Use case · Media, Gaming & Entertainment

Personalised content recommendation

Recommendation models that personalise what each viewer, listener or player sees next, across catalogue, homepage and notifications.

The challenge

What organisations face

Streaming, publishing and gaming platforms hold large catalogues, but generic carousels and editorial lists bury most content. Viewers churn when they cannot find something relevant quickly, new titles struggle for visibility and teams cannot measure which personalisation changes actually improve engagement.

The solution

What VulcanTech engineers

VulcanTech would build a recommendation platform combining content embeddings, collaborative filtering and contextual signals, served through low-latency APIs to apps, web and notification systems. Business rules protect editorial priorities and rights windows. An experimentation framework measures each model change, and cold-start strategies give new titles and new users relevant results.

Expected outcomes

What changes for the business

  • More relevant content surfaced for each user
  • New releases reaching the right audiences
  • Personalisation changes measured through controlled experiments

Capabilities

Service lines involved

Free discovery session

Explore personalised content recommendation for your organisation

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  2. 2A senior engineer — not a salesperson — walks through your problem.
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