Playbook
Let AI streamline your NPS analysis for actionable customer insights.
Sources
Zendesk
Intercom
Gong
Grain
Chorus
Getting started
Understanding your customers' loyalty and satisfaction is crucial for product teams. The more insights you gain from your NPS data, the better you can tailor your products and services to meet user needs and expectations.
However, analyzing NPS data and extracting actionable insights can be a complex and time-consuming process.
In this playbook, we'll show you how to efficiently analyze your NPS data using Merlin.
Step 1: What you'll need
You'll need access to Lancey's Merlin agent.
Connect to your product analytics, customer support, and CRM platform within Lancey's integration tab.
Get access to Lancey
Step 2: Setting up filters
Once Merlin is set up, it's able to make sense of your product data automatically. We'll leverage Merlin's ability to query, segment, and action for the next two steps.
To conduct a meaningful NPS analysis, we need to identify specific segments of users based on their NPS responses. This will help us understand different user groups and their sentiments towards our product.
For example, you might be interested in finding all users who are promoters (score 9-10) and have recently upgraded their subscription, or detractors (score 0-6) who have submitted multiple support tickets.
Prompt
Find me all users who are promoters and have upgraded their subscription in the last 30 days.
Merlin will do the tedious work of going through your data set, finding the users that match this condition, and give you a preview.
Step 3: Generating and Distributing NPS Reports
Once Merlin has analyzed the NPS data, the next step is to distribute these insights to your team and relevant stakeholders.
Merlin can generate a detailed NPS report and send it to your team via email or shared documents to be sent regularly. This ensures everyone is informed and can plan accordingly for improvements based on customer feedback.
Prompt
Merlin, generate a monthly NPS report and send it to the customer experience team.
Example Output: Monthly NPS Analysis Report
Date: [Date]
Overview:
Current NPS Score: [Score]
Change from Last Month: [Percentage Increase/Decrease]
Segment Analysis:
Promoters (Score 9-10): Number and percentage of total respondents
Passives (Score 7-8): Number and percentage of total respondents
Detractors (Score 0-6): Number and percentage of total respondents
Key Insights:
Top Positive Feedback Themes: Most mentioned positive aspects by Promoters.
Top Negative Feedback Themes: Most mentioned negative aspects by Detractors.
Trend Analysis:
NPS Over Time: Graph or data points showing NPS trends over the last months.
Feedback Theme Trends: Changes in key feedback themes over time.
Predictive Insights:
Future NPS Predictions: Estimated NPS score for the next month based on trends.
Impact Areas: Potential areas of improvement or concern highlighted by predictive analysis.
Recommendations:
Strategic Actions for Improvement: Suggested actions based on Detractors’ feedback and predictive insights.
Engagement Strategies: Recommendations for increasing Promoter engagement and converting Passives to Promoters.
Thanks,
[Product Manager]
Wrapping up
And we're all done here! Get back to building great products. We also have other playbooks you can explore.