| app_name | Speak & Learn English: Learna | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| app_id | 6478287397 | ||||||||||||
| developer | DEEP FLOW SOFTWARE SERVICES | ||||||||||||
| category | Education | ||||||||||||
| paywall_type | Free Trial - Soft Paywall | ||||||||||||
| pricing_model | 1 offer set across week, year | ||||||||||||
| mrr | $63.70K | ||||||||||||
| rating | 4.65 | ||||||||||||
| versions_count | 8 | ||||||||||||
| offers |
|
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| onboarding_count | 24 | ||||||||||||
| walkthrough_count | 6 | ||||||||||||
| app_detail_url | https://www.paywallpro.app/apps/Speak-&-Learn-English:-Learna-us?id=1128935&utm_source=github&utm_medium=open_dataset&utm_campaign=paywall_gallery |
Category: Education Estimated MRR: $63.70K Paywall Pattern: Free Trial - Soft Paywall Pricing Model: 1 offer set across week, year Captured Version: 3.1.6 Version Release Date: 2026-03-17
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Speak & Learn English: Learna is an Education app by DEEP FLOW SOFTWARE SERVICES. This compact public preview highlights representative iOS subscription paywall screens from the US storefront.
Its paywall is a useful reference for studying how apps in the Education category present subscription value, structure pricing, use trials, and reduce purchase friction.
The full PaywallPro page includes the complete screenshot set, version history, onboarding context, and deeper revenue signals.
- Speak & Learn English: Learna uses the Free Trial - Soft Paywall pattern in the Education category.
- The preview exposes one visible offer set; the full PaywallPro page may include more historical context.
- The paywall presents week, year option(s), which can help reveal how the app uses price anchoring and subscription framing.
- The pricing structure shows how a leading Education app packages subscription value for its users.
Paywalls in the Education category need to communicate value quickly and make the subscription decision easy to understand.
This Speak & Learn English: Learna paywall is worth studying because it shows how a real subscription app combines offer framing, pricing structure, visual hierarchy, and purchase flow into one conversion experience.
For app builders, product managers, growth teams, and designers, this case can be used as a reference when researching pricing, trial strategy, subscription UX, or paywall redesign ideas.
| Field | Value |
|---|---|
| Category | Education |
| Paywall type | Free Trial - Soft Paywall |
| Pricing model | 1 offer set across week, year |
| Captured version | 3.1.6 |
| Version release date | 2026-03-17 |
This paywall uses the Free Trial - Soft Paywall structure.
This pattern is useful for studying how the app presents subscription value, reduces purchase hesitation, and guides users toward a paid plan.
| Offer | Week | Year |
|---|---|---|
| Offer 1 | $14.95 | $39.99 |
| Metric | Value |
|---|---|
| App Store rating | 4.65 |
| Category rank | #3 |
| Estimated MRR | $63.70K |
| Avg daily revenue | Not available |
| Avg daily downloads | Not available |
| Avg daily ARPU | Not available |
| Onboarding preview count | 24 |
| Walkthrough preview count | 6 |
| Full history available on PaywallPro | Yes |
- How Speak & Learn English: Learna frames subscription value for users in the Education category.
- How the app structures pricing options and subscription periods.
- How the paywall uses visual hierarchy to guide the purchase decision.
- How trials, discounts, or offer sets are used to reduce purchase friction.
- How this paywall can inspire pricing, UX, or A/B testing ideas for similar apps.
- Which plan or offer is visually prioritized?
- Does the paywall lead with value, price, trial, urgency, or social proof?
- Is the annual plan positioned as the best-value option?
- How much cognitive load does the pricing section create?
- What would you test if you were optimizing this paywall?
- How does this paywall compare with other apps in the Education category?
This is a limited public preview.
For the full paywall history, complete screenshot set, onboarding flow, historical changes, pricing experiments, and deeper revenue analysis, visit:
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