UC-4
Cut the budget without cutting the thing your audience actually shows up for.
Rank every programme on cost per audience-hour and on what it brings in — and find the small-audience programmes that are the only service in their county before anyone proposes cancelling them.
- Who this is for
- Programme Director · Chief Operating Officer · Chief Financial Officer
- When it comes up
- Budget balancing after an appropriation cut. Uncomfortable, and unavoidable.
Sound familiar?
Three things we hear in almost every conversation.
- “We have to close a two and a half million dollar gap and every decision is being argued from memory.”
- “The loudest programme in the building is not the one with the audience, and I cannot prove it.”
- “We cancelled something once that turned out to be the only thing we aired for a whole part of the state.”
What it runs on
The data you already have.
A connector pulls on a schedule. An upload is the export you already download — dropped in, profiled and cleaned on arrival. We label which is which because there is no live connector for Nielsen, streaming providers, podcast hosts or donor CRMs yet, and pretending otherwise would waste your time.
- Programme scheduleupload
- Audience by daypart and programme (Nielsen export)upload
- Streaming and podcast by episodeupload
- Carriage and licensing costsupload
- Underwriting revenue by programmeupload
- YouTube Analyticsconnector
How it works
From those files to the answer, in 4 steps.
The catalogue gets a Pareto line
Every programme ranked by audience, with the cumulative curve drawn and the threshold marked — so you can see precisely which handful of titles carries most of your reach, and how long the tail really is.
analyze_content_catalog · rank_entities
Cost meets audience on the same row
Carriage cost, production cost and underwriting revenue joined to audience hours, giving a cost per audience-hour and a net contribution per programme. This is the number the conversation is missing.
join_datasets · calculate_derived_metrics
Trends separate decline from a bad month
Each programme against its own history, so a title in genuine structural decline is distinguishable from one that had a soft quarter — and from one that is quietly growing.
compare_periods · rolling_window_analysis · detect_change_points
Geography protects the irreplaceable
Before anything is cut, the analysis flags programmes whose audience is concentrated in counties with no alternative service. A small statewide number can be the entire service somewhere specific, and that is a different decision.
analyze_concentration · create_geo_chart · benchmark_segments
What you get
On your screen at the end of it.
- Every programme ranked by cost per audience-hour
- The Pareto curve showing where your reach actually comes from
- Net contribution per title, once underwriting is counted
- A flag on every programme that is the only service in its county
Try it with your data.
Send us your schedule, an audience export and your carriage costs. We will rank your catalogue and show you what the tail really looks like.
Free, no obligation, and the dashboard is yours whether or not you continue. Prefer to talk first? Book a walkthrough.
Questions
What people ask before they start.
+Our cost data is not per-programme. Can we still do this?
Partly, and the gaps are stated rather than filled in. A coverage report shows which programmes have cost data and which do not, so the ranking is explicit about what it could and could not include.
+Can it combine broadcast ratings with streaming and podcast numbers?
It aligns them and shows each contribution separately with the method written down. It does not silently add incompatible metrics together — that would produce a number nobody could defend.
+How far back should our data go?
Two years lets you separate a trend from a season. One year is workable; anything less makes decline and seasonality hard to tell apart, and the analysis will say so.
+Can we share this with the board without sharing the underlying salaries?
Yes. Regions within a dashboard carry their own access rules, and columns can be governed individually, so cost detail can be visible to the executive team and hidden from a wider audience.
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