Addressable Ads Drive $60M and Cut Content Fees by 10% for Pay-TV Operator

Context

A multinational cable and TV operator serving European and South American markets sought to transform its commercial model. The operator delivers TV, broadband, mobile and landline services across advanced fiber and 5G networks and supports roughly 86 million fixed and mobile connections. It also manages a corporate investment arm with a diverse portfolio spanning technology, media, sports and infrastructure. With a verified first‑party footprint that included more than 24 million households (including joint ventures) and 14 million+ connected devices, the business had a unique opportunity to convert viewing and engagement data into commercial value for advertisers and content partners across its broadcast and digital inventory.

Challenges

Brand and content partners were paying flat rates with no ability to target audience segments, leaving revenue potential untapped. There was no behavioural or engagement data layer to support audience‑based pricing or value‑driven content negotiations. Internally, vast volumes of viewing and navigation data existed across platforms but were fragmented — no single platform could ingest, harmonize and operationalize the high velocity of telemetry. Commercial conversations remained cost‑driven rather than value‑based, and the company lacked measurement and addressability capabilities needed to unlock premium pricing and more favourable content contract terms.

Implementation

The Fractional Head of AI led a product‑first approach to build audience measurement and addressable advertising capabilities from zero. The program aggregated consumer data across more than 24 million households and 14 million devices, combining first‑party viewing signals with deterministic third‑party attributes to create a privacy‑compliant, unified audience graph. Behavioural, viewership and engagement layers were injected into the platform to enable real‑time segmentation and cross‑channel measurement.

Segmentation models were designed to support precise audience targeting across linear and digital broadcast channels — from sports viewers and young families to high‑value binge audiences — and to expose transparent metrics advertisers value (reach, frequency, incremental reach, and conversion proxies). AI models produced granular, local and macro insights for campaign planning and attribution. The team partnered with Programming & Strategy to translate audience analytics into negotiation levers, enabling commercial teams to move from flat‑rate buys to value‑based pricing tied to measured audience outcomes.

The team intentionally built a product, not a one‑off project: AI was embedded across the stack to power dynamic segmentation, yield optimization and reporting dashboards that became both an internal commercial tool and an incremental revenue stream for external clients. Cloud infrastructure and data engineering pipelines were developed to handle the cast amount of data and support low‑latency delivery to ad servers and programmatic partners.

Results

The platform unlocked a new addressable advertising revenue stream that generated $60M of incremental revenue. Advertisers were able to target precise audience segments at scale, pay for performance and buy based on demonstrable value rather than publisher inventory alone. The operator also used audience‑backed analytics in content negotiations, delivering a 10% reduction in content fees through evidence‑based contractual discussions and performance‑linked structures.

Beyond immediate financial gains, the initiative converted a previously siloed asset — first‑party viewing and engagement data across 24M+ households and 14M+ devices — into a strategic product offering. The AI‑driven platform now supports ongoing commercial optimization, richer advertiser propositions at local and macro levels, and a reproducible approach for future product extensions. In short, the company shifted from selling undifferentiated reach to monetizing verified audiences and measurable outcomes, improving margin on advertising and reducing incoming content costs through data‑informed negotiation.