You've mentioned that tying the team's work back to revenue is a hard story to tell. We've been doing some thinking on it. What follows is a handful of ways the story could go, along with how the number behind each one would actually get computed.
Some of these are probably off, and that's fine. Take what's useful and ignore the rest.
O&O
We know this world best, so we went deepest here.
1
What a promo plan does to ratings
"This plan should be worth about 0.3 of a point on the premiere, call it $500K in audience value. Ask me after, and I'll show you how close we got."
Measure The panel shows who saw a campaign's promos. Compare their tune-in against similar viewers who didn't see them. The difference, in rating points, is what the campaign bought.
Learn Do that for every campaign, every season. Each franchise builds a track record: how much lift its promo weight buys, and where more weight stops helping.
Steer Weight moves off saturated campaigns and onto ones still climbing. Same inventory, more tune-in. A promo that isn't landing shows up in week one, while there's still time to shift it.
Prove Next quarter's measurement shows what the moves recovered. Forecasts come as ranges, tighter for returning shows, and every prediction gets scored against what actually happened.
Why it's possible now None of this needs new data. The as-run logs, campaigns, and panel viewing have existed for years, just too messy and scattered to join. Prism exists to fix exactly that. And modeling like this is far cheaper for us to build and keep running than it would have been even a few years ago.
Why it compounds The measuring and the placing happen in the same system. Whatever a quarter teaches feeds the next quarter's plan on its own. No study, no handoff.
The financial case
The measurement side produces lift in rating points. The dollar side is a number you already have.
rating-point lift × your value of a rating point = what a campaign produced
RatingsMeasurement
2
More reach from the same weight
"You want more reach on 90 Day Fiancé? There's $1.5M of weight sitting past the point of doing anything. It's yours."
How it gets counted The panel counts how many times each viewer saw a campaign's promos across every network. That count doesn't exist today because each network plans alone. The first few exposures do the persuading. After that, another impression moves nobody, and all of that airtime is spent on nothing.
What changes A campaign can carry an effective reach goal, not just a GRP number. The optimizer then plans toward reaching new viewers enough times to matter, instead of piling more impressions on people who have already seen it. Part of this is available today; the new optimizer builds it out fully. The measurement in #1 can then show what that added reach bought.
Why it's possible now Plans are written in GRPs, and GRPs add while people don't. A campaign can hit every one of its numbers and still hammer the same heavy viewers. Effective reach goals are the fix, and building them out is part of what the new optimizer is for.
The financial case
The waste is measurable weight, and promo weight has a value.
weight past useful frequency × value of a promo GRP = value recoverable as reach
Reach & frequencyPromo effectiveness
3
Pricing our own air
"That launch got about $2M of our air, and it returned 300K premiere viewers."
How it gets counted Put a value on every promo slot, by network, daypart, and position. The slots are already tracked; the price tag is what's missing. Where the rates should come from is one of the things we'd work out with you.
Why it might be useful A priced slot can be compared, apples to apples, against anything else measured in dollars or demo GRPs. It also lets owned media be reported like a budget: this much value used, this much produced. Whether those comparisons ever come up in your world is a better question for you than for us.
The financial case
Priced slots make the portfolio total itself.
slots used × market rate per slot = media value deployed
Inventory valuePlanning
4
Schedule changes, absorbed fast
"They moved the finale to Thursday. The minute it changed we knew it put $800K of delivery at risk across 12 campaigns, and by Friday we'd clawed most of it back."
How it gets counted When a change lands, the new schedule runs through the same system that holds every plan. Out comes the impact, campaign by campaign: placements affected, delivery at risk, what a replan can recover.
Why it matters A campaign's flight is finite. Every day between the schedule changing and the plan adjusting means delivery lost, with fewer days left to win it back. Known same day, the loss is usually recoverable. Known late, the campaign just misses.
Why it's possible now The schedule, the inventory, and every campaign's plan already live in one system. Re-running them against a changed schedule is the same machinery as any what-if. The real-time optimizer, still in progress, is the eventual end state: a plan that adjusts on its own as the schedule does.
The financial case
Every change has delivery riding on it. The question is how much gets saved.
delivery at risk per change × changes per year × share recovered = value protected
SchedulingDelivery protection
5
Promos steered by signup data
"Prime promos on TLC sign up twice as many people per impression. Shifting the weight there is worth $3M a year in subscribers."
How it gets counted Your streaming attribution shows where signups actually came from. Compare that against where each campaign's target audience is, and some placements turn out to produce more signups than their audience size says they should, while others produce fewer. Placement scoring learns to favor the first kind.
How you'd know it's working Signups per unit of promo weight, quarter over quarter, on the same air. Each plan can also carry an expected conversion rate, so results get checked against what was expected, not just admired.
Why it's possible now The signup data is already flowing: your attribution, delivered quarterly, with years of history behind it. The placement scoring that uses it is part of what Momentum and Prism are being built to do.
The financial case
Signups are already valued internally. The trend line does the rest.
added signups per quarter × value of a subscriber = the gain
StreamingAttribution
6
Trying plans before committing
"We ran the quarter both ways before committing. The version we picked delivers 6% more, about $2M in audience value."
What exists The scenario machinery is already in the goal optimizer: copy the current plan, change something, re-optimize, compare the results side by side. That was always the intention behind building it, and the data underneath is there.
What's missing Shape, not machinery. Running a scenario isn't yet built around the questions your team actually asks, and we only half-know what those questions are. Which what-ifs matter, which comparisons should be one click, what a useful answer looks like. That's a conversation we'd want to have with you, and organizing the data underneath it is Prism's part of the job.
The financial case
The value lands wherever a tried plan beat the default one.
(chosen plan − default plan), summed across decisions = the gain
PlanningWhat-ifs
7
Growth without growing the team
"They handed us 5 more networks. We didn't add a single planner. That's $2M a year that never got spent."
What it means The optimizer and the agent carry the volume. Planners carry the strategy. Growing the portfolio stops meaning growing the operation.
Where it stands This is the north star of the current build, not a someday idea. The real-time optimizer, the agent, and Prism are its pieces, and most of the starters above are steps toward it.
"One plan covers the linear promos and the digital ones. Counting each viewer once freed about $1M in duplicated weight."
The sketch The same slot-valuing and frequency logic, extended to owned digital inventory, so linear and digital promotion can be planned with one view of who has been reached.
The financial case
Overlap between the two halves is measurable weight.
duplicated linear + digital weight × value of that weight = value redeployable
DigitalReach & frequency
9
Film promos, scored by tickets
"The campaign on our own air sold about 40K tickets opening weekend, call it $500K at the box office."
The sketch Ticket attribution is arriving alongside the signup data. The same placement scoring from #5, pointed at movie campaigns.
The financial case
Tickets are already valued. Attribution supplies the count.
incremental tickets attributed × value per ticket = campaign value
TheatricalAttribution
Beyond O&O
Made possible by the foundation of Prism and Momentum.
10
Paid media that skips who we already reached
"Paid only buys the people our air missed now. Same reach, about $2M less a year in paid."
The idea Owned exposure feeding paid planning, so the two stop overlapping. Same total reach for fewer paid dollars.
The financial case
Paid impressions are hard dollars, so avoided ones are too.
"The audience we built for Shark Week promos? Ad sales packaged it at a premium. An extra $200K, on one deal."
The idea The definitions behind promo targeting could also define what ad sales sells. Data-defined audiences are the direction the ad market has been moving for years.
The financial case
Audience-targeted inventory generally prices above a demo-only ratecard.
inventory sold with audience targeting × CPM premium = new revenue
Ad salesNew revenue
12
Finding the paid spend that does nothing
"A third of that search spend, about $3M, was buying signups we would have gotten anyway. It funds something useful now."
The idea Holdout testing against the attribution data. Spend that takes credit for signups that would have happened anyway gets found, and that budget goes somewhere useful.