Case Study AthenaBeam is a direct-to-consumer (D2C) smart-home lighting subscription service that provides automated replacement plans, control apps, and smart bulbs. Over three years, the company has achieved strong retention growth; retention rates rose from 41% in 2023 to 71% in 2025, while churn dropped from 59% to 29%. On the surface, this looks like a major success story. However, leadership voiced concerns after internal surveys and support feedback revealed persistent customer dissatisfaction. To understand the disconnect between retention and satisfaction, a data-driven analysis was conducted across:
Customer purchasing behavior Service performance metrics (response/resolution times, escalations) Customer sentiment (NPS) Churn behavior
The objective is to determine the operational factors that influence loyalty and churn, as well as the reasons why customers stick around yet are still unhappy.
Our company has achieved strong customer retention growth over the past three years. Retention rates improved from 41.36% in 2023 to 60.94% in 2024 and then 71.49% in 2025.
At the same time, churn rate dropped sharply from 58.64% to 28.51% during the same period. At first glance, we might think our customers are very happy. However, Net Promoter Score (NPS) shows that there is a deep dissatisfaction across customer interactions and service experiences. The analysis shows that customers are staying longer but growing more frustrated. The company’s retention rates look great on paper, but slow responses, long wait times, and unresolved issues are damaging satisfaction (NPS = –75). To fix this, we should train support staff to solve issues faster, set clear service targets, and regularly track customer satisfaction alongside retention. By improving communication and service speed, we can turn “loyal but unhappy” customers into “happy and loyal” ones. Doing this will not only protect retention but also increase each customer’s lifetime value to over $500 by 2026.
Customer Lifetime Value (CLV = $423.66)
Over a period of 1.75 years (Average Customer Lifespan in Years), each customer typically brings in $424 in total revenue. If churns continue to decline, their value might increase to $500+ in 2026, given that retention is improving. That is threatened by a low NPS, though, because dissatisfied clients are less inclined to recommend, promote, or renew. Customers return about every 3 months (average days between purchases are 86 days). Even though customers keep coming back and stay active for ~1.75 years, our NPS of -73 signals they’re not happy doing it. They’re buying again (98.5% Repeated Purchase Rate, an exceptionally high), perhaps due to a subscription model, product dependency (they need our service despite all the frustration), habit or pricing and not satisfaction. So, in short, good news is we have achieved excellent purchase consistency as customers don’t just buy once. Bad news is they do not like the service. If a competitor offers smoother experience or better support, this retention could collapse quickly.
NPS Results Across all dimensions, category, subscription plan, income bracket, and acquisition channel, NPS scores averaged between –70% and –75%, indicating that there are more critics than supporters. • By Category: Across all categories (Account, Billing, Pricing, Product Quality, Shipping, Usability) have similar dissatisfaction levels (≈ –72 and –77%), especially Account, indicating systemic or operational failure. • By Plan: All tiers (Basic, Standard, Premium) showed similar low scores (≈ –73%). • By Income: Low-income and upper-middle segments were the most dissatisfied (≈ –75%). • By Channel: Email and Chat performed poorest (–75% and –74%), suggesting slow or impersonal digital service. This pattern indicates that the entire delivery of the customer experience, in particular service quality, is the issue rather than certain customer segments.
Average NPS by Resolution Time
NPS is fairly stable and moderately positive (≈4.5) when tickets are resolved within 1–7 days. When resolution takes longer than a week (>7d), NPS drops sharply to 2.0. Fast resolution (<1 day) doesn’t drastically improve NPS, but delays beyond 7 days severely hurt satisfaction.
Escalation vs. Resolution Outcomes
Only 8% of non-escalated tickets remain unresolved. When a ticket is escalated, unresolved cases more than double (19%) as they take longer, involve more complexity, and are less likely to end successfully. They nearly triple the chance of an unresolved issue and could be a strong operational driver of poor NPS and eventual churn.
Resolution Time vs. Churn
For most resolution buckets, churn rate hovers around 19–20%, which is fairly stable. However, the few customers who waited >7 days to get a solution churned at 25%, indicating possible patience thresholds. While short delays don’t yet trigger high churn, extreme outliers show a measurable jump in customer loss. All these operational analysis reveals that resolution delays beyond 7 days correlate with a sharp drop in satisfaction and a rise in churn. Escalations almost triple the chance of unresolved outcomes (8% to 19%), confirming that internal hand-offs are a major friction point. Faster, first-contact resolutions should be prioritized to sustain NPS and reduce churn.
- Customers are staying longer, but they are unhappier. It can be due to contract structure, limited options, or pricing.
- Service Experience is the main issue. Support channels (Email, Chat) have the worst NPS, pointing to slow response times, repetitive handoffs, or low first-contact resolution.
- Emotional loyalty (NPS) is terribly low, despite operational measures (churn, retention) demonstrating progress. When competitors or alternatives get better, this disparity may cause dramatic increases in churn.
1. Prioritize First-Contact Resolution Customer service representatives may resolve the majority of problems within the initial interaction without having to "escalate" the case to another team. Ideally, a single person should handle each ticket until it is resolved. Because customers likely get frustrated when they must repeatedly explain their problem, which lowers NPS and increases churn. Faster solutions and happier customers are the results of fewer escalations. Escalations should not exceed 10% of all support tickets.
2. Reduce Resolution Times Set clear response and resolution goals for all support tickets: Fix simple issues within 24 hours. Fix more complex problems within 72 hours. If any case lasts longer than 7 days, alert a manager automatically. We see that when tickets stay open for more than a week, customer satisfaction (NPS) drops by more than half. This means that speed matters. Target should be solving 90% of problems within 3 days.
3. Improve Digital Support Experience Chat and email systems should be updated so that customers can get faster replies and can reach the right person immediately. Use chatbots for simple questions, and direct complex issues straight to live agents. Track how long customers wait in each support channel and how that affects NPS.
4. Root Cause Analysis for Escalations Most of our services have high number of problems. We should improve those through staff training and clearer help materials.
If you want to access the process of analysis, you can read it on here.