> Audience consultant Khalil Cassimally's rule is to use synthetic audiences to narrow, never to decide. They rank options and surface objections, but cannot tell you magnitudes like willingness to pay

> Start with the decision you need to make, not the question you want to ask. Most synthetic research fails by producing interesting material nobody was ever going to act on

> Ground the panel in words real readers actually wrote. Old interview transcripts, cancellation reasons, unread survey comments. The test is whether you can name the humans inside the system

> Most teams only ever count responses. The better question is where your draft conflicts with what you have documented about a reader, which is analysis rather than impersonation

> Tell it to answer as a reader rather than an analyst, and that indifference is valid. Then validate whatever survives with real people, which is where the saving comes from

Few newsrooms are commissioning representative surveys. Meanwhile interviews cost real money and real weeks. Plenty of newsrooms also treat editorial instinct as the senior evidence, with audience feedback consulted after instinct has already decided. The effect is the same either way. When there is appetite for research, it goes to the bigger decisions while everything else gets settled without evidence.

That leaves a whole category of question permanently unanswered. The recurring ones, where we need to know:

• How a piece of content will serve the users we are trying to reach
• Which of several options is weakest, before we invest in any of them
• What objections a change is likely to run into
• How different groups of users will react to the same thing

To take one example: whether a new onboarding flow feels like a data grab. Too small to commission a study for, and it creates uncertainty that festers within the onboarding team. So somebody decides on instinct, usually whoever is most senior, and the instinct becomes the decision. It might well be right. Nobody will ever know though because nothing was tested.

This is the gap synthetic audiences fill. They don’t have to replace the research we already do well. What they change is the dozens of small calls a month that currently run on somebody’s hunch. And for the many newsrooms doing no audience research at all, the comparison isn’t between synthetic feedback and properly-designed research. It’s between synthetic feedback and nothing, and synthetic feedback done well beats nothing.

The value is that a whole class of decisions moves from opinion to evidence, at a cost and speed that makes asking routine.

What a synthetic audience is

“Synthetic audience” is an umbrella term, and the field hasn’t settled on what sits under it. You’ll see people use synthetic personas, synthetic users, digital twins, synthetic panels and silicon samples loosely and sometimes interchangeably. I’m using three here because the differences between them change what we can trust.

• A synthetic user is an LLM given a description of a type of person and asked to respond as they would. We write the description – the segment’s age range and media habits, whatever we know – put it in the prompt, and ask the question. Nothing sits underneath it. What comes back is the model’s averaged sense of what somebody matching that description would say, assembled from everything in its training data about people like that.
• A digital twin is built from one real person’s own material: an interview transcript, their survey answers, their support emails, their behaviour on our site. That material goes into the prompt and the model answers new questions as that person. It’s also possible to fine-tune a commercially available LLM on the material instead of putting it in the prompt. Academic studies from Stanford and Columbia tested that route, and neither found it beat simply placing the person’s words in the prompt. Which is good news for small teams: building a twin should not require any substantial engineering lift.
• A synthetic panel is either of the above, multiplied. We can build twenty or fifty across our segments, put the same question to all of them, and read the pattern rather than any single answer.

What synthetic audiences are good for

A number of use cases have emerged. These four have the clearest evidence behind them:

Testing language before it goes out. Paywall messages, membership appeals, onboarding copy, campaign framing. We put the draft in front of a synthetic panel and ask what they find unclear and what would make them stop reading. This is the highest-value use, partly because language is what these models handle best, and partly because it’s a decision we make most often.

Narrowing a field of options. Six newsletter concepts, or four pricing structures. The panel won’t tell us which one to launch. But it will reliably tell us which ones are weakest. So, the real research budget goes to the survivors. Spindrift Beverage Co., a US drinks brand, used a synthetic panel to choose between new product concepts. It reached the same answer in a week that a 500-person consumer study had taken two months to produce.

Surfacing objections we haven’t thought of. Ask the panel what would stop them subscribing, or what they’d assume about us from our about page, and we get a list of concerns to check. Where synthetic panels have been compared against real research, they have identified the same themes and the same objections. The magnitude and the proportions differ, the list doesn’t.

Comparing groups against the same thing. Put one paywall message to a synthetic lapsed-subscriber panel and a synthetic loyal-reader panel, then read the difference. Relative comparison is where these systems are most useful.

You may have spotted that all of the four use cases narrow or pressure-test rather than decide.

How accurate are synthetic audiences

A figure of around 85% circulates in coverage of this field, usually without much explanation. Read quickly, it suggests a synthetic version of a person gets 85 out of every 100 answers right. That isn’t what was measured.

The figure comes from the Stanford study. Researchers interviewed just over a thousand people at length. They built a digital twin of each person from their interview transcript. Then they tested whether the twin could predict that person’s answers to a survey the person had already completed.

But they didn’t score the twin’s answers against the persons’ answers and leave it at that. Because if we ask a person to fill the same survey again two weeks later, they match their own earlier answers only about eight times in ten. (Memory shifts!) So, the fair question is not whether a twin matches perfectly. It’s how a twin does against that eight-in-ten human benchmark.

Researchers found that the synthetic twins reached roughly 85% of that human benchmark – so, not 85% of the answers.

The figure tells us that synthetic twins built on rich individual material carry genuine signals about the people they came from.

The evidence in this field is still early, and most of it comes from outside media. For me, that’s another reason to use synthetic audiences for narrowing rather than deciding, which is what the rest of this piece argues for.

Where synthetic audiences stop

They can’t tell us how much. Synthetic responses cluster. Real people spread out more across opinions, while synthetic ones converge towards each other. A panel can tell us which option comes out ahead. It can’t tell us by how much, which rules out adoption rates, willingness to pay, satisfaction scores and anything else where the size of the number is the finding.

They can’t show us the small segments that matter. Clustering also means that the users at the edges disappear: the share of subscribers already on their way to cancelling, or the small core of superfans who account for a disproportionate slice of revenue. Those groups are small because they’re specific, and specificity is something a synthetic panel loses.

They tilt in a consistent direction. Synthetic respondents tend to be WEIRD (Western, Educated, Industrialised, Rich, and Democratic). They come out more comfortable with technology, less worried about privacy, better informed and more agreeable than the people they’re modelled on.

They shouldn’t speak for communities we haven’t spoken to. A team in the US building a WhatsApp media-literacy service for the Indian diaspora tried synthetic personas and got the diaspora as Westernised media imagines it. They caught it because they knew what the actual community sounds like. This is the kind of stereotype that synthetic responses can perpetuate.

How to start experimenting with synthetic audiences

Running a synthetic panel takes four steps, and each exists to make the next one worth doing.

The first fixes what you’re actually trying to settle, so you don’t generate material nobody acts on. The second decides what evidence the panel stands on, which sets how much weight its answers can carry. The third picks the kind of question you’re putting to it, which determines whether the answer is usable at all. The fourth gets an honest answer out, then records it in a form a colleague can judge for themselves rather than take on trust.

Set up once, the marginal cost of the next question is close to nothing. That’s the point. You’re building something you put questions to whenever they come up.

1. Fix the decision before you write the question

Most synthetic research fails before a panel is ever built, by producing interesting material nobody was going to act on in the first place.

Understand what you’re trying to achieve – what decision you’re hoping to make. Then determine the insights you need to inform the decision. Then figure out how to get those insights from a synthetic panel.

This ensures that the work you’re going to do is aligned with what you’re working towards. This is the step that stops the output becoming a slide nobody uses.

2. Decide what data the panel is standing on

What a panel stands on sets the ceiling on everything after it. The same question put to a well-grounded panel and an ungrounded one produces answers that may look similar but instead mean completely different things.

There are three levels:

• Nothing. A prompt describing a reader, with no evidence underneath it. What comes back is the model’s general impression of people like that.
• Demographics. Market or audience data about the segment you’re aiming at. Better, and still a description of a category rather than of anybody.
• Real material from real readers. Words that actual people you can name said or wrote.

The test is whether you can name the humans whose words are in the system. If you can’t, you’re on one of the first two levels.

Reaching the third level may be easier than it looks, depending on what your newsroom has kept. Worth looking for:

• Past interview transcripts, from any research project, however old
• Open-text answers from surveys (which usually go unread)
• Subscriber cancellation reasons
• Support and complaints emails
• Comments and community posts

Prepare the material by anonymising the person and keeping the detail that makes them specific: their circumstances, and what they came to you for. Spread it across your segments rather than piling it up. Fifteen people covering five reader types beats forty of the same type.

3. Pick the job

There’s more than one kind of question you can put to a synthetic panel. Two are worth setting out here, because most teams use the first but never the second. Choosing deliberately between them is what separates a usable answer from a merely plausible one.

• Count them. Put the same question to the whole panel and use the aggregate: which of six concepts is weakest, or which objection comes up most often. Read the ranking and ignore the margins. This is the workhorse, and it’s subject to the tilt described earlier.
• Analyse against them. Instead of asking how users would react to a membership appeal, ask where that appeal conflicts with what you’ve documented about them. The model isn’t being asked to be anyone. It compares your draft against a profile you wrote and can check, then hands back specific points of friction you can verify or throw out. Most teams never try this, and it’s the job best matched to what these systems genuinely do well, which is analyse language.

4. Make it argue back, then record what you did

Left alone, these models are agreeable, and an agreeable panel tends to tell you what you already believe.

Three things to build into the prompt:

• Tell it to answer as a reader rather than as an analyst. Otherwise the responses arrive sounding like a dull report, with tidy conclusions no human user would share.
• Tell it that being indifferent is a valid answer. Plenty of readers genuinely don’t care, and a panel where everyone holds a strong view is already wrong.
• Show it a few examples of how real people answered a similar question, with any polished phrasing taken out.

Then narrow with the panel and validate the surviving one or two options with real people. You’re only testing what has already survived something, which is where the saving comes from.

Finally, write up what you ran: who the panel was defined as, what it was grounded in, what you showed it, what you asked, what came back, and what still needs checking. Synthetic output is convincing whether or not it happens to be right. In one study, experienced researchers reviewing persona material could not reliably say which of it had been written by people. Making the output less convincing doesn’t help either, because results that read as obviously machine-made don’t get acted on. Since you can’t remove the believability, the write-up is what stops a plausible answer becoming a fact by repetition.

Start with the research you already have

The case for synthetic audiences isn’t that they closely match real readers. Academic testing has consistently found that they don’t. The case is that most audience questions in most newsrooms are currently answered by whoever is most senior in the room, and a synthetic panel grounded in things our actual readers said is better than that.

So, use them to narrow, not to decide. Ground them in real material, and know which level you’re on. Ask them to compare and to analyse. Keep them away from magnitudes, from the small segments that may matter most, and from communities you haven’t met. And, finally, validate what survives with people.

To get started: find the research your newsroom already commissioned and hasn’t opened since – the launch interviews, the subscriber survey, last year’s churn study – and work out which of this month’s decisions it could answer, if only you could ask it questions.

> The Economist has launched a dedicated subscription tier for access to audio and video formats, priced lower than the core digital subscription to attract new audiences

> The "Halo Effect": From early signals, the team has observed an uptick in core Premium sign-ups. Seeing a cheaper, format-specific option next to the full product acts as an anchor, nudging undecided visitors to pay a little extra for the full suite.

> Net-New Audience: Conversions through Play have been driven almost entirely by brand-new readers rather than existing subscribers trading down.

> Play is part of The Economist's wider strategic development (alongside podcasts, short-form video and "Insider") towards building deeper, more "human" relationships with audiences

The reasoning behind building it as a tier rather than a separate product, in Arnot’s words, was straightforward: a growing audience across all age ranges, not only younger readers, is consuming news in audio and video form specifically in the in-between moments of a day, commuting, walking a dog, running errands. The Economist wanted a way to show up at this moment without asking people to pay full price for a format mix they didn’t want yet. It’s also, deliberately, a lower-priced entry point aimed at bringing younger demographics into The Economist’s orbit before they’re ready for the full written product.

Arnot was clear that this is not a sign of declining interest in text. Older subscribers still demand “the whole buffet” of text, audio, and video. However, AV formats are specifically what attract the next generation, audiences who are likely to skew toward 90% audio-video consumption and 10% print.

How Play is marketed and priced

On the acquisition side, paid media campaigns in test markets lead directly with the Play proposition. However, when prospects land on the offer page, they see all three tiers side-by-side: Play, Premium (Digital), and Premium Plus Print.

Play receives the same intro mechanics as the core subscriptions: 30% off an annual pass or a one-month free trial.

Early signals, three weeks in

So far, subscription growth is looking very promising and, critically, existing Premium subscriptions in those markets have stayed healthy. Arnot even noted an uptick in Premium sign-ups that they attribute partly to Play’s presence on the offer page. Seeing a cheaper, format-specific option next to the full product seems to be nudging some undecided visitors toward paying a little more for everything, rather than pulling people down to the cheaper tier. So far, everyone acquired through Play has been genuinely new to The Economist, rather than existing subscribers trading down.

Importantly, Arnot’s team is watching closely to check that the new lower tier isn’t cannibalising their classic subscription. The logic they’re applying: it’s fine to accept some cannibalization risk as long as incremental new subscriptions outweigh it, and so far, that hasn’t materialized as a problem.

Product portfolio realignment: Play vs Espresso

The Economist already operated a lower-cost daily news offering, Espresso, alongside Economist Podcast Plus. However, Espresso offers only a handful of written pieces per month—a materially thinner proposition than Play’s full audio-video catalog.

To prevent audience confusion and eliminate product overlap:

1. The Economist delisted Espresso from app stores entirely within the Play pilot markets.
2. The team funneled all lower-friction entry points toward one unified brand experience inside the primary app ecosystem.

The wider relationship-building strategy

For Arnot, Play is one piece of a long-term evolution toward human-centered publishing:

1. Podcasts (top of funnel): Un-paywalled podcasts introduced audiences to journalists as real people—a shift for a publication that historically ran without bylines.
2. Short-form video (mid funnel): Put journalists directly in front of the camera, deepening visual familiarity.
3. Insider (retention & loyalty): A premium feature launched in late 2025 that brings subscribers into the newsroom through editor-led shows, biweekly newsletters, and newsmaking interviews with global leaders. The value of these “human” formats was echoed by Diana Babei, Principal Product Manager, at Audiencers’ Festival London, who shared that insider is already proving to build loyalty and trust in ways that article text doesn’t, including high engagement with this product (75% of subscribers) and lower churn among Insider viewers. 

4. Play (acquisition & conversion): Uses the same human-first AV formats that drive Insider’s loyalty, but packages them at a lower price point to build habits and acquire audiences who haven’t yet subscribed

Arnot connected this directly to the pressure AI search and AI-generated summaries are putting on publishers broadly: as it becomes easier for a reader to get information without ever visiting a publisher’s site, the case for a human-centered, personality-driven product only gets stronger, not as a defensive move, but as one of the few remaining things a subscription can offer that a summary can’t.

Insider and Play, in that sense, aren’t two separate initiatives so much as two different answers to the same underlying bet: that in an AI-saturated information environment, the publishers who win will be the ones readers feel some kind of human connection to, whether that connection starts with a $15 audio tier or a premium interview.

Key takeaways for publishers

• Lower barriers, high intent: Play acts as both an affordable entry tier for news consumers and a funnel toward the full-fat product
• Single-app ecosystem: Consolidating tiers inside one core app keeps brand equity intact and simplifies the upgrade journey
• Format-led segmentation: Rather than gating by topic, gating by format (AV vs. text) aligns naturally with mobile habits and daily routines
• Human-first defensibility: Prioritising formats that showcase real journalists builds trust and retention that AI summaries cannot replicate. 

Lennart Schneider is Founder of Subscribe Now, helping decision-makers in the subscription economy attract subscribers and keep them happy.

Let’s take a closer look at how it works in this excerpt from the book:

• Reach

Reach includes every interaction with potential subscribers, whether through your own channels or through partners, referrals, paid advertising, or other touchpoints.

a) Anonymous contacts: most of these contacts remain anonymous. They have interacted with your brand, but you cannot identify or contact them directly.

b) Leads: Leads are potential customers whose identity is known and who can ideally be contacted directly. Examples include newsletter subscribers, freemium users, registered accounts, or prospects collected through sales or telephone campaigns.

• Trials

Trial users are people who are testing the subscription through a free or discounted offer while deciding whether the product provides enough value to justify becoming paying subscribers.

• Active subscribers

Active subscribers are customers who have paid at least one regular subscription fee. Later in this article, I’ll explain in more detail where I draw the line between trial users and active subscribers.

Within the subscriber base, customers often move between different pricing tiers through upgrades and downgrades, increasing or decreasing their customer value.

A subset of active subscribers consists of customers with expiring subscriptions. When subscribers cancel, their subscription usually remains active until the end of the current billing period. In other words, the cancellation has been submitted but has not yet taken effect. During this remaining term, there is still an opportunity to persuade customers to reverse their cancellation.

• Former subscribers

Once a subscription has expired, customers become former subscribers. If they have given permission to be contacted, the win-back process begins. Former subscribers effectively become qualified leads again and can be targeted with dedicated retention and reactivation campaigns to encourage them to subscribe again.

Let’s go through these stages in detail:

1. Reach

The first step in any subscription business is making sure that potential customers become aware of your brand, your product, and your subscription offering. To achieve this, you should continuously expand the range of channels through which you reach your target audience. In addition to your own website, these channels may include social media, podcasts, public relations, events, partnerships, and many other customer touchpoints.

However, reach alone is not enough. What matters is reaching the right people. Ten million impressions may sound impressive, but they have little value if the audience has no genuine interest in your product. That’s why every subscription business should define an Ideal Customer Profile (ICP)—a description of the customers who are most likely to become successful, long-term subscribers.

Very few products are truly designed for everyone. Instead, companies should focus on the people or organizations that have a real need for what they offer. If you cannot clearly define your target audience, you risk wasting both time and marketing budget on customers who are unlikely to convert. An ICP therefore defines not only who you want to attract, but also who you deliberately choose not to target.

The best starting point is your existing subscriber base. Analyze your most valuable customers, identify the characteristics they have in common, and use those insights to guide future acquisition efforts. At the same time, you should regularly challenge your assumptions and explore whether there are attractive customer segments beyond your current audience.

For the digital subscription of a regional newspaper, an Ideal Customer Profile might look something like this:

Potential subscribers have lived in the region for several years, feel connected to their local community, and are interested in topics such as local politics, schools, transportation, public safety, sports, real estate, and local events. They are typically between 35 and 64 years old, employed, and have started a family. Many own their homes and expect to remain in the region for years to come. Although this profile is still relatively broad, it also illustrates that younger audiences or digital nomads may currently be much harder to convert into paying subscribers and therefore might not be the primary focus of acquisition efforts.

At the same time, additional customer segments may exist outside this core audience. For example, people who no longer live in the region may still have a strong interest in the local football club. The German newspaper Ruhr Nachrichten identified exactly this opportunity and introduced a separate, lower-priced BVB subscription for Borussia Dortmund fans living outside its core distribution area. This represents a second Ideal Customer Profile that can be targeted independently and generates up to 2,500 additional subscribers during a single football season.

Once you have identified the right audience, the next challenge is to create a positive first impression and spark genuine interest. Or, as Lucas von Gwinner and Dirk von Gehlen would put it, to build a strong brand. In their book Macht Marke, they argue that a brand is far more than a company’s name or logo—it is its reputation.

Before people decide to subscribe, they need to understand what your brand stands for and why it solves their problem better than any competing alternative. Strong brands communicate a clear positioning that differentiates them from competitors. As a result, they not only increase awareness but also improve conversion rates and strengthen long-term customer retention.

2. Leads

Before asking people to commit to a subscription, it is often worth getting to know them first and gradually introducing them to your product. A well-designed lead generation strategy helps build a large pool of potential subscribers whom you can engage with on an ongoing basis.

Compared with anonymous visitors, leads are significantly more likely to become subscribers. Because you know more about them, you can tailor your communication and offers to their individual interests, needs, and stage in the customer journey.

One of the key metrics at this stage is the Lead Rate, which measures the percentage of people reached who are willing to share their contact information and give permission to be contacted.

For example, if 5,000 out of 100,000 people reached provide their email address and marketing consent, the Lead Rate is 5%.

Lead generation serves two important purposes. First, it creates an owned audience that you can contact repeatedly without relying solely on paid advertising or third-party platforms. Second, it allows you to build trust over time before presenting a subscription offer. Especially for products that require a high level of commitment or involve a longer purchasing decision, this gradual relationship-building can significantly improve conversion rates.

3. Trials

In most cases, customers can only determine whether a subscription is worth paying for after they have experienced the product firsthand. Free or discounted trial offers lower the barrier to entry and encourage potential subscribers to give the product a try.

There is no universal formula for determining the ideal trial length or discount level. Companies continue to experiment with different approaches, and in my interviews I have seen everything from one-day trials to introductory offers lasting two years. Some businesses prefer short trials that generate revenue quickly, while others use longer trial periods to help customers build lasting habits, making the subscription an integral part of their daily lives before they begin paying the full price.

One of the most important phases of any subscription begins during the trial: onboarding. Effective onboarding helps new customers discover the value of their subscription as quickly as possible. The sooner they experience meaningful benefits and establish regular usage habits, the more likely they are to become long-term subscribers.

The Trial Start Rate measures the percentage of people reached who begin a trial. For example, if 2,000 out of 100,000 people reached start a trial, the Trial Start Rate is 2%.

The Lead-to-Trial Rate, on the other hand, measures how many known leads convert into trial users. If 500 out of 5,000 leads sign up for a trial, the Lead-to-Trial Rate is 10%.

Not every trial results in a paid subscription. Users who decide not to continue after the trial often return to the lead pool. If they have given permission to be contacted, they can be nurtured through future marketing campaigns and may eventually decide to subscribe.

4. Active subscribers

Active subscribers are the foundation of every subscription business. They generate predictable, recurring revenue and therefore determine the long-term health of the business. At this stage, the primary objective is to retain subscribers for as long as possible while increasing their lifetime value through upgrades and cross-selling where appropriate.

The Conversion Rate measures the percentage of people reached who become paying subscribers. For example, if 1,000 out of 100,000 people reached purchase a subscription, the overall Conversion Rate is 1%.

Like most funnel metrics, this KPI can also be broken down by funnel stage. If 200 of those 1,000 subscriptions originated from 2,000 trial users, the Trial-to-Paid Conversion Rate is 10%. Likewise, if 750 out of 5,000 leads purchase a full subscription, the Lead-to-Paid Conversion Rate is 15%.

One important question remains: When does a trial become an active subscription?

In practice, the boundary is not always clear. Many subscription businesses offer heavily discounted introductory pricing before customers begin paying the regular rate. However, not every discounted offer should be classified as a trial. A clear definition is essential because it directly affects the accuracy of key performance indicators such as retention and churn.

Consider the following examples:

1. DIE ZEIT

The German newspaper DIE ZEIT offers a print subscription in which the first 13 issues cost €5 each before increasing to €7.50. Since subscribers pay roughly two-thirds of the regular price from the very first issue and generate at least €65 in revenue, I would classify them as active subscribers from day one.

2. BILDplus

A BILDplus subscription costs €1.99 per month during the first year before increasing to €7.99 and can be cancelled at any time. In this case, I would consider only the first month part of the trial period. Once the subscription renews, customers become active subscribers, even though they continue to receive a substantial introductory discount.

3. The New York Times

The annual All Access subscription is sometimes available for $20 instead of the regular $90. Because these customers pay only around one-fifth of the standard price—and many are likely to cancel before ever paying full price—there are two reasonable approaches. They can either be treated as long-running trial users or as heavily discounted active subscribers.

Why does this distinction matter?

Cancellation rates during trial periods are typically much higher than among established subscribers. For that reason, trial users are generally excluded from core KPIs such as Retention Rate and Churn Rate. An inconsistent or poorly defined distinction between trials and paid subscribers can therefore distort these metrics and make performance comparisons misleading.

The Retention Rate measures the percentage of active subscribers who remain subscribed from one period to the next. If you begin the month with 10,000 subscribers and 9,500 are still active at the end of the month, your monthly Retention Rate is 95%.

The Upgrade Rate and Downgrade Rate measure how frequently subscribers move between pricing tiers. For example, if 200 out of 4,000 subscribers on the Basic or Standard plan upgrade to a higher-tier subscription within a month, the monthly Upgrade Rate is 5%.

4.5 Expiring subscriptions

Expiring subscriptions are subscriptions that have already been cancelled but remain active until the end of the current billing period. Although this stage is often overlooked, it can last for a surprisingly long time.

For example, a customer with an annual subscription may cancel on the very first day simply to avoid missing the cancellation deadline. Even though they have already submitted their cancellation, they remain an active subscriber for another 365 days. That also means you have 365 opportunities to convince them to stay. In many cases, a cancellation is not a final decision against the subscription but simply a precaution to avoid an unwanted renewal.

The Cancellation Rate measures the percentage of subscribers who submit a cancellation request during a given period. If 300 out of 10,000 active subscribers cancel within a month, the monthly Cancellation Rate is 3%.

The Cancellation Rate should not be confused with the Churn Rate. The two metrics often differ because a cancellation usually occurs well before the subscription actually ends.

For example, if a customer cancels in January but still has six months remaining on an annual subscription, they contribute to the Cancellation Rate in January but only enter the Churn Rate in June—provided they do not withdraw their cancellation beforehand.

In addition, the Churn Rate includes not only voluntary cancellations but also involuntary churn, such as failed payments or expired payment methods.

The Reactivation Rate measures how many subscribers reverse their cancellation before their subscription expires. If 30 out of 300 cancelling subscribers decide to stay before the end of their billing period, the Reactivation Rate is 10%.

Finally, the Save Rate measures the percentage of subscribers who begin the cancellation process but never complete it. In other words, it captures the cancellations that were successfully prevented before they were ever submitted.

4.6 Former subscribers

Once a subscription has expired, the customer becomes a former subscriber and the win-back process begins. Provided you still have permission to contact them, former subscribers can be reached through email, phone calls, push notifications, or other marketing channels with tailored offers and messages designed to encourage them to return.

From the perspective of the subscription funnel, former subscribers effectively become highly qualified leads again. Unlike new prospects, they already know your product, have experienced its value, and have demonstrated a willingness to pay in the past. As a result, win-back campaigns often achieve significantly higher conversion rates than campaigns targeting first-time subscribers.

As a subscription business matures, win-back becomes increasingly important because a growing share of the addressable market has already subscribed at least once. Over time, acquisition efforts naturally shift from attracting entirely new customers to re-engaging former ones.

For that reason, it is useful to measure how many people you are targeting have previously been subscribers. The Former Subscriber Rate measures the percentage of contacts—such as recipients of an email campaign or visitors reaching a paywall—who have held a subscription before.

This metric provides an indication of how frequently you are “fishing in the same pond.” While it is often impossible to identify former subscribers across third-party channels such as social media, logged-in users on your own website can usually be matched to their subscription history.

In some industries, particularly video streaming, customers regularly pause and restart their subscriptions depending on the content available. In these markets, cancellation is often not the end of the customer relationship but simply a temporary break.

The Win-Back Rate measures the percentage of former subscribers who return within a given period. For example, if 1,000 out of 5,000 former subscribers purchase another subscription within one year, the annual Win-Back Rate is 20%.

Viewed as a whole, the subscription funnel is not a linear process but a continuous cycle. Every former subscriber represents a potential future customer, making retention and reactivation just as important as acquiring new subscribers.

With a hard paywall leaving practically zero articles for free, Foreign Policy prioritizes low-effort, high-impact tactics, three of which were shared at Audiencers' Festival Montréal:
> Build one segmented "win-back" email, targeting lapsed-but-recent visitors
> Test an exit-intent registration wall instead of loosening your paywall
> Turn your best columnist into a short email course for readers who aren't ready to subscribe yet

The paywall is genuinely strict, and getting stricter

FP offers essentially no free content. Osnos was upfront that this is unusual – freemium is perhaps the most popular model in Europe, whilst in Canada a lot of content is freely accessible and many media are government supported. And their model has only gotten more restrictive over time. In 2018, the meter allowed around five free articles a month. Today it’s practically zero. Because there’s no ad revenue to fall back on, every article needs to justify its existence through subscription value.

Four problems sitting underneath that strategy

Osnos framed FP’s current position around four challenges, several of which will be familiar to most publishers reading:

• Top-of-funnel erosion. Organic discovery through Google search, historically a major channel, has dropped off significantly, even though FP isn’t chasing traffic.

• A demographic gap. FP’s core paying audience skews over 50. But it also has a large 18-to-23 segment, driven almost entirely by university group subscriptions. Those students are a meaningful exposure channel (Osnos says it’s one of the most common things she hears from subscribers she meets: “I used to read FP at university”), but they arrive through IP-authenticated access, meaning FP has no contact information for them, and loses nearly all of them the moment they graduate.

• High pricing on a strict meter. Because there’s no ad revenue, FP has to price for value and hold the line on access, which creates real friction for readers who aren’t ready to pay upfront.

• Rising competition in a moment that should otherwise favor FP. Geopolitics is dominating headlines, which sounds like a tailwind, but it also means FP is now competing directly with much larger outlets like The Washington Post and The New York Times for the same coverage. Osnos noted that FP used to see clear, isolated traffic and subscription spikes tied to major geopolitical moments (the clearest being the outbreak of the Russia-Ukraine war). More recent moments, including developments around Venezuela, have still moved the needle, but far less distinctly, because so many outlets are now covering the same stories simultaneously.

Given a small team (3 on the individual subscription side, 2 focused on group subs), Osnos’s operating principle is to prioritize low-effort, high-impact tactics, three of which she shared with us in Montréal: 

Win 1: The weekly trending digest

This is a weekly email combining a curated feed of articles, with marketing messaging at the top and bottom. Its effectiveness comes almost entirely from precise targeting and testing, not from the format itself.

Targeting: the email goes to users who visited the site in the last 30 days but haven’t visited in the last 7, a segment the team calls “Active 30, Dark 7.” These readers haven’t seen the last week’s stories, so the email surfaces what’s new rather than repeating content they may have already seen, and it re-engages them before they drift into a fully at-risk state. Readers still inside that 7-day window get more direct subscription-offer messaging instead, since they don’t need a content refresher.

Article selection: the team tested a blend of signals (last-touch conversion attribution, subscriber engagement time, and Apple News performance as a proxy for general news interest) against Sailthru’s personalization engine. Curated selection matched or outperformed the automated personalization engine consistently. Osnos’s read: curation still beats algorithmic personalization here, even though full automation would have been the lower-effort path.

Format specifics, tested directly: seven articles per edition, chosen after testing five, seven, and ten; seven won. The email always ends with an “end unit,” a final clickable item (a magazine issue, a new feature, a limited offer) so the reader has somewhere to go after the content rather than the email simply stopping. The top of the email is segmented into four different versions depending on who’s reading it, students and academics with .edu addresses see different pricing and messaging, former subscribers see a different version again, and existing subscribers never see price or offer messaging at all (they instead see messaging to reinforce sub benefits e.g. gift links, new issues, FP Live).

Effort and what’s next: the whole build takes under 30 minutes a week and consistently lands in FP’s top 10 monthly conversion sources (by campaign). The team is now testing an internally built AI tool that analyzes FP articles for conversion and subscriber-traffic performance and generates optimized headlines and decks, since the email leans almost entirely on headline and deck to pull readers back to the site.

Win 2: The exit-intent registration wall

FP has tested hard paywalls against softer meter strategies repeatedly, across every audience segment (known, unknown, newsletter subscribers, everyone), and hard paywalling consistently converts 5x better. That’s why 80% of FP’s traffic sees a hard paywall 100% of the time.

The remaining 20% is where the exit-intent wall comes in. When the system detects a reader about to leave the page (or swipe away on mobile) without paying, it offers a registration prompt instead: create a free account, get that one article. This avoids cannibalizing the primary hard-paywall conversion moment while still capturing readers who weren’t going to pay this time but are worth keeping in the funnel.

What happens after account creation matters as much as the wall itself. New registrants go through on-site onboarding and a structured nurture sequence: an explanation of why FP exists, a set of “greatest hits” articles with the paywall temporarily removed, a note from a subscriber-favorite columnist, and promotion of newsletters, which the team has found to be one of the strongest drivers of paid conversion among registered-but-not-subscribed readers, along with FP Live, FP’s video series. The average time from account creation to paid subscription across this flow is 14 days.

Win 3: Newsletter courses

FP’s first newsletter course, an introduction to core international relations theory, was launched in 2026 and authored by Stephen Walt, a Harvard professor and one of FP’s top-converting columnists (also featured in the onboarding nurture sequence above). The format is a five-part email series covering foundational IR concepts.

The logic behind it: geopolitics is increasingly relevant to people well outside FP’s usual readership, but without some grounding in the basics, a general reader has a hard time getting real value from FP’s actual coverage. The course is designed to meet a younger, less specialized audience where they are and bring them into FP’s orbit gradually.

In its first six weeks, the course drew roughly 9,500 signups. 40% of signups were net new to FP, meaning they’d never previously been in FP’s email system. Paid acquisition for the course is running at a $1 cost per lead, against FP’s normal average of roughly $3. These users are driven to the FP website rather than using an ad platform email capture, a strategy that may lead to higher CPLs but means higher quality leads.

The course also functions as a self-contained subscription funnel. Throughout its five parts, it embeds subscription messaging: “homework” assignments using gift links to relevant FP coverage, and promotion of specific benefits, like FP’s podcasts, that the team believes will resonate with a similar audience. Rather than offering a broad free trial that risks prompting cancellations among existing subscribers, FP built a narrower incentive: completing the course earns a 30-day free trial, available only to that specific, already-engaged cohort. So far, 18% of readers exposed to the trial offer go on to claim the trial.

Because the course is built once and requires no ongoing maintenance to keep running, it fits the same low-effort, high-impact principle as the other two tactics: a small team’s structural bet, built on the front end and left to keep converting on its own.

For any publisher weighing a stricter paywall against the traffic it might cost, Osnos's session is a useful reminder that the constraint didn't stop growth, it forced the team to continuously innovate and develop tactics precise enough to convert when article access can’t.

> Product decisions at most news organisations get made by whoever's loudest in the room, or by instinct built from experience. To overcome this, Germany's FUNKE Mediengruppe built a framework to replace that with something structured and evidence-led instead: a KPI tree

> Start with one metric at the top, not a dashboard. Funke picked Engaged Time, then broke it down layer by layer: what drives sessions, what drives active users, what drives new vs. returning. Each layer down gets more specific, until you hit something Stefan calls a movable metric, one a single product decision can actually shift

> Once you have even a partial tree, run a basic sensitivity check. Move two input variables by 5% each and see which one moves the KPI above it more. That tells you where to run your next sprint, not guesswork

> Only after the tree exists, build the org around it. Funke's four pillars (Reach, Engagement, Monetisation, Infrastructure) came directly from the tree's branches

> Don't start with the whole tree. Stefan's advice is to instrument one branch, show your team what it reveals, and let that build the internal case before you expand

How are product decisions actually made?

It is worth asking this question honestly, about your own organisation.

Is it the most senior person in the room? Is it instinct built from years of experience? Or is it different departments each pushing their own priorities, without a shared picture of what the product actually needs? Some news organisations have already built strong product cultures, where decisions stem from shared data and clear goals. For many others, the reality is messier.

The problem is not that any single input is wrong. The problem is the absence of a shared view, one where decisions are understood in relation to each other rather than evaluated in isolation. In practice, what often happens is that each team or department sees a part of the picture and acts on it. Everyone is doing something, but it does not click together, and a lot of value gets lost in the gaps.

When data is also missing from the equation, the risks compound. In product discussions about what to build next, maybe the loudest voice, the most confident person, or the most senior stakeholder gets their way. And maybe their suggestion is the right one. But without a shared framework to evaluate it against, there is a real chance that a lot of value gets lost. Hello, agency theory.

There is also a structural challenge specific to product development: new features are expected to have long-term impact, but evaluating that long-term impact after release is genuinely hard. Who hasn’t heard the famous “We simply have to implement Feature X, then in 6 months PV will have increased by xy%”. Too many things change between shipping a feature and having enough time to assess results. This makes it easy to keep moving by instinct, because instinct, in this environment, is rarely held to account.

So ultimately, the goal is to ground product decisions in evidence, not to take judgment out of the process.

Build the tree first

To solve this, the first thing we did was build a KPI tree.

For us as a news organisation, the metric at the top of that tree is Engaged Time, the total time users spend meaningfully interacting with content in our apps. Users choose to spend their time with us rather than somewhere else. The more intentionally they do that, the more value we deliver to them, and the more value we can generate commercially. When Engaged Time grows, the downstream indicators follow: ad impressions increase, subscription conversion improves, churn decreases.

Starting from Engaged Time, you break it down: what drives it? Session length and session frequency. What drives sessions? Active users. What drives active users? New users coming in, and existing users returning. How do new users arrive? Through different channels, direct, social, newsletter, search, each with its own conversion rate and return behaviour. How do existing users come back? Through habit, through push notifications, through content that gives them a reason to return tomorrow.

At each level of the tree, what you are really working with are ratios. How many visits convert to downloads? How many downloads become active users? How many active users encounter the paywall, and what share of those convert? Each ratio is a product decision waiting to be made. And there is something important about working with ratios rather than absolutes: it is easier to move five ratios by a small amount than to move one ratio by a large amount. The more levers you identify in the tree, the more opportunities you have to create meaningful impact.

The further down you go, the more granular the metrics become, and the closer you get to what we call movable metrics. These are metrics specific enough that a concrete product decision can actually shift them. You cannot ship a feature which directly increases Engaged Time. But you can ship a feature that improves how the homepage surfaces content, which changes the click-through rate to articles, which increases time in session, which moves Engaged Time. If you understand the chain, you know exactly what you are building toward.

Building the tree also means filling it with data. Some of it already exists. Some requires new tracking. The more granular you go, the more likely you will find instrumentation gaps. But as the picture fills in, something useful happens: you stop describing what the product produces and start understanding how it produces it.

The tree can also be filtered by user segment. The ratios look different for subscribers, registered users, and anonymous visitors. Understanding where those differences appear tells you where the most valuable product work is concentrated.

What the tree reveals

One of the most useful things a completed tree enables is simple calculation.

Once you have your first tree filled with data, even if only some branches, you can start to model the relationships between metrics. Take any KPI in the tree that is influenced by two variables below it. Increase each of those variables by five percent in isolation and see what happens to the KPI above. Which one has the bigger effect? A basic sensitivity analysis like this tells you quickly where the highest-leverage opportunities are in your product, and where effort is likely to be wasted.

Once you have identified a movable metric worth pursuing, the next question is how to actually move it. This is where mapping opportunities and solutions becomes important. For any given metric, there are usually multiple opportunities to influence it, and for each opportunity, multiple possible solutions. A structured approach, which opportunity has the highest potential, which solution is the most feasible, is what connects the diagnostic work of the KPI tree to actual product decisions. That process deserves its own deep dive, but it is the natural next step after the tree has done its job.

With that kind of visibility, prioritisation conversations change. Where should product investment go? What should marketing focus on? The tree does not make those decisions for you, but it makes the trade-offs visible. And visible trade-offs are easier to act on than invisible ones. That is the practical value: better prioritisation, and therefore better return on the investments you are already making.

A concrete example: once the tree was in place, we started observing new users as a specific segment. Sessions and page views among this group were dropping off within the first 30 days, pointing to a retention problem the aggregate numbers had been masking. Looking at what differentiated users who stayed from those who did not, the data pointed clearly to push notification subscription as a key factor. Push subscription rate during onboarding became our movable metric for this branch of the tree. We ran a series of A/B tests across the onboarding funnel, which increased push subscribers as a leading indicator, and significantly grew engaged time for this user segment, resulting in a higher 30-day retention rate as the lagging indicator.

From tree to organisation

Once the KPI tree was in place, the structure of the team followed naturally from it.

The tree has distinct branches, and those branches became four operational pillars:

Reach covers everything connected to bringing new users into the app and converting existing web readers into app users. App store presence, referral channel performance, cross-platform conversion. Reach asks: how do we grow the active user base?

Engagement takes over once a user is inside the app. Its mandate is habit formation: building the product and editorial conditions under which users return regularly and spend meaningful time. Onboarding, notification strategy, content personalisation, homepage design. Engagement asks: how do we make the app worth coming back to?

Monetisation is the commercial result of Reach and Engagement doing their jobs well. Ad revenue, subscription conversion, ARPU. Monetisation asks: how do we convert engaged attention into sustainable revenue?

Infrastructure is the supporting pillar: technical stability, data pipelines, analytics instrumentation. Without it, the other three pillars cannot move with speed or confidence. Infrastructure asks: are the foundations strong enough to build on?

And beneath all four pillars sits journalism, not as a pillar but as the foundation. Great editorial content influences all four. It drives Reach through word of mouth and search. It drives Engagement through loyalty. It drives Monetisation through willingness to pay. It makes Infrastructure worth investing in. The product framework serves the journalism, not the other way around.

The four pillars themselves are not a new idea. What matters is what sits beneath them: clear ownership, defined KPI sets, and the mandate for each team to break those KPIs further down within their branch of the tree. Downloads is a Reach KPI. But how are downloads generated? Through app store visits and the download conversion rate. Which of those can be moved? That is where the actual product work begins.

The pillars are independent in ownership but interdependent in practice. Reach without Engagement produces churn. Engagement without Monetisation produces a great product that does not sustain itself. A decision in one pillar usually affects the others.

Working together across pillars

Having clear ownership per pillar solves one problem. It creates another: how do you keep four teams, each focused on their own metrics, moving in the same direction?

This is where the organisational question becomes as important as the product question. Each pillar needs to understand what the others are working on, how prioritisation decisions are being made, and how a new feature or product change in one area will affect the others. Without that shared understanding, you end up with well-run silos rather than a well-run product.

What we built is a cross-pillar structure where all relevant stakeholders, from editorial and data to advertising, subscriptions, and tech, sit down together with the same data in front of them. Each pillar shares its learnings, its priorities, and its dependencies. Where one pillar needs something from another to move forward, that gets named and resolved together.

The goal is not process for its own sake. The goal is to get genuinely data-oriented as a group, not just in individual teams, but across the whole organisation. When everyone is looking at the same KPI tree and asking the same questions about what is moving and why, the conversation shifts. It becomes less about opinions and more about what the numbers are actually showing.

That shift is harder to achieve than it sounds. But it is where the real value of the framework sits.

A new way to think about what comes next

The KPI tree has changed how we make product decisions. The next opportunity is to apply the same thinking to strategic planning.

A user-centric planning approach starts with an understanding of how users move through the product: where they drop off, where they convert, and what drives them to return. Leading indicators first, active users, retention rates, engagement depth, push notification reach. The lagging indicators, including revenue, follow from those.

A subscriber target becomes meaningful when it is anchored to retention rate assumptions, conversion rate assumptions, and active user trends. A combination of leading and lagging indicators, connected through the KPI tree, gives every team a clear view of which part of the tree they are responsible for moving and how their work connects to the overall goal.

But the KPI tree also points toward something bigger. Every data point collected across all KPIs is a training signal. The logical next step is a statistical or AI-driven model that operates on top of the tree and surfaces the highest-leverage actions automatically. Imagine a system that tells you: sending four percent more push notifications related to sport, at 4:30pm, has a 78 percent probability of increasing MAU by two percent, which flows through to a 1.5 percent revenue effect. (Numbers are illustrative to get the point across.) The tree helps you understand your product and it can become the foundation for a system that actively tells you where to act next.

Even if we are not fully there yet, the tree gives us the language and the structure to get there.

Where to start

If you are thinking about building something similar, start with the first draft of the tree.

Start with one branch, not the whole tree. Instrument what you can, show your team what it reveals, and let the results build internal confidence in the approach. The framework earns trust the same way any good product does: by demonstrating value before asking for full commitment. Then expand.

It does not have to be complete. It will not be. Gaps in tracking will appear. Assumptions will turn out to be wrong. Metrics you thought were independent will prove to be connected. Correlation is not causation.

That is the process, not a problem with it.

The value of the tree is not in its perfection. It is in the discipline of building it, because building it forces you to ask, at every level, the question that product decisions too often skip: what needs to happen for this metric to change?

Ask that consistently. Break each number down until you find something specific enough to act on.

And when you find it, build toward that.

> The Observer launched its first-ever digital subscription in November 2025 at £16 a month or £144 a year, with a single umbrella tier covering print, digital, audio and Culture Club benefits from spring this year.
> Culture Club, a set of arts and culture perks worth more than £800, is given to every subscriber instead of being held back for a premium tier.
> Early data shows subscribers who engage with multiple parts of the product, from Nigel Slater's recipes to the puzzles to podcasts, are significantly less likely to cancel.
> The Salt Path investigation and its podcast and documentary afterlife have been the single biggest growth catalyst since launch.

Lessons:
> A single, transparent subscription can beat early tiering when you are reintroducing a brand to its audience.
> Retention comes from breadth of engagement across a product, not from any one flagship story.
> Old brand equity can bridge readers into new daily habits, but only if the product is built to earn that habit.

Why there are no tiers

Where many publishers reach for tiers early, The Observer launched with a single umbrella subscription covering print, digital, audio and now, Culture Club (see below). “We wanted the subscription to be simple to understand, great value for money and comprehensive,” Riley says. Reintroducing a heritage brand to an audience that may not be familiar with it, or has never encountered it digitally at all, is not the moment to ask people to choose between packages.

A separate audio-only subscription, a legacy of the Tortoise audio model, exists through Apple Podcasts and Spotify for readers who want nothing else, and there is real cross-pollination between formats. But the umbrella model is deliberate: with only six months of data, Riley says tiering decisions now would rest on very little evidence. Simplicity was the safer bet, leaving room to see where the value lands before carving up the product.

Culture Club, for every subscriber

The Observer’s most visible product launch since the initial rollout is Culture Club, a set of arts and culture benefits bundled into every subscription: two-for-one tickets to the National Gallery, exclusive cinema screenings with directors, author events and book clubs held in the newsroom, and discounted theatre tickets. “It’s your cultural life, curated,” is how Riley describes it.

Rather than a separate product built for a distinct audience, Culture Club is included in the standard subscription and goes to every reader who pays for it, with no separate tier. Riley frames it as adding significant partner benefits to those that The Observer was already quietly offering, like giving a 70% discount on home cinema memberships through their partner MUBI and turning them into a coherent proposition tied to the brand’s editorial identity. Arts and culture were the deliberate focus rather than, say, food or travel: Riley sees it as a standout interest for Observer audiences that other subscription products in the market have overlooked. The commercial logic is retention as much as acquisition: subscribers who attend an event or use a benefit build a tangible relationship with the brand that a login alone cannot create.

Riley traces the conviction to the i newspaper, where he launched reader events and saw that most people find news organisations distant and faintly mysterious right up until they are sitting in a room talking to a journalist. Subscribers who have had that kind of experience with a brand, in his experience, are simply more likely to stay, which is the logic Culture Club now builds into the subscription itself.

Pricing without the tricks

The Observer priced its subscription at £16 a month or £144 a year, deliberately avoiding 99p-style pricing. “That was part of just trying to be really clear about what we think the value is of the work that we’re doing,” Riley says. An under-35 price point at 50% off acknowledges that younger readers are often priced out of premium subscriptions, with 35 chosen as a deliberate life-stage threshold.

The Observer has no obvious competitor to benchmark against. The Guardian’s UK voluntary model and the Times’ hard paywall represent decades of pricing evolution aimed largely at winning back or re-engaging audiences a mature business has already exhausted. The Observer has no such legacy to correct for, which Riley treats as an advantage: the headline price can reflect where the business is now, without unwinding years of promotional pricing.

What’s driving retention

Six months in, Riley says the clearest signal in the data is breadth of engagement. Subscribers who touch multiple parts of the product, reading Nigel Slater’s recipes, doing the crossword and listening to a podcast, are significantly less likely to cancel than those who arrived for one thing and never explored further. Because the product is still young, many subscribers do not yet know everything they have access to.

That is why subscriber messaging pushes Culture Club so hard: highlighting more than £800 in available benefits is a fast way to demonstrate value to someone who subscribed for a single podcast series before they reach a cancellation decision. The Observer has also seen a healthier-than-expected skew towards annual plans, which Riley reads as an early show of faith, buying time to build a relationship before the first renewal.

The Salt Path’s second life

The Chloe Hadjimatheou investigation into the bestselling memoir The Salt Path was a hit before the subscription even existed, driving millions of readers to the open-access site last summer and helping build the registration base the launch depended on. In January, a narrative podcast series built on the investigation became, in Riley’s words, the biggest catalyst for subscriber growth in the first few months after launch, driving uptake in both the standalone audio subscription and the full subscription that includes it. A Sky documentary over Christmas had extended the story’s reach further. A new Hadjimatheou series, We Call Her Emma, has just been released, an investigation focusing on the extraordinary rise of Asma al-Assad from West London girl to the heart of Syria’s brutal dictatorship: the next test of whether a story that brings subscribers in at scale can hand them on to the rest of the product.

Building fast without the legacy costs

The Observer’s product team has moved almost entirely to an agentic coding approach, using AI tools to handle the bulk of feature development. A small team of engineers from an outside agency works alongside an in-house tech lead and product manager. Claude writes most of the code for new features, while the engineers concentrate on harder technical problems and on testing and quality assurance, checking that the output does what it was meant to. The approach lets a young, lean organisation compete with newsrooms that have far larger legacy technology teams, freeing more of the business’s resources for journalism itself.

Riley applies the same instinct himself. After seeing a story-support widget demonstrated by a US publishers’ collective at the recent Audiencers Festival in London, he built a rough version of it within an afternoon, not to launch it but to show his own team the idea. Prototyping, he says, has become quick enough that showing is often faster than telling.

On the harder question of AI companies and publisher content, Riley is careful not to stake out a fixed position. The Observer has partnered with Particle News, an AI-powered aggregation app, as its first UK publisher, and Riley points to Reuters Institute research showing a growing share of global news journeys now beginning inside a chatbot as a signal publishers cannot ignore, whatever position they eventually take on direct deals versus industry coalitions.

The hardest part isn’t the technology

Asked what has been harder than expected, Riley doesn’t hesitate: discipline. A brand this old, with this much editorial breadth, invites endless extensions: more tiers, more products, more features, especially now that the barrier to building any of them has collapsed.

“When Claude can build you a recipe site in an afternoon, you have to ask yourself: is that really what we want to build?”

Riley has previously cited The Atlantic’s decade-long path to a million subscribers as a realistic model for the kind of timeline this takes. His ambition for The Observer is to build a sustainably profitable media business on reader revenue and other income streams, and he argues that doing so without the legacy cost base of an older company changes the calculation. He won’t share subscriber numbers this early. Six months in, he says, The Observer is on track. There is, by his own admission, still a long way to go.

Jack Riley is Chief Customer Officer at The Observer, where he leads customer revenue strategy across subscription growth, marketing, data and product. He joined in 2025 from The London Standard, where he was Chief Digital Officer, and previously led Huffington Post’s turnaround to profitability as Managing Director. The Observer is owned by Tortoise Media.

The Guardian doesn't have a paywall, anyone can read it, whether they pay or not. So the 1.4 million people who choose to give money anyway aren't paying for access, they're paying for something else entirely

> Ownership is the product: The organisation's value proposition comes down to three words - global, independent, free. Owned by the Scott Trust, their sole purpose is to ensure The Guardian can keep publishing. It's this that's sold to readers

> One email, built entirely around that pitch, generated $2 million. When The Washington Post and LA Times pulled their 2024 election endorsements, The Guardian sent readers a simple message - we published ours, and always will, because no billionaire can tell us not to

> But it's the method that's worth noting rather than the moment: The Guardian surveys readers right after they give, with the goal of understanding the why. The top answers include protecting the free press, editorial independence, or the journalism itself

> These surfaced motivations don't just become a slide that's presented once to the team, they're used to build every single message that asks for support. They keep telling the story, deliberately and repeatedly

The starting point: ownership as the product

The Guardian was founded just over 200 years ago as The Manchester Guardian, a local UK paper. It’s now the fifth most visited news site in the world, pulling in roughly a billion page views a month. Its US team is small, about six people, working alongside a much larger marketing and reader revenue team of around 90 people at the London HQ.

The organization’s value proposition, as Harkin frames it, comes down to three words: global, independent, free. The independence part is structural, not just marketing language. The Guardian has no billionaire owner. It’s owned by the Scott Trust, established 90 years ago with a single purpose: ensure The Guardian can keep publishing in perpetuity. The Trust isn’t built to generate returns for shareholders. It exists to keep funding journalism.

That structure becomes the actual product sold to readers, not just backstory.

Ownership isn’t just a backstory

In the lead-up to the 2024 US election, both The Washington Post and the LA Times pulled their presidential endorsements, reportedly at the direction of their billionaire owners. Inside The Guardian, an editor suggested sending readers a simple message: we published our endorsement, and we always will, because no billionaire can tell us not to.

That email went out to The Guardian’s list. It generated two million dollars.

Harkin described it as one of those moments where you assume your analytics dashboard is broken, because the spike looks impossible for a normal day. What it confirmed for her team was that US readers are far more media-literate about ownership structures than publishers often give them credit for. People understood exactly what billionaire ownership can do to editorial decisions, because they’d just watched it happen at two major outlets, and they responded to a publication that structurally couldn’t be pressured the same way.

What people say when you ask them why they paid

The Guardian surveys readers immediately after they support the organization, while the motivation is still fresh. The consistent, top-ranked answers: protect the free press, protect editorial independence, protect the journalism itself. Further down the list, at roughly position six, is a motivation specific to The Guardian’s model: keeping the journalism free and open for everyone, not paywalled.

Further down still, in positions eleven through fourteen, is a newer and growing motivation: dissatisfaction with other media sources. Harkin ties this directly to visible cases of ownership interference, citing Jeff Bezos later restricting which topics The Washington Post’s opinion pages were authorized to cover. Readers notice, and it shows up in what they tell you when they give.

How this research becomes the actual email copy

The endorsement email wasn’t written as an abstract mission statement. It was built, deliberately, around the specific motivations the research had already surfaced, worded so it read as natural rather than like a fundraising checklist:

• Dissatisfied with other media: named exactly what The Washington Post and LA Times did, and what The Guardian did instead
• Wants editorial independence protected: explained the Scott Trust ownership model in plain terms
• Wants work that holds power to account: made clear that only the editor-in-chief, never a business owner, decides what gets published
• Wants to protect the free press: the direct ask

Harkin’s point in walking through this line by line: the research isn’t a slide you present once internally and then forget. It’s the literal structure of the copy you send.

The revenue mechanics underneath it

Readers who want to support The Guardian financially see three recurring options: a five-dollar monthly contribution, a fifteen-dollar tier called Supporter Plus that comes with added benefits, and a higher Digital Plus tier with more on top. There’s also a one-time support option and a recently launched student discount.

Alongside the main organization sits theguardian.org, a registered nonprofit. Harkin pointed to US philanthropic culture, Americans give roughly half a trillion dollars a year to causes, ranging from small one-off donations to major gifts, as a real reason this structure matters specifically in the US market, even though The Guardian itself isn’t a nonprofit. The motivations that drive nonprofit giving (mission alignment, wanting to sustain something you believe should exist) map closely onto why people choose to pay The Guardian.

The Guardian currently has 1.4 million digital subscribers. The UK has the largest paid supporter base, but North America, US and Canada combined, is the fastest-growing region, now at 14% of the base.

The takeaway

Her closing point applies well beyond publications without a paywall: figure out the full range of motivations and emotional connections your audience has with your organization, not just the functional value proposition of “you get access to the app.” Then keep telling that story, deliberately and repeatedly, across your marketing rather than assuming people already know it.

For The Guardian, that story is ownership. For another publication, it might be something else entirely, a specific beat, a founding mission, a community it serves. The method Harkin described, survey people right after they convert while the reason is still fresh, then build your actual marketing copy around what they tell you, works regardless of what that story turns out to be.

> According to OpinionWay, the average French person consumes about 6 media families a day, 20% already use a generative AI to get informed, but a majority say they feel overwhelmed, even fatigued, by the news

> Faced with information fatigue, unlimited access is not the answer. Les Echos is instead making the opposite bet, that of selection

> "La Sélection" consists of between 9 and 15 articles a day, chosen from a daily output of 120 to 150 pieces, following a reader-needs grid (inform, reflect, get inspired, develop, unwind) and a strict quota discipline

> Three platforms (a dedicated tab in the app, a section on the site, a daily newsletter), a weekly long read on Saturdays, and 5 shareable articles a month. Early bird price sits at €9.90 a month

Presented in the opening by Célia Pénavaire, the title’s values break down into three guiding axes for this selection: reason over ideology (an economic DNA that calls for a rational, almost mathematical reading of the world), optimism over fatalism (giving room to success stories and to solutions that work), and ambition over declinism (investigations and analysis to handle professional and personal challenges).

On the production side, it is a genuine editorial discipline, run by a dedicated team (two full-time journalists, according to our information). Each day, the newsroom produces between 120 and 150 articles; this team selects 9 to 15 of them, spread across a reader-needs grid (inform, reflect, get inspired, develop, unwind) with fixed quotas per category, several times a day. Concretely, “develop” accounts for around 20% of topics, while “get inspired” and “unwind” are capped at 10% each. A culture piece or a roundup of the best summer crime novels thus has its place alongside the conflict in the Middle East.

Three platforms, a weekly long read, and sharing

“La Sélection” is designed to be identifiable on the three most consulted platforms: a dedicated tab in the app (in the form of immersive cards), a section of the same name on the Les Echos site, and a daily newsletter in your inbox (at 8:30am, signed by the newsroom). On the app, choosing your interests unlocks additional articles; on the site, subscribers can access the full history of past selections. All with some personalisation, but deliberately limited, to preserve a common core shared by all subscribers. On top of that, every Saturday morning, an exclusive long read looks back on the week’s key events, signed by the editors-in-chief Christophe Jakubyszyn and Clémence Lemaistre. And because information is meant to be shared, the offer includes 5 articles to share freely with those close to you each month.

Pricing: a deliberately accessible positioning

Conceived as a daily intellectual companion, the offer is meant to be accessible to as many people as possible, and gives access only to this daily selection (site, app and newsletter). The early bird price is €9.90 a month. Yasmine Maslouhi claimed a positioning “cheaper than Canal+, cheaper than Netflix, and even cheaper than Le Monde today”. A special VivaTech offer was available on the stand: two months free. Note that the AI assistant for professional use was presented right next door, on the same stand.

To subscribe to La Sélection, it’s here. See you in a few months for the first results…

> When you start testing value props and benefits, it's easy to mix and match features, and try to cram everything onto one page to make subscription "worth the cost". But research has proven that the biggest driver of loyalty isn't usually price or feature count. It's a sense of uniqueness, something the reader couldn't get anywhere else

> Your team can answer this easily, but the real value comes from asking the same questions of the people you're trying to reach. At a minimum, show your prototype to one more person than has seen it already

> Once you know your differentiation, packaging decisions get easier. Rachel's 3-question test before bundling anything: does it strengthen or dilute each product's identity? Are the audiences actually converging? Can your ops hold it together without the seams showing?

> Sometimes the research tells you to do nothing. One of Skift's four products stayed untouched, on purpose, and it's now one of their steadiest, best growing subscriptions

The exercise: fill in the blank

To find that sense of uniqueness, Goligoski runs newsroom leaders through simple prompts about their organizations:

• First in the subject, region, or world to ___
• Best compared to competitors in ___
• Only organization to ___

The exercise surfaces an origin story fast. But it’s only half the picture, and it’s the easy half — anyone can answer these questions for themselves around a conference table. The real value comes from asking the same questions of the people you’re trying to reach, who often can’t name your staff or your specific value prop but can place you loosely (“oh, that’s the one about the business of fashion”). The gap between the two answer sets is the actual work. It tells you what you think differentiates you and what has actually landed.

Her rule of thumb for this kind of testing: n+1 is better than n. At a minimum, show your prototype to one more person than has seen it already. You’ll walk away smarter from even one conversation, and Goligoski says fifteen years into doing this work, people still thank her for simply being asked for their perspectives.

But watch out for “feature soup.” When you start testing value props and benefits, it’s easy to try to cram everything onto one page or into one pitch. If a first-time visitor needs a magnifying glass to understand what they’re being offered, you’ve already lost the differentiation you were trying to build.

A few examples she pointed to of publishers getting specificity right:

• Caper, a New York food media outlet, prices its annual subscription against hyper-local reference points: “less than a burrata pizza slice at L’Industrie, a potato pancake at Veselka” instead of the generic “less than a cup of coffee a day.” It grounds the price and quietly reminds readers how many small recurring charges they’re already carrying.

• The New York Review of Books and The Paris Review have a once-a-year summer bundle offer for two publications with possible audience overlap and growth potential, a financially compelling deal rather than a permanent merge.
• Capital B, a Black-media outlet in the US, sent an anniversary email that included an actual screenshot of the text exchange between its two co-founders deciding to launch. It reads as human in a way most subscription marketing doesn’t.

Goligoski’s closing asks for anyone doing this work: 

• Limit friction wherever you find it
• Take a less-is-more approach to any data you collect (only ask what you’ll actually act on)
• Keep a running, visible wishlist of the features and coverage areas you hear people ask for. That list becomes a genuine insight bank over time.

The Skift case study: is your product an audience or a feature?

Mines joined Skift, a B2B travel media and events company, two years ago and inherited what she called “a family I didn’t plan for”: four separate subscription products, none designed to sit together.

• Skift Pro: always-on travel news, home-grown, positioned as “the Bloomberg of travel”
• Skift Research: long-form, data-driven reports, also home-grown, aimed at strategy and analytics buyers making a major decision rather than staying informed daily
• Airline Weekly: a roughly 20-year-old acquired product, once faxed, now a newsletter with its own site, read closely by aviation executives (Delta CEO Ed Bastian has called it “the only thing I read every week”)
• Daily Lodging Report: a similarly old acquisition, a daily digest for hospitality and real-estate operators

Three questions before you package anything

1. Identity: does combining these products strengthen each one’s core value, or dilute it?
2. Audience: are these audiences actually growing toward each other, or are they deliberately separate?
3. Operations: can your UX, billing, and support genuinely hold a bundle together, or will the seams show? Mines runs subscriptions with a five-person team, a small product team, and a small design team, capacity is a real constraint.

Applying these questions to the Skift context

Airline Weekly: bundled the content, not the experience. Skift already had aviation coverage in both Pro and Research, plus an aviation conference. The instinct was to fold Airline Weekly’s coverage into all of it. But the products stayed on separate platforms — readers had to hop between a newsletter, a website, and (for a much smaller group) a conference ticket. Layering content across products without integrating the actual user experience just produced a disjointed one. Nobody complained loudly about it; it showed up quietly instead, in renewal numbers drifting down. 

Mines’ takeaway: audit the identity of what you’re bundling before you bundle it. Packaging without UX clarity is just confusion with a price tag.

Daily Lodging Report: the right move was nothing. This subscriber base — Mines described them candidly as mostly finance and real-estate professionals — wanted exactly one thing: the digest, in their inbox, undisturbed. Skift gave the product a new site and new data tools anyway. The response was, in effect, I don’t care, just give me the newsletter. 

So, they left it alone, and it’s remained one of their steadiest, best-growing products. Leaving a product untouched is a strategic decision, not a lack of ambition. Some products’ value comes directly from their constraints.

Pro + Research: complementary, not interchangeable. These two live in the same sales conversation but serve different budgets and different personas — daily information versus decision-support research. Combining them into one package would have devalued Research and bloated Pro. Skift’s framing: they don’t need the same package, they need the same conversation.

Mines’ shorthand for thinking about all of this is a marriage metaphor: some products should merge households (full integration makes both better); some should keep separate addresses (related, committed, but each keeps its own front door); some need couples therapy first (real potential, but only after the UX and integration work happens); and some are simply happy as they are, and the kindest, smartest move is to leave them alone.

From the Q&A: a few things worth stealing

Don’t let a new feature justify a price increase — check whether anyone asked for it first. When Skift acquired the Women Leading Travel membership group, the team raised prices and then went looking for features to justify the increase — a research report, an add-on. Mines stopped that process to ask a more basic question: did any of these members actually want the research report? They hadn’t. What they wanted was networking and job connections, and that’s where Skift redirected. Goligoski added a comparable example: ProPublica offers a branded t-shirt only after someone donates, framed as a thank-you rather than a subscription perk — about 17% of donors take it, self-selecting into people who’ll actually wear it and become visible advocates, rather than shipping merchandise nobody asked for.

Test new features free before you charge for them. Goligoski’s suggestion for the free-versus-paid feature question: launch new features free first, watch uptake, get people to describe the value in their own words, and work out the rough edges before you decide whether it becomes a paid add-on or a built-in part of the product.

When you research your gap between positioning and perceived value, don’t blend your audiences. Talk to loyal long-term subscribers, low-frequency readers, and non-subscribers separately, and be explicit — internally — about exactly who any given finding came from. Self-reported research also goes stale fast, so treat it as something to refresh regularly rather than a one-time study you cite for years.

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The takeaway to carry into your next packaging conversation: don’t start with pricing, and don’t start with the bundle itself. Start with audience needs and wants, including the friction points people tell you about. The best package isn’t the one with the most crammed into it — it’s the one your subscriber would actually notice if it disappeared.