Chasing churn: post-sales metrics and triggers explored

1. Overview

I led a research initiative to uncover pain points in post-sales activities, prioritize metrics, and identify key drivers of customer churn, aiming to improve team performance and retention strategies.

For confidentiality, some specifics—like survey protocols, sample details, metrics and other deliverables—aren’t included in this case.

2. Background

The post-sales squad faced two critical challenges: they lacked performance metrics and struggled to identify the root causes of customer churn. This gap made it difficult to understand and improve their effectiveness, leaving key questions about user pain points unanswered.To address these challenges, this research focused on three core objectives:

Discover real pain points: understanding what truly impacts users in post-sales activities.
Gather actionable metrics: identifying quantitative ways to monitor these pain points.
Uncover churn triggers: pinpointing the main factors leading to customer churn.

3. Problem statement

The challenge

Without clear metrics or a deeper understanding of user pain points, the post-sales team couldn’t focus on what mattered most. This hindered their ability to address churn effectively or improve their performance.

Key questions we wanted to answer

What are the real pain points in post-sales activities?
How can we represent these pain points with meaningful metrics?
What are the primary triggers causing customers to churn?

4. Research

The research methodology combined qualitative and quantitative approaches tailored to the project’s three objectives:

Objective A (identify pain points):
- Conducted a literature review to revisit prior internal research on user pain points.
- Launched a survey using Net Promoter Score (NPS) to assess pain points quantitatively.
- Began analyzing open tickets to identify recurring issues.
Objective B (prioritize metrics):
- Reviewed literature to explore common post-sales metrics.
- Prioritized metrics based on importance and feasibility.
- Started aligning pain points with quantitative metrics to establish clear tracking methods.
Objective C (understand churn triggers):
- Designed a plan to analyze churn data, including ticket history, subjects, and churn rates.
- Initiated surveys to document churn motivations.
- Conducted discussions with support and consulting teams and began planning interviews with churned users.

The overarching hypothesis is that churn isn’t always directly linked to post-sales issues, meaning other factors might also play a significant role.

5. Ideation

Building on the research findings, I developed a structured approach to tackle the challenges:

Pain point analysis: focused on gathering insights through surveys, ticket analysis, and interviews.
Metrics prioritization: defined clear metrics to monitor post-sales activities effectively.
Churn visualization: planned for a dashboard to display churn data and metrics in a way that aids decision-making.

This phased approach allowed for iterative progress while accommodating the complexities of aligning pain points with meaningful metrics.

6. Design process

The research and design process emphasized collaboration and practicality:

Iterative surveys and interviews: engaged users and internal teams to refine hypotheses and gather actionable data.
Aligning metrics with pain points: worked on translating qualitative insights into quantitative metrics for better monitoring.
Dashboard planning: began outlining a visualization tool to consolidate and track results effectively.

7. Results and insights

Key progress and findings so far include:

Pain points: initial insights into user frustrations and recurring issues in post-sales activities.
Metrics prioritization: identified the most critical metrics for monitoring post-sales performance.
Churn triggers: discussions with internal teams and churned users are beginning to shed light on primary churn drivers.

While the work is still in progress, these steps provide a strong foundation for improving post-sales performance and reducing churn.

8. Reflection and learnings

Challenges

Aligning pain points with quantitative metrics remains a complex task that requires further analysis.
The creation of the monitoring dashboard has yet to begin, which limits the visibility of the collected insights.

Key takeaways

Understanding user pain points is essential for building meaningful metrics that drive actionable insights.
A structured, phased approach ensures progress even when faced with complex data alignment tasks.
Collaboration with internal teams and users is key to uncovering nuanced churn triggers.

9. Future opportunities

As this research continues, the next steps include:

Analyzing open tickets: completing the review to identify additional pain points.
Building a dashboard: developing a tool to visualize metrics and churn triggers effectively.
Expanding user interviews: diving deeper into discussions with churned users to refine insights further.

This project is ongoing, and updates will be shared as we uncover more insights and develop tools to improve post-sales performance. Stay tuned for progress!