PPV and bundle pricing calculator

Why comparing beats guessing

Pricing arguments among creators tend to be about the right number, which is unanswerable, when the useful question is which of several plausible numbers produces the most money from the audience you actually have. That is a comparison, and comparisons are calculable.

The thing that makes it non-obvious is that price and conversion move in opposite directions but not at the same rate. Double the price and lose half your buyers and you are exactly level. Double the price and lose a third of your buyers and you are substantially ahead, with less content to make and fewer people to service. Which of those happens depends on your audience, and the only way to find out is to try it and record what happened.

Where the money actually is

For most subscription creators, PPV and tips are a larger share of income than subscriptions. The subscription gets someone through the door and establishes that they are willing to pay you; what they spend afterwards is where the business is. A creator with two hundred subscribers and strong PPV conversion routinely out-earns one with six hundred and none.

This is worth knowing before you conclude your problem is subscriber count. Doubling what your existing audience spends is often more achievable than doubling the audience, and the tool's scenarios are a way of finding out what that would take.

Bundles

A bundle works when it converts people who would have bought nothing, not when it discounts people who would have bought anyway. Model it as a scenario: a bundle price with a higher conversion rate against individual items at a lower one. If the bundle wins, it is finding you buyers. If it loses, you have discounted your best customers for no reason.

What this tool refuses to tell you

It will not give you a "perfect" price, and any tool claiming to is guessing with more confidence than it has earned. The conversion rates you enter are estimates about human behaviour, and the output is only ever as good as they are. Use figures from your own previous sends where you have them, model a range where you do not, and treat the result as a way of ordering your options rather than a prediction.

• •A single content set can be re-sold to new subscribers for months, so a high production cost is spread further than one send suggests.
• •Sending too often trains people to wait for the next one, which shows up as falling conversion rather than as an obvious mistake.
• •Very low prices can reduce conversion rather than increase it, because they signal something about the content.