Improve customer retention rate

Quickly diagnose where, when, and why you’re retaining customers.

Analytics Challenge

Business Challenge

KPI Impact

Analytics Challenge

Like churn, you need to continuously analyze customer retention rate if you want to keep up with how quickly customer behavior changes.

However, the real challenge in analyzing customer retention is in the changing nature of customer behavior. To uncover the key drivers behind changes in retention, you need to be able to quickly diagnose the trends across operational, behavioral, acquisition, price, product usage, and more.

With the sheer number of factors impacting retention, you’ll need to test to determine not only that they stayed or left the platform, but why, making it difficult to diagnose the reason for changes quickly.

Retention Rate

Retention rate measures the percentage of customers retained by the end of a given time period.

Retention = # Continued active users / Total # users at start of time period

Analytics Challenge

Like churn, you need to continuously analyze customer retention rate if you want to keep up with how quickly customer behavior changes.

However, the real challenge in analyzing customer retention is in the changing nature of customer behavior. To uncover the key drivers behind changes in retention, you need to be able to quickly diagnose the trends across operational, behavioral, acquisition, price, product usage, and more.

With the sheer number of factors impacting retention, you’ll need to test to determine not only that they stayed or left the platform, but why, making it difficult to diagnose the reason for changes quickly.

Business Challenge

The value of efficiently retaining customers can’t be overstated. With an estimated 80% of future revenue coming from at least 20% of existing customers, monitoring and optimizing this metric is the key to success.

While you should also monitor your customers’ churn rate, retention analysis allows you to diagnose where, why, and how customers leave your platform.

Customer retention rate is a feedback metric. It lets your business understand how changes impact your customers based on their response (staying or leaving your platform). By quickly identifying the factors that retain customers, you can intervene before they stop using your product. Once you’ve diagnosed these holes in your product, sales, or marketing strategy, you’ll be able to step in and improve your retention rates faster.

KPI Impact

Uncovering the factors behind your customer retention rate and intervening early enough to make even small changes will have compounding effects on the business.

Retaining customers is cheaper than finding new ones — reducing customer acquisition costs (CAC) for the businesses, increasing customer lifetime value (CLV), saving the sales team time and energy in prospecting new customers, and much more.

In fact, research shows that just a 5% increase in customer retention rate leads to 25% – 95% increase in profits, depending on the company and industry. Imagine the impact a 5% increase in retention could have on your business.

Best practices for analyzing retention rate

As you’d do with customer churn, customer retention rate should be tracked at the account or customer level. Each row should represent a unique customer, with one record per time period.

To diagnose the driving factors impacting your retention rate, make your dataset as wide as possible. Start with the recommended fields below and add as many descriptive variables as you can to augment your analysis.

Schema Blueprint:

  • One row per account
  • Metric column =
    Reactivated (T/F)

Recommended

Account ID

Status = (Active/Churn)

Account Creation Date

Product SKU(s)

Product Usage

Product Category

Product Sub-Category

Calendar Month

Customer Acquisition Date

Customer Tenure (Days)

New Customer (T/F)

Last Activity

Days Since Last Log In

Optional

Engagement Score

Customer City, State, Zip

Customer Tier

Email Engagement

# of Users on Account

Contract Type

Monthly Charges

Total Charges

Email Subscribed (Y/N)

Account Deleted (Y/N)

Account Deleted Reason

CSAT

Response Time

# Customer Success Tickets

Schema Blueprint:
  • One row per account
  • Metric column =
    Reactivated (T/F)
Recommended

Account ID

Status = (Active/Churn)

Account Creation Date

Product SKU(s)

Product Usage

Product Category

Product Sub-Category

Calendar Month

Customer Acquisition Date

Customer Tenure (Days)

New Customer (T/F)

Last Activity

Days Since Last Log In

Optional

Engagement Score

Customer City, State, Zip

Customer Tier

Email Engagement

# of Users on Account

Contract Type

Monthly Charges

Total Charges

Email Subscribed (Y/N)

Account Deleted (Y/N)

Account Deleted Reason

CSAT

Response Time

# Customer Success Tickets

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