SmartHelping / Customer Forecasting / Excel
Spend & Retention
Forecast customer counts and revenue using spending and retention patterns that change with customer age. Enter monthly acquisitions and define your curves across a 60-month framework for a startup or an existing business.
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See the model in action
Walk through the customer spend and retention forecast.
Three core inputs
Build the forecast around how customers behave.
Use the 60-month input framework to connect customer acquisition with the retention and spending patterns you expect.
Customers acquired per month
Enter the number of new customers acquired in each forecast month. These acquisition groups enter the model at different points in the calendar.
Retention by customer age
Define retention percentages for month 1, month 2, month 3, and onward in the customer relationship. Shape the pattern to reflect how retention changes as customers stay longer.
Average spend by customer age
Enter average customer spending for each month of the customer relationship. Spending can increase, decrease, or follow another pattern; it does not have to extend through all 60 months.
Calendar month and customer age
Follow the customer relationship as it develops.
Customer age measures the time since acquisition. A newly acquired customer starts at the beginning of the retention and spend curves, even when that customer joins later in the forecast.
Shape retention
Model a pattern in which more customers leave during the first few months, followed by slower losses among longer-standing customers. Set the age-specific retention values to reflect the behavior you expect.
Shape spending
Reflect customers who spend a certain amount when they join, spend more later, and then spend less as the relationship matures. The spend inputs let you define that sequence directly.
Customer counts and revenue
See how the assumptions combine in the forecast.
Useful applications include SaaS, eCommerce, and boutique retail, particularly where customer retention and spending change during the customer relationship.
Expected customer counts
Connect new customer acquisitions with the retention curve to forecast the customer base over time.
Expected revenue
Combine the customer forecast with spending assumptions that change by customer age to project revenue.
Also included in these bundles
Explore more recurring-revenue and business-model tools.
Related concepts
Read more about customer analysis.
Questions before you start
A few useful details.
What does customer age mean?
It is the number of months since a customer was acquired. Retention and spending assumptions follow that customer age, while new customer acquisitions are entered by forecast month.
Can retention and spending change over time?
Yes. Define the values by customer age so the forecast can reflect changing retention and spending patterns.
Do I have to enter spending for all 60 months?
No. The model provides up to 60 months of average customer spend inputs, but the spend pattern does not have to extend through the full period.
Can I use this for a startup or an existing business?
Yes. Use acquisition, retention, and spending assumptions that reflect the business you are forecasting.
Model the customer relationship
Turn retention and spending patterns into a revenue forecast.
Customer Spend & Retention Excel Model — $45, one-time purchase.
