1. Past runs
2. The next run (optional)
Booking curve assumed: 35% of final bookings are in 28 days out, 60% at 14, 80% at 7, 92% at 3. Replace it with your own history when you have it.
Result
Questions people ask
What is a good ad sell-through rate for a newsletter or podcast?
There is no single number, because it depends on how many slots you offer per issue. As a rule of thumb, sell-through above about 90% usually means you are underpriced or short of inventory, and below about 60% means price, reach or slot count is out of line with demand. Track it per run and watch the trend rather than one number.
How does this tool decide whether to raise or lower my price?
It anchors on your current price and recent sell-through, applies a price response that is fitted from your own history when there are enough varied-price runs (otherwise an assumed one), and finds the price that earns the most per run. It never moves more than 25% in one step.
Why does a sold-out run not prove I can charge more?
A sold-out run only shows demand was at least your capacity, not how far above it. The tool assumes a modest excess and labels it, and it leaves sold-out and empty runs out of the price-response fit because they only bound demand.
Is this a forecast or financial advice?
No. It is a planning aid that does arithmetic on the numbers you paste in and on stated assumptions. Real buyers respond to timing, audience fit and relationships. Treat the output as a hypothesis to test one price change at a time.
What this does not cover
Audience quality and niche, seasonality, sponsor renewals and relationships, make-goods, agency commissions and marketplace fees, tax, and the difference between flat-fee and CPM deals. Price response is a simple constant-elasticity model; with fewer than four usable runs at two or more prices it is an assumption, and the page says so.
Related tools: the newsletter sponsorship rate calculator for a first price from audience size, and the podcast sponsorship rate calculator.