GROWING STATION AND NETWORK
REVENUE FIVE WAYS WITH DATA SCIENCE

The chart below shows five years of revenue growth for two major Christian networks:

Network A leadership was fully supported by Data Science

Network B leadership had no Data Science

The leadership team of Network A was fully supported by Data Science and increased revenue 50% in five years.

This article discusses the five ways that Data Science helps station and network leaders grow signal coverage, listening audience, and donor revenue.

DATA SCIENCE

Data Science can create new data and information to support Christian radio leaders as they grow their stations and networks.

There are five distinct growth factors in the Data Science Growth Cycle.

The Data Science Growth Cycle

A listener-supported radio station or network grows through five Primary Growth Factors. In chronological order, they are:

1. Signal Development – Growing signal coverage
2. Market Development – Growing market awareness
3. Program Development – Growing program effectiveness
4. Pledge Development – Growing pledges to provide support
5. Gift Development – Growing gifts actually received

Data Science provides objective, quantitative criteria to support station and network growth. It defines both the five primary Network Growth Factors and the five Key Performance Indicators.

Actively managing the five KPIs increases station and network revenue.

THE FIVE DATA SCIENCE GROWTH FACTORS

The leaders of one major network were fully supported by Data Science, and averaged 15% annual revenue growth. At that network, Step 1, Signal Development made the largest contribution to long-term revenue growth.

1. The primary goal of Signal Development is to convert ‘Capital Dollars Invested” into “Target Listeners Covered.”

KPI-1 is (Target Listeners Covered)/(Capital Dollars Invested)

Signal Development feeds Target Listeners Covered into Market Development.

The map below is a representative example of the Data Science analysis of a Signal Development market opportunity.

EXAMPLE OF A SIGNAL DEVELOPMENT DATA SCIENCE MAP – Courtesy of V-Soft

2. The primary goal of Market Development is to convert “Target Listeners Covered” into “Cume Listeners Sampling.”

KPI-2 is (Cume Listeners Sampling)/(Target Listeners Covered)

Market Development feeds Cume Listeners Sampling into Program Development.

3. The primary goal of Program Development is to convert “Cume Listeners Sampling” into “P1 Listener Fans.”

KPI-3 is (P1 Listener Fans)/(Cume Listeners Sampling)

Program Development feeds P1 Listener fans into Pledge Development.

4. The primary goal of Pledge Development is to convert “P1 Listener Fans” into “Dollars Pledged.”

KPI-4 is (Dollars Pledged)/(P1 Listener Fans)

Pledge Development feeds Pledged Dollars into Gift Development.

The diagram below shows the optimized strategy for a pledge drive using Data Science and BroadcastMetrics.

EXAMPLE OF A PLEDGE DRIVE STRATEGY ANALYSIS Courtesy of BroadcastMetrics

5. The primary goal of Gift Development is to convert “Dollars Pledged” into “Gift Dollars Received.”

KPI-5 is (Gift Dollars Received)/(Dollars Pledged)

A portion of Step-5 Gift Dollars Received is then reinvested into Step-1 Signal Development, and the Growth Cycle repeats itself.

The faster the Growth Cycle “spins,” the faster the station or network grows.

SIZE AND SPEED OF THE FIVE DATA SCIENCE GROWTH FACTORS

Data Science helps to allocate scarce resources among the five revenue opportunities. It also helps to balance short-term revenue growth with long-term revenue growth.

Each of the five primary revenue growth factors has different characteristics for:

• Size of increasing revenue, and
• Speed of increasing

For example, one network’s leadership team wanted to emphasize long-term growth and therefore prioritized Step 1, Signal Development.

Another network wanted to emphasize short-term cash flow and therefore prioritized Step 5, Gift Development, and Step 4, Pledge Development.

The specific needs of each station or network at any point in time can be met by changing the relative emphasis among the five Data Science Growth Factors.

SUMMARY

Data Science can support radio leadership in developing a comprehensive station or network growth strategy. It creates new data and information to support radio leaders as they grow their stations and networks.

Newly created data and information help radio leaders to effectively allocate scarce human resources, capital resources, and operating resources in a manner that helps maximize growth.

The new data and information created by Data Science help support network leaders as they grow:

• Signal coverage,
• Listening audience, and
• Donor revenue

Reinvesting a portion of increased Gift Development revenue (Step 5) into Signal Development (Step 1) helps a station or network grow.

Repeating the Data Science growth cycle year after year enables continuous, long-term, sustainable station and network growth.

Frank Kavenik is a Christian Radio Data Scientist who serves founders and leaders of major Christian radio networks.  He has completed over 900 Revenue Science projects serving radio leaders as they increased signal coverage, listening audience, and donor revenue.  

Frank developed the BroadcastMetrics Strategic Planning and Data Science System to serve Christian radio executives as they grow their stations and networks.  He has served the founders and leaders of some of the largest and fastest-growing Christian radio networks. 

Frank holds degrees in law, management, and engineering.  He has also been a radio station founder and owner.