Three numbers, and a couple of minutes will draw an indicative picture of how Axate’s subscription and casual pay-as-you-go payment platform could help you build your direct audience revenue. Here’s what sits behind it, and how we can help you add your own data to give an even better answer.
Most media companies we talk to ask the same first question: what would this be worth to us?
The reader revenue assessment is designed to give a quick, honest starting point. It is an indicative illustration, not a forecast, and it is built to be conservative. But even so, we hope it will show you how even some simple changes can start to grow the bottom line.
The basics
The model is built on inference drawn from three key data points:
Your monthly unique users, which we treat as a baseline for your immediately addressable audience
Whether you sell a subscription today.
Your full subscription price before any discounts, or the price you would charge if you launched one.
What it works out
From those three numbers, the assessment infers the rest:
Your real audience. It removes 15 per cent for bots and other non-human traffic before anything else is calculated. That is a cautious figure: Imperva estimates that bots generated 51 per cent of all web traffic in 2024, though analytics tools already filter out some of it.
What kind of media company you are. A large enterprise, a stable subscription-led publication, an ad-led business or a specialist niche proposition - based on your audience size and whether you already charge.
What a reader would pay. A price per article and a free point, worked out from your subscription price, so that PAYG looks compelling, but never offers better value than subscribing.
For example, a title with 750,000 monthly users and a £26 subscription would see a price of 80p an article, with a maximum of £1.60 in a day.
The assumptions that matter most
The report shows you every assumption it uses. The defaults assume a title that publishes at least one new piece of content every day, which is what gives readers a reason to come back. Four do most of the work:
Share of content that carries a price (default: 80%). If most content stays free, results fall towards nothing.
How often a regular PAYG reader returns and pays (default: about once a week). Return frequency is the biggest single driver of value, and depends on publishing something new every day.
Share of readers who become paying customers (default: varies with audience size). Smaller, specialist audiences tend to convert at a higher rate.
Subscription discounting (default: stopped). Readers you would have kept with a cut price get a PAYG route instead.
If you do not sell a subscription today, the assessment assumes you launch one at the price you gave, alongside PAYG.
Two scenarios, not one
The report gives two paths, each for year one and year three:
Baseline: change the business model. This means introducing casual payment in the form of PAYG, putting a price on most of your content and stopping discounting any subscriptions. It’s very achievable, does not require any changes to the product whatsoever - though it does require a deliberate strategic change.
Stretch: change the product too. The reality is, most digital products are built around one of two revenue models - either one that aims to capture ‘all you can eat’ subscribers, or one that aims to maximise ad revenues.
We firmly believe that the real upside will come from building new products that customers will come back to habitually, around twice a week rather than once. This is where the value compounds.
Where the model is deliberately cautious
The figures are what you keep after the cost of taking payment. The tool does not count any effect on advertising, and it does not count single-article sales on top of day access.
Both are potential upside it leaves out.
How we refine it with your data
The tool knows nothing about your content, your market or your readers.
On a half-hour call we open the model with you and replace our defaults with what you actually know, one assumption at a time:
your audience figures, net of the bot traffic you already filter;
how much of your content you would realistically price;
how often your loyal readers return, from your own analytics;
how often you publish, which changes the free point and how often PAYG readers are likely to return;
your current subscribers, churn and any pricing tests you have run.
The result is a range you can take into planning, built on your numbers rather than ours.
[Book a call] · [Try the assessment]