Every channel gets tired. Drag one and see exactly where.
The first dollar you put into a channel works harder than the fifth. These curves are your model’s actual answer to “how much harder” — drag a channel’s spend and the revenue figure recalculates from the same maths the budget planner uses. Nothing is being simulated for show.
tires slowly — still the best next dollar
$107.7M
as you ran it
$30.49
still profitable
tires slowly
$18.3M
as you ran it
$0.72
below break-even
tires steadily
$6.5M
as you ran it
$0.56
below break-even
tires slowly
$5.0M
as you ran it
$0.49
below break-even
tires slowly
$3.5M
as you ran it
$0.60
below break-even
tires steadily
$3.5M
as you ran it
$0.49
below break-even
tires steadily
$3.4M
as you ran it
$0.55
below break-even
tires steadily
$3.3M
as you ran it
$0.54
below break-even
tires slowly
$2.0M
as you ran it
$0.69
below break-even
“Next $1 returns” is the number that should drive a budget decision, not the average. Search — Non-brand has averaged $42.94 across everything you spent there, but the next dollar returns about $30.49. TV — Broadcast's next dollar returns about $0.49, which is the case for moving money — and it does not depend on being sure that channel lost money overall.
Your year, as you have it set right now
$263.8M
total revenue · against $263.8M at the spend you actually ran
$22.6M
media spend · was $22.6M
$6.78
revenue per $1 of media
Nothing is moved yet, so this is the run's own answer: $263.8M, the same figure on every other screen. Drag anything and watch how much less the revenue moves than the spend does.
The caveat that travels with this screen
These curves are the model’s best guess, drawn as single lines because that is what you can drag. The ranges behind them are wide enough that a small move is a direction, not a forecast. The budget planner puts the uncertainty back on — it reports the odds a plan beats what you do today rather than a single number.
What dragging does not change
Nothing here re-runs the model, and nothing here changes a verdict. Whether a channel has proven it pays is a property of the fit and stays where it was on the channels table. This screen is for exploring what the answer implies, not for arriving at a new one. revenue per unit of spend.
Two different questions, and people mix them up
What your next dollar is worth, channel by channel
Each bar is the range we think the answer sits in, and the solid mark is our best single guess. A short bar means we are confident; a long one means the data did not pin it down. The vertical line is break-even — a bar sitting entirely to its right has proven it pays, and one that straddles it has not, whichever side its mark falls on. A bar ending in › runs off the right of this scale — the numbers beside it are still the real ones. We hold the scale back so the other channels stay readable.
Keep funding these
No channel has proven the next dollar pays
Every channel's range crosses break-even, so we cannot yet say of any of them that more money would pay for itself. That is a statement about the data, not about the media.
The best of them
Search — Non-brand
Its best guess of $30.49 is the highest here, so it is where an extra dollar should go first — but the range still reaches down past break-even, so treat that as a bet, not a fact.
Where we are least sure
Search — Brand
Search — Brand's range runs from $0.12 to $45.78 — the widest here. Usually that means its spend barely moved, so the model had little to learn from. Vary it and this bar will tighten.
The same channels, with the rest of the numbers
What each channel has returned across everything you already spent, next to what the next dollar would return. The gap between those two is what you have used up: early spend in a channel works harder than late spend, so a channel can have a great history and very little left to give.
| Channel | Spend | So far | Next dollar | Already used up | Share of the effect |
|---|---|---|---|---|---|
| Search — Non-brand | $2.5M | $47.71$1.02–$60.78 | $30.49$0.45–$38.08 | −36% | 45.3%1.0–57.6% |
| Search — Brand | $1.7M | $1.55$0.31–$72.52 | $0.72$0.12–$45.78 | −53% | 1.0%0.2–46.1% |
| Out of Home | $1.3M | $1.21$0.28–$4.04 | $0.69$0.15–$2.52 | −43% | 0.6%0.1–1.9% |
| TV — Cable | $2.8M | $1.06$0.29–$2.99 | $0.60$0.15–$1.82 | −44% | 1.1%0.3–3.1% |
| Social — Meta | $3.5M | $1.27$0.28–$5.45 | $0.56$0.11–$2.72 | −56% | 1.7%0.4–7.2% |
| Social — TikTok | $1.9M | $1.22$0.29–$5.36 | $0.55$0.10–$2.66 | −55% | 0.9%0.2–3.8% |
| Programmatic Display | $1.8M | $1.22$0.28–$5.46 | $0.54$0.10–$2.71 | −55% | 0.8%0.2–3.7% |
| Video — CTV | $2.1M | $1.16$0.25–$4.60 | $0.49$0.09–$2.18 | −58% | 0.9%0.2–3.7% |
| TV — Broadcast | $5.1M | $0.86$0.27–$2.07 | $0.49$0.13–$1.28 | −44% | 1.7%0.5–4.0% |
What each channel would do at other budgets
Each curve runs that channel from spending nothing up to 2.0× what you spent, keeping the same on-and-off pattern rather than smearing the money evenly — so every point on it is a plan you could actually go and buy. The shaded band is how sure we are: where a curve flattens off is itself a guess, and the band shows how much room that guess has.
Doubling spend would add roughly 45% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 43% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 38% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 37% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 36% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 49% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 36% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 31% more outcome from this channel — it is approaching its bend.
Doubling spend would add roughly 39% more outcome from this channel — it is approaching its bend.