Purchasing a new radio station (or upgrading an existing station) can represent a significant investment of time and money for your radio ministry. Accurately forecasting future revenue for a potential new station acquisition is critical in deciding whether to purchase a station and what price to pay.
This article will present the five methods you can use to forecast future donor revenue. These forecasting systems are listed below from A through E based on their revenue forecasting accuracy. Like most things in life, higher quality systems are also more expensive. The more accurate systems cost more to build and maintain but produce more accurate revenue forecasts.
If you are purchasing an inexpensive translator or a small station, a less expensive and less accurate system may be adequate for your needs. If you are analyzing the purchase of a large, expensive station, your ministry could benefit from investing in one of the more accurate forecasting systems. Higher-level systems will give you more confidence in your revenue forecast but are more expensive to build and maintain.
The five types of revenue forecasting systems for new stations, arranged from highest accuracy to lowest accuracy, are:
- Donor-based (highest accuracy)
- Population-based, Multiple-contour
- Population-based, Single-contour (lowest accuracy)
A. Donor-based Revenue Forecasting System
The A-level Donor-based Revenue Forecasting System is the most accurate and most powerful. A Donor-based system forecasts new station revenue by identifying potential donors in your new station’s coverage area.
For each of your prospective donors, their name, address, estimated giving capacity, estimated net worth, and additional characteristics are forecast. This model also compensates for signal strength and annual growth. After accounting for these and other factors, your revenue model predicts the yearly donor revenue for your new station.
Another advantage of a Donor-based revenue forecasting system is that it identifies each donor in the coverage area by name, address, and giving characteristics. It enables your donor development team to send postcards and letters, make phone calls, and even invite high-value potential donors to meetings and special donor events. Enhancing and growing your donor development strategies and tactics is a valuable benefit of a Donor-based system.
Although a donor-based system is the most accurate, it also the most expensive to build and maintain. It is the best system to use when the new station represents a significant investment for your ministry, and you require the most accurate revenue forecast. The added donor-development benefits of a Donor-based system can help to fund your new station.
B. Psychographic-based Revenue Forecasting
The B-level Psychographic-based Revenue Forecasting System is similar to the A-level Donor-based system, except that it applies your donorship model at the neighborhood level rather than to individual donors. The B-level model is developed based on an analysis of the Psychographic clusters of your existing donors.
The first step in building your psychographic donor model is to analyze data and information from your existing donors and station(s). The second step is to apply your psychographic model to every neighborhood in your new station’s coverage area. Third, you then compensate for signal strength, donor penetration, and your market growth curve.
The sum of the forecast revenue from each neighborhood your new station will cover then produces your multi-year revenue forecast.
C. Demographic-based Revenue Forecasting System
The C-Level Demographic-based Revenue Forecasting System is developed based on the demographic characteristics of your existing donors. First, the demographics of your past donors are analyzed. Then your demographic donor model is applied to your new station’s coverage area to forecast annual revenue.
After compensating for your donor penetration by signal strength and your yearly growth curve, the demographic model produces your annual revenue forecast for future years.
D. Population-based, Multi-contour Revenue Forecasting System
The D-Level Population-based Multi-contour Revenue Forecasting System forecasts future revenue based on the population of each differential signal strength contour for your new station. It does not compensate for either psychographics or demographics. This forecasting model is based on your past donor penetration by signal strength in multiple concentric contours and your past revenue growth curve.
The sum of the revenue forecast for each contour for each year your station is on-the-air then produces your multi-year revenue forecast.
E. Population-based, Single-contour Revenue Forecasting System
An E-level Population-based Single-contour Revenue Forecasting System forecasts future revenue based on the population in just one cumulative signal strength contour for your new station. The revenue forecast for that contour for each year then produces your multi-year revenue forecast.
A Population-based single contour revenue forecasting system is the least accurate of the five levels of new station revenue forecasting systems. It is also the least expensive and the quickest to build.
Your ministry might use an E-level Population-based single-contour model to analyze small, inexpensive stations and translators where a lower level of revenue forecasting accuracy is acceptable to you.
Your ministry’s ability to accurately forecast future revenue for new stations is critical when considering purchasing a new station (or upgrading an existing station). Understanding the five levels of Revenue Forecasting Systems can help you decide which model will best meet your objectives.
For smaller station purchases, the inaccuracy of the E-level Population-based systems may be acceptable to you. For more expensive acquisitions, higher-level forecasting systems may better meet your need for increased accuracy.
Matching your forecasting model to the size of the investment you are making will help assure the correct investment decision when purchasing a new station. Similar logic applies when upgrading your existing stations. A large and expensive upgrade may require a higher level of revenue forecasting accuracy than a less expensive upgrade.
Choosing the right revenue forecasting model to meet your station purchasing objectives is integral to your radio ministry’s success.
Frank Kavenik helps founders and leaders of Christian radio networks to increase coverage, audience, and revenue. He is the developer of the Radiometrics Data Science System. Frank holds degrees in management, law, and engineering. His profile and contact information are available on LinkedIn at: