Data-Driven Decisions: Merchant Retention Metrics
Understanding Retention Metrics is pivotal to the effective management of your merchant base. By getting to the heart of these key indicators, you’ll be better equipped to make informed decisions that boost retention rates, extend merchant lifetime value, and ultimately, increase profitability. In this article, we will dive into the “Retention Metrics” of the Merchant Retention Dashboard, as previously outlined in our comprehensive article “Product Analytics: Merchant Retention Dashboard.”
Retention Metrics: Sample Data Set
Decisions Based on Data
1. Merchant Retention Rate
- Decision Criteria: If the retention rate is declining or below industry standards. In the above sample data set:
Merchant Retention Rate declined from 92% to 85% over three months.
- Possible Decisions:
- Investigate why merchants are leaving. This might involve surveys or interviews to gain qualitative insights.
- Enhance the value proposition, offer loyalty programs, or optimize onboarding processes. - Outcome: Improved retention rate and potentially increased revenue.
- If Ignored: Continued loss of merchants, reduced lifetime value, and higher costs of acquisition.
- Negative Trend:
- Consistent Decline: A steady decrease over multiple periods.
- Seasonal Dips: Lower retention rates during particular seasons, which may be repeated annually.
- Abrupt Drops: Sudden, significant declines that may be triggered by a particular event or change.
2. Churn Rate:
- Decision Criteria: An increase in churn rate or a rate that is higher than the industry average. In the above sample data set:
Churn Rate increased from 8% to 15%
- Possible Decisions: Investigate and address the reasons behind the churn.
- Outcome: Lower churn rate, higher merchant satisfaction.
- If Ignored: Ongoing loss of revenue and market share.
- Negative Trend:
- Increasing Churn: A higher percentage of customers leaving your service over time.
- Spikes in Churn: One-off increases, often coinciding with a specific event like a price change or service outage.
- Segment-Specific Churn: Higher churn rates among a particular customer or merchant segment.
3. Merchant Lifetime Value (MLV):
- Decision Criteria: If MLV is declining or stagnating. In the above sample data set:
MLV Dropped from $900 to $800
- Possible Decisions: Introduce features or services that enhance the value merchants get, encouraging them to stay longer and spend more.
- Outcome: Increased MLV.
- If Ignored: Reduced revenue potential and possibly, the viability of the product.
- Negative Trend:
- Gradual Diminishment: Decline in the value over several measurement periods.
- Fluctuation: Frequent ups and downs in MLV, which makes it hard to predict and plan for the future.
4. Customer Acquisition Cost (CAC):
- Decision Criteria: Rising CAC or CAC greater than the industry average. In the above sample data set:
CAC rose from $100 to $140
- Possible Decisions: Optimize marketing spend or enhance the product to make it more appealing without additional costs.
- Outcome: Lower CAC, improved profitability.
- If Ignored: Lower margins and potentially unsustainable business model.
- Negative Trend:
- Rising Costs: Increasing expense to acquire each new customer or merchant.
- Low ROI: High acquisition costs that do not result in expected revenue or lifetime value.
5. MLV: CAC Ratio
- Decision Criteria: If the ratio is less than 3:1. In the above sample data set:
The ratio went from 9:1 to 5.7:1
- Possible Decisions: Revisit pricing strategies, introduce upselling or bundling to improve MLV, or optimize CAC.
- Outcome: Better unit economics, and improved profitability.
- If Ignored: Business may become unsustainable.
- Negative Trend:
- Decreasing Ratio: Indicates that the lifetime value generated by merchants does not justify the cost of acquiring them.
6. Time to Churn
- Decision Criteria: If the average time to churn is decreasing. In the above sample data set:
Reduced from 15 to 13 months
- Possible Decisions: Investigate and fix any emerging issues that could be contributing to quicker churn.
- Outcome: Increased merchant retention and higher lifetime value.
- If Ignored: Quick erosion of the customer base and potential brand damage.
- Negative Trend:
- Shortening Time: If the average time to churn is getting shorter, customers are leaving the service more quickly than before.
Criteria for Decision-Making
- Significant Deviation: Make decisions when there is a statistically significant deviation from expected metrics.
- Trend Confirmation: Confirm that it is an actual trend over an extended period, not just a one-time dip due to seasonality or other short-term factors.
For example, suppose your monthly churn rate has increased from 2% to 5%, your Merchant Retention Rate has decreased from 90% to 75%, and your MLV: CAC ratio has fallen below 3:1. This would be a clear signal to dive deeper into your customer data, conduct exit interviews, and perhaps reassess your value proposition.
Consequences of Inaction
- Financial Drain: Continually acquiring new customers to replace those who churn is costly.
- Brand Image: High churn and low retention could lead to a negative brand image, making it even harder to acquire new customers.
Conclusion
In conclusion, tracking key metrics like Churn Rate, Merchant Retention Rate, MLV: CAC Ratio, and Time to Churn is crucial for any product manager to make informed, data-driven decisions.
Negative trends in these areas serve as early warning signs that immediate action is needed. The criteria for making these decisions include significant deviations from set benchmarks and the confirmation of persistent negative trends over time.
Failing to act on these troubling signals not only affects short-term revenue but can also have long-term implications on brand reputation and financial sustainability.
We have just explored the initial segment of the Merchant Retention Dashboard. For more in-depth insights, stay tuned for the upcoming articles. The topics are about to get even more compelling, so keep following!
If you are interested in circling back to our foundational discussion on data-driven insights, you can find that article here: “Data-Driven Insights: Payment Platform”. Feel free to dive back in!