OTT & Streaming Intelligence — Cubot BI
Solution

OTT & Streaming
Intelligence

Streaming platforms generate enormous volumes of data — viewing events, subscriber behaviour, content interactions, device signals. The challenge is not collecting it. It is turning it into something a content head, a CFO, or a retention team can act on — without building a data team to make it work.

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Key performance indicators
MAU
Monthly Active Subscribers
Active vs total base, trend by period
↑ 6.2% MoM
4.8%
Churn Rate
Monthly churn by tier and cohort
↑ 0.4pts vs last month
68%
Completion Rate
Average content completion across titles
↑ 3.1pts
38 min
Avg Watch Time / User
Daily average per active subscriber
Stable
22%
Trial Conversion Rate
Free or trial users converting to paid
↑ 2.8pts
ARPU
Revenue Per User
By subscription tier and geography
↑ 4.1% QoQ
7.4
Engagement Score
Composite frequency, depth, and completion
↑ 0.6 pts
84%
Ad Fill Rate
AVOD inventory utilisation by segment
↓ 1.2pts
Content Types

Across every format

The intelligence layer works across content types — each with its own engagement patterns, completion behaviour, and monetisation model — all handled within a unified data model.

🎬
Video on Demand
Movies, series, originals — completion, drop-off, rewatch
🏆
Live Streaming
Sports, news, events — concurrent viewers, peak load, engagement
🎵
Music Streaming
Skip rates, repeat listens, playlist adds, genre affinity
🎙️
Podcasts & Audio
Episode completion, listener retention curve, ad spot performance
📱
Short-Form Video
Session depth, scroll behaviour, share and save signals
📚
EdTech & E-Learning
Course completion, lesson drop-off, certification conversion
📰
News & Publishing
Article completion, scroll depth, paywall conversion, subscriber engagement
📺
FAST Channels
Free ad-supported streaming TV — viewership, ad inventory, channel switching
Capabilities

Intelligence across the full operation

From content performance to subscriber behaviour to advertising yield — a unified intelligence layer built on your streaming and subscriber data.

Content Intelligence
Completion rates, drop-off by episode and segment, rewatch behaviour, content decay curves, peak viewing windows, and content ROI from cost through to total watch hours generated.
Subscriber Intelligence
Acquisition by channel and campaign, cohort analysis by join date and genre, lifetime value by segment. Which content attracts subscribers who stay versus those who leave after one series.
Anomaly Detection & Alerts
Sudden churn spike. Watch-time collapse on a key title. Revenue drop on a tier. Buffering correlated with cancellation. Threshold and trend-break detection surfaced before management has to explain them.
Executive Intelligence
Automated periodic summaries — weekly, monthly, board-level. Content rankings, subscriber movement, revenue by tier, key anomalies flagged. Leadership sees the business without pulling a report themselves.
Advertising Intelligence
Fill rates, CPM by content type and audience segment, ad completion rates by placement. Which inventory is underpriced. Audience segment performance for direct advertiser conversations.
Peer & Genre Benchmarking
Compare title performance across genres, release windows, and content types. Identify which categories are over- or under-invested relative to their contribution to engagement and retention.
Predictive Intelligence

Scores that drive action

Predictive indicators are computed from behavioural data already in the platform — viewing patterns, session frequency, genre shifts, device activity. They surface as scores per subscriber and per title, updated each cycle, giving teams the lead time to act rather than react.

Scores are computed from your own data, inside your environment. Subscriber behaviour and predictive signals never leave the organisation.

Subscriber scores — illustrative
Engagement & churn signals — current period
Subscriber segment A
Sports genre · Mobile · 14 months tenure
Retain
Subscriber segment B
Drama genre · Smart TV · 6 months tenure
Watch
Subscriber segment C
Multi-genre · Mobile · 2 months tenure
At Risk
Subscriber segment D
Kids genre · Tablet · 22 months tenure
Retain
Churn Propensity Score
Per subscriber, updated each cycle — recency, frequency drop, genre shift, inactivity
Per user
Content Decay Signal
Flags titles where viewership is falling faster than expected — approaching zero marginal value
Per title
Conversion Likelihood
Trial and free-tier users most likely to convert — based on viewing depth and session patterns
Per user
Binge Score
Session depth and consecutive episode consumption as an engagement quality indicator per subscriber
Per user
Renewal Risk Score
Accounts approaching renewal date flagged by engagement level — enabling proactive retention
Per user
Data Sources

Connects to where your data lives

The intelligence layer is built on top of data already being generated by your platform. The pipeline ingests, structures, and models it — no manual preparation, no data team required.

Subscriptions
Subscription Management
Active subscribers, tier, billing cycle, trial status, renewal dates
Viewing
Video Delivery & CDN
Stream events, watch time, completion, quality, buffering signals
Behaviour
App & Web Analytics
Session data, navigation, search, device, engagement events
Revenue
Payment & Billing Platform
Revenue by tier, payment method, failed charges, refunds
Advertising
Ad Server
Impressions, fill rate, CPM, completion rate, segment performance
Customers
CRM & Customer Data
Demographics, acquisition source, preferences, support history
Acquisition
Marketing & Campaign Data
Channel attribution, campaign performance, cost per acquisition
Content
Content Catalogue & Metadata
Title, genre, format, licensing cost, release date, production data

See what your streaming data can tell you

Get in touch to discuss how the intelligence layer maps to your platform, content types, and business priorities.

info@cubotbi.com
www.cubotbi.com
CUBOT BI for Digital Media