform. Get to the root of customer issues and understand the "why" behind the feedback.‍
• Filter & Customize the Analysis: Tailor your analysis to specific areas or business objectives. Prioritize features, identify churn risks, and focus on what matters most for your unique goals, whether you're a Product Manager focused on feature roadmaps or a CX leader trying to reduce support interaction volumes.‍
• Craft Strategic Documents: Utilize the insights to create strategic documents like Product Requirements Documents (PRDs) for informed decision-making.‍
• Integrate Seamlessly with Existing Tools: Viable integrates with your existing customer feedback tools, ensuring a smooth workflow. Leverage AI-powered insights within your current ecosystem, enhancing efficiency and productivity.

By harnessing Viable's capabilities, businesses can efficiently evaluate the impact of customer feedback on their KPIs, enabling data-driven decisions that boost customer satisfaction and loyalty. Whether the aim is to enhance NPS, CSAT, or App Store Ratings, Viable equips companies with the necessary tools and insights to achieve their objectives.

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Enhancing NPS with Other Generative AI Tools

Many AI tools exist today to help you streamline customer interactions and provide more personalized experiences. Here's how different generative AI tools can impact NPS:

1. Automated Follow-Ups: Implementing automated follow-up systems can ensure timely engagement with customers after key interactions. This automation helps in quickly assessing customer sentiment, collecting valuable feedback, and addressing any issues or concerns promptly. By maintaining an open line of communication and showing customers that their feedback is valued, businesses can improve NPS and foster customer loyalty.
2. Personalized Recommendations: AI-driven systems can analyze customer data to provide personalized product or service recommendations. By understanding individual preferences and behaviors, these recommendations can significantly enhance customer satisfaction, making customers more likely to recommend the company to others. This tailored approach not only boosts NPS but also increases the potential for upselling and cross-selling.
3. Predictive Analysis: Utilizing predictive analytics can help businesses identify potential detractors before they impact NPS negatively. By analyzing patterns and trends in customer behavior and feedback, companies can proactively address concerns and prevent issues from escalating. This proactive approach strengthens customer relationships and contributes to a higher NPS.
4. Autonomous Agents: Implementing autonomous agents, such as chatbots or virtual assistants, can provide immediate support to customers, resolving their queries quickly and efficiently. This instant support enhances the overall customer experience, leading to improved NPS scores as customers feel their needs are being met promptly and effectively.
5. Customer Segmentation: AI tools can segment customers based on their likelihood to recommend the company's products or services. By identifying potential Promoters and Detractors, businesses can tailor their strategies to enhance the experiences of those likely to advocate for the brand while addressing the concerns of those who might not. Focusing on these segments allows companies to allocate resources more effectively and improve NPS.

Incorporating generative AI tools into customer engagement strategies can significantly enhance NPS by providing more personalized, efficient, and proactive customer experiences. By leveraging these tools, businesses can foster customer loyalty and drive growth through positive recommendations.

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To learn more about how Viable's generative AI solutions can elevate your NPS and customer loyalty, start your free 30-day trial today.