Paywall Conversion Signals

Paywall Conversion Signals

Benchmark pricing, trials & friction across outlets — and understand what truly drives subscriber revenue.

Benchmark pricing, trials & friction across outlets — and understand what truly drives subscriber revenue.

Why this matters

Why this matters

Digital news outlets rely on subscriptions, but pricing, trial paths, and paywalls vary widely by country. Traditional benchmarks are fragmented, often anecdotal, and miss the link between model, subscriber base, and revenue.

This segment standardizes outlet data across geographies: paywall type, trial availability, pricing tiers, conversion friction, and estimated subscriber revenue. Each field is aligned to a common taxonomy, scored for confidence, and ready for strategic or operational use.

How Starzdata solves this

How Starzdata solves this

  • Normalize outlets and domains with standardized taxonomy.

  • Enrich with paywall type, trial, pricing tiers, and subscriber base.

  • Add friction score and comments to explain conversion barriers.

  • Model revenues with transparent rules, FX-normalized.

  • Provide confidence scores per field, source, and method.

This segment is activated with a blend of trusted sources and your own inputs

AI reasoning

Curated APIs

Web intelligence

What you get:

What you get:

  • Comparable paywall and subscription data across markets.

  • Transparent pricing tiers in local and normalized USD.

  • Subscriber and revenue estimates with confidence scoring.

  • Friction scores to compare onboarding experiences.

Your benchmarks, structured and decision-ready.

Sample data for this segment

#outlet nameoutlet name confidenceprimary domainprimary domain confidencegeo countrygeo country confidencepaywall typepaywall type confidencetrial availabletrial available confidencesubscription currencysubscription currency confidencesubscription price min localsubscription price min local confidencesubscription price max localsubscription price max local confidencesubscription price median localsubscription price median local confidencesubscription price median usdsubscription price median usd confidenceconversion friction scoreconversion friction score confidenceconversion friction commentconversion friction comment confidenceactive paid subscribersactive paid subscribers confidenceestimated subscription revenue monthlyestimated subscription revenue monthly confidenceregulatory contextregulatory context confidence
1The New York Times99%nytimes.com99%US99%metered96%true96%USD99%9.9997%29.9996%15.9997%15.9997%3592%Account creation + card before trial; 2 email step...85%950000080%15180000078%No specific federal constraints on paywalls.85%
2The Times UK98%thetimes.co.uk99%UK99%hard97%97%GBP99%2695%3895%3195%39.394%4891%No trial; multiple verification screens; limited p...84%45000070%1395000072%No paywall constraints; consumer fairness rules ap...88%
3Le Monde98%lemonde.fr99%FR99%metered96%true95%EUR99%7.9996%19.9996%11.9996%13.295%3292%Trial available; card capture after paywall; clear...85%55000075%659450075%France encourages free crisis info; no general ban...86%
4El País97%elpais.com99%ES99%freemium94%true95%EUR99%895%1895%1295%13.295%2891%Straightforward flow; Apple/Google Pay supported.84%30000070%360000072%No specific paywall limits.85%
5The Hindu97%thehindu.com99%IN99%freemium95%95%INR99%9995%19995%14995%1.894%4291%Multiple OTP steps; limited wallets; no trial.84%22000065%3278000070%No national restrictions on digital paywalls.84%
6Folha de São Paulo97%folha.uol.com.br99%BR99%metered95%true95%BRL99%24.995%49.995%34.995%794%3892%Requires CPF; payment form lengthy; trial present.84%35000070%1221500072%No paywall restrictions.85%
7The Australian97%theaustralian.com.au99%AU99%hard96%96%AUD99%2896%3996%3396%21.894%5091%No trial; forced card; newsletter opt-in default o...83%30000065%990000070%No material constraints on paywalls.85%
8Asahi Shimbun97%asahi.com99%JP99%freemium94%95%JPY99%280095%480095%380095%26.594%3791%Clean flow; domestic cards preferred; no trial.84%60000070%228000000072%No formal limits; consumer protection applies.85%
9South China Morning Post97%scmp.com99%HK99%metered95%true95%HKD99%19895%32895%29895%38.194%4192%Account + card; optional phone; clear pricing ladd...84%18000065%5364000070%Unrestricted digital paywalls.85%
10Mail & Guardian97%mg.co.za99%ZA99%freemium94%true95%ZAR99%4995%9995%6995%3.894%4691%Third-party gateway; mobile UX inconsistent; trial...84%8500060%586500068%No formal constraints.84%
Showing 1 to 10 of 11 entries • Click row for details

Each row = one outlet. Columns show:

  • Identity: outlet name, domain, country.

  • Paywall & Pricing: type, trial availability, min/max/median price (local + USD).

  • Conversion friction: numeric score (0–100) plus short explanatory comment.

  • Subscribers & Revenue: modeled estimates for active paid users and monthly revenue.

  • Regulatory context: notes on local rules.
    Every enriched field includes a confidence % based on source availability, freshness, and methods.

Your questions on this segment, answered

What about DIY scraping or internal tracking?

What about DIY scraping or internal tracking?

What about DIY scraping or internal tracking?

How does this compare to analyst reports?

How does this compare to analyst reports?

How does this compare to analyst reports?

Can I request additional outlets or geographies?

Can I request additional outlets or geographies?

Can I request additional outlets or geographies?

How do you model subscriber revenue?

How do you model subscriber revenue?

How do you model subscriber revenue?

Do you include free or ad-funded outlets?

Do you include free or ad-funded outlets?

Do you include free or ad-funded outlets?

How is the conversion friction score calculated?

How is the conversion friction score calculated?

How is the conversion friction score calculated?

Can I use this for market sizing and benchmarking?

Can I use this for market sizing and benchmarking?

Can I use this for market sizing and benchmarking?

What makes this dataset reliable?

What makes this dataset reliable?

What makes this dataset reliable?

How often is the paywall dataset refreshed?

How often is the paywall dataset refreshed?

How often is the paywall dataset refreshed?

Your questions on this segment, answered

What about DIY scraping or internal tracking?

DIY scraping gives control but is hard to maintain, inconsistent, and not standardized across markets.

How does this compare to analyst reports?

Analyst reports give useful trends, but are often high-level, slower, and not outlet-level with confidence scoring.

Can I request additional outlets or geographies?

Yes, custom extracts can be generated on demand with the same taxonomy and scoring.

How do you model subscriber revenue?

It’s estimated as median subscription price × active subscribers, adjusted if discounts are known.

Do you include free or ad-funded outlets?

Yes, they are included with “none” as the paywall type.

How is the conversion friction score calculated?

It combines onboarding steps, trial design, and payment options, explained with a short note.

Can I use this for market sizing and benchmarking?

Yes, it provides standardized pricing, subscriber, and revenue data across markets.

What makes this dataset reliable?

Each field carries a confidence score based on source availability, freshness, and methods.

How often is the paywall dataset refreshed?

Updates run monthly or on-demand, depending on outlet changes.

{ "_meta": { "dictionaryColumns": ["Variable", "Data_Type", "Sample_Value", "Description"] }, "data": [ { "Variable": "outlet_name", "Description": "News outlet name", "Business_Rules": "Standardized, no duplicates", "Source_System": "Curated Listings", "Data_Type": "VARCHAR", "Sample_Value": "The New York Times" }, { "Variable": "primary_domain", "Description": "Primary domain for the outlet", "Business_Rules": "Lowercase, no trailing slash", "Source_System": "Web Intelligence", "Data_Type": "VARCHAR", "Sample_Value": "nytimes.com" }, { "Variable": "geo_country", "Description": "Country of operation", "Business_Rules": "ISO 3166 alpha-2 or name", "Source_System": "Web Intelligence", "Data_Type": "VARCHAR", "Sample_Value": "US" }, { "Variable": "paywall_type", "Description": "Paywall classification", "Business_Rules": "ENUM: hard|metered|freemium|none", "Source_System": "Web Intelligence + AI Reasoning", "Data_Type": "ENUM", "Sample_Value": "metered" }, { "Variable": "trial_available", "Description": "Whether free trial is offered", "Business_Rules": "BOOLEAN true/false", "Source_System": "Web Intelligence", "Data_Type": "BOOLEAN", "Sample_Value": "true" }, { "Variable": "subscription_currency", "Description": "Currency of pricing", "Business_Rules": "ISO 4217", "Source_System": "Web Intelligence", "Data_Type": "VARCHAR", "Sample_Value": "USD" }, { "Variable": "subscription_price_min_local", "Description": "Minimum monthly price tier (local currency)", "Business_Rules": "Decimal >=0; exclude temporary promos if unclear", "Source_System": "Web Intelligence", "Data_Type": "DECIMAL", "Sample_Value": "9.99" }, { "Variable": "subscription_price_max_local", "Description": "Maximum monthly price tier (local currency)", "Business_Rules": "Decimal >= min; highest regularly available tier", "Source_System": "Web Intelligence", "Data_Type": "DECIMAL", "Sample_Value": "29.99" }, { "Variable": "subscription_price_median_local", "Description": "Median monthly price across tiers (local currency)", "Business_Rules": "Median of active tiers; exclude enterprise/bundles", "Source_System": "AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "15.99" }, { "Variable": "subscription_price_median_usd", "Description": "Median price normalized to USD", "Business_Rules": "FX-normalized to analysis date", "Source_System": "AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "15.99" }, { "Variable": "conversion_friction_score", "Description": "Composite score of onboarding friction", "Business_Rules": "INTEGER 0–100 (higher = more friction)", "Source_System": "AI Reasoning", "Data_Type": "INTEGER", "Sample_Value": "40" }, { "Variable": "conversion_friction_comment", "Description": "Short note explaining friction drivers", "Business_Rules": "One line; cites main blockers (e.g., forced app, card-first)", "Source_System": "AI Reasoning", "Data_Type": "VARCHAR", "Sample_Value": "Card required before trial; multi-step email verification." }, { "Variable": "active_paid_subscribers", "Description": "Estimated number of active paid subscribers", "Business_Rules": "INTEGER >=0; modeled where undisclosed", "Source_System": "Web Intelligence + AI Reasoning", "Data_Type": "INTEGER", "Sample_Value": "9500000" }, { "Variable": "estimated_subscription_revenue_monthly", "Description": "Estimated monthly subscription revenue (local currency)", "Business_Rules": "active_paid_subscribers × subscription_price_median_local; adjusted for discounts if known", "Source_System": "AI Reasoning", "Data_Type": "DECIMAL", "Sample_Value": "151800000.0" }, { "Variable": "regulatory_context", "Description": "Summary of regulation affecting paywalls for this geography", "Business_Rules": "Short text; neutral phrasing; optional if none", "Source_System": "AI Reasoning", "Data_Type": "TEXT", "Sample_Value": "No constraints on metered paywalls; crisis info exceptions." } ] }