> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unibee.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Customer Metrics

> Customer LTV, quick cards, trend, breakdown, formulas, and notes in UniBee Analytics.

# Customer Metrics

# Customer LTV

The **Customer LTV** page helps you estimate how much recurring revenue an average active customer is expected to generate over time.

It combines customer count, average recurring revenue, and churn data into a simple monthly view, so teams can quickly understand whether customer value is improving or declining.

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## What you can see

### Quick Cards

At the top of the page, quick cards show Customer LTV values for key comparison points, such as:

* Current month
* 1 month ago
* 3 months ago
* 6 months ago
* 12 months ago

This helps you quickly compare recent and historical customer value.

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### Customer LTV Trend

The trend chart shows how **Recurring Revenue LTV** changes over time.

Use it to:

* monitor long-term changes in customer value
* identify periods of improvement or decline
* compare recent performance with past months

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### Recurring Revenue LTV Breakdown

The breakdown table shows the monthly components used in LTV calculation, including:

* **Active Customers**\
  Total number of active recurring customers included in MRR calculation.

* **ARPC**\
  Average recurring revenue per active customer.

* **Customer Churn Rate**\
  Percentage of customers who canceled or did not renew recurring subscriptions during the period.

* **Lifetime Value (LTV)**\
  Estimated recurring revenue an average customer is expected to generate before churning.

* **MoM LTV Change**\
  Month-over-month percentage change in LTV.

This table helps you understand not only the final LTV result, but also the main drivers behind it.

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## How Customer LTV is calculated

### Active Customers

Number of active recurring customers included in MRR.

### ARPC

**ARPC = MRR ÷ Active Customers**

ARPC shows the average monthly recurring revenue per active customer.

### Customer Churn Rate

**Customer Churn Rate = Lost Customers ÷ Starting Customers**

It reflects how many recurring customers were lost during the selected period.

### Lifetime Value (LTV)

**LTV = ARPC ÷ Customer Churn Rate**

This estimates how much recurring revenue an average customer may generate before churning.

### MoM LTV Change

**MoM LTV Change = (Current Month LTV - Prior Month LTV) ÷ Prior Month LTV × 100%**

This shows whether customer value is increasing or decreasing compared with the previous month.

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## Notes

* This page focuses on **recurring revenue LTV**
* LTV is shown in the reporting currency used in Analytics
* Trend and table results follow the same MRR and churn logic configured in your Analytics setup

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## Why it matters

Customer LTV helps teams evaluate the long-term value of recurring customers.

It is especially useful for:

* tracking customer quality over time
* comparing revenue per customer against churn
* identifying whether customer value is becoming stronger or weaker