Personalized News & Podcast Platform

Personalized News & Podcast Platform

Newslaundry needed a mobile product that could grow engagement and subscriptions without drifting into the low-trust, algorithm-first patterns common in news apps. The product had to feel modern and personalized while still reflecting editorial judgment.

That made this both a content distribution problem and a brand problem. The app needed to deepen habit without undermining what users valued about the publication.

Business Context

A web-first presence limited how often users returned, while podcast listening and premium content journeys were split across surfaces that did not reinforce one another.

At the same time, editorial teams needed confidence that personalization would support quality journalism rather than simply optimize for the loudest content.

Newslaundry needed to compete with algorithmic news feeds while maintaining editorial integrity. Their web-only presence limited mobile engagement, and podcast content was scattered across platforms.

How We Approached the Build

Discovery and workflow mapping

We looked at the full audience loop: article consumption, podcast listening, subscription conversion, and repeat usage. That helped us identify where the mobile product needed to guide users more deliberately.

Architecture and product design

The implementation combined native mobile delivery, content and subscription services, and a recommendation layer designed to work with editorial constraints instead of operating as a black box.

Delivery and integration

The product strategy centered on creating one coherent member experience: discovery, listening, reading, saving, and upgrading all needed to reinforce each other.

What We Implemented

The final app experience was built around the moments that matter most for reader retention and revenue:

• A personalized feed that surfaced relevant stories while preserving room for editorially important coverage.
• A unified podcast experience with playback continuity and offline support so audio could become part of the daily habit loop.
• Subscription journeys that made the value of membership clearer at the right moments in the product.
• Save, continue, and engagement features that reduced the gap between one good session and an ongoing relationship.

AI and automation layer

Recommendation logic was shaped to support editorial curation, not replace it. The system considered behavior and content affinity while still allowing the newsroom to protect what users should see, not only what they were most likely to click.

That balance made personalization compatible with the brand rather than a threat to it.

Stack and engineering decisions

The implementation used React Native, Node.js, PostgreSQL, Recommendation Engine, and Stripe across the experience, service, data, intelligence, and integration layers.

• Experience & channels: React Native
• Core services & data: Node.js and PostgreSQL
• AI/ML & automation: Recommendation Engine
• Cloud, integrations & ops: Stripe

Rollout and measurable outcomes

Launch success depended on more than shipping the app. We watched how reading, listening, and subscription actions changed over time so the feed, prompts, and premium journeys could be refined around real audience behavior.

• Subscriber Growth: 4x
• Daily Engagement: 45 min
• Podcast Listens: 500K/mo
• App Rating: 4.8★

Why This Delivered Business Value

The result was a more habit-forming product and a clearer mobile membership funnel, without compromising the publication’s editorial position.

Taken together, the engagement delivered 4x subscriber growth, 45min average daily engagement by aligning product experience, workflow design, and implementation detail around the same business objective.