> "Subscription fatigue" is the easy explanation when a paid product struggles. The more useful question is whether there was enough recurring value to begin with, rather than benefits assembled to justify a monthly charge

> Start with frequency: what do people already come back for. Then use registration as the halfway test, because if your most engaged readers won't create an account, a payment step will not fare better

> Build the paid tier around a behavior that already exists, giving people materially more of it. If the pricing page needs six unrelated benefits to feel substantial, no single benefit is strong enough

> Be deliberate about what stays free. A story that brings in thousands of first-time visitors has a different job from a specialist product consumed repeatedly by known users, and should be treated differently

> Forecast before you keep building. Apply realistic registration, free-to-paid and retention rates to your own segments, and if the range falls short of what the business needs, stop before the pricing conversation starts

I’ve run this process with several businesses this year, and it holds up every time. You don’t decide what the subscription includes and test it against the market. You pull apart your own traffic and behavior data, and only decide whether to keep building once that data has told you there’s something worth building. Here’s the process.

1. Start with frequency

The first thing I want to understand is what people already come back for.

For a publisher, that might be a morning briefing, live coverage, a specialist vertical, or a particular columnist. Pull the behavior of your most engaged users and look for repeat patterns. Which products correlate with higher visit frequency? Which newsletters reliably drive people back to site? Which features appear disproportionately among your most active readers?

You’re looking for evidence of habit. A large audience visiting once or twice a month may still support a strong advertising business, but it’s weak evidence for a recurring consumer proposition.

2. Use registration as the next test

Before asking for a credit card, see whether people are willing to identify themselves.

Registration introduces a small amount of friction and asks the user to exchange something of value, usually an email address and some data, for a better experience. That makes it a useful halfway point between anonymous consumption and payment.

Look at registration conversion by audience segment, then compare registered and anonymous users on frequency, depth of engagement and eventual propensity to subscribe. If your most engaged readers still resist creating an account, that’s worth understanding before a payment step goes in front of them.

If registered users who adopt a particular feature come back twice as often, that is a much more useful metric for proposition design than a brainstorm full of ideas about premium benefits.

3. Build paid around behaviors that already exist

Once you know what your most engaged registered users are doing, the paid proposition should give them materially more of it. That might mean greater access, deeper utility, more convenience, exclusivity or a better experience. The important part is that the benefit connects to something the audience has already demonstrated it values.

If live coverage drives unusually high frequency, ask what a paid live product could add. If specialist newsletters show the strongest retention signals, deeper analysis or additional editions may have more value than an unrelated bundle of perks. If users who save articles and follow topics return more frequently, better personalization may be more compelling than another piece of “exclusive content.”

This is also where proposition bloat creeps in. If the pricing page needs six unrelated benefits to make the subscription feel substantial, that’s usually a sign no single benefit is compelling enough. The pricing page should be the output of the proposition work rather than the place where the proposition gets decided.

4. Be deliberate about what remains free

Publishers have an added complication because the free product often drives discovery, advertising revenue and the future subscriber funnel.

Moving too much behind a paywall can reduce the audience available to convert later. Leaving too much outside makes the paid proposition harder to distinguish. The answer depends on what role each piece of content or product plays in the journey.

A story that brings thousands of first-time visitors into the funnel may have a very different job from a specialist product consumed repeatedly by known users. Treating them identically because they both sit on the same website is usually where the trouble starts.

5. Forecast before you keep building

Most subscription models get validated backward. Leadership picks a revenue number it needs, and the team keeps building a forecast toward it without checking whether the underlying audience can actually get there. The proposition work continues on momentum, not evidence.

Build a forecast from the same data steps 1 to 4 produced instead. Take your traffic and frequency segments, apply a realistic registration rate, apply a free-to-paid rate benchmarked against comparable products at a similar price and frequency, then apply a retention curve for that price tier. You’ll get a range, not a number. Compare it to what the business actually needs. If the range falls well short, that’s the signal to stop building and rethink before the pricing conversation even starts. Better to find out before another quarter of work goes into a proposition the audience was never going to support.

Do the work in steps one through five before you launch anything. Some of what comes back will tell you to stop, and that’s a better outcome at step five than a year into a proposition the audience behavior was never going to support.

If those behaviors aren’t there, you’re not a subscription business. Yet.

Jonathan Gupta-Buckley founded The Twenty One and Kaai after a decade leading audience and subscription growth inside News Corp, including building the largest paid subscriber base in Wall Street Journal history. Today, TTO embeds senior operators inside the world’s most ambitious businesses to solve growth challenges in practice, build internal capability, and leave teams with systems they can run themselves. Kaai is TTO’s proprietary AI growth analytics tool. It is currently deployed at a number of global media businesses.