OTT Platform Usage and Streaming Behaviour Research Services

Understand what viewers truly do, why they switch, and how to turn engagement into revenue. Research Bureau delivers expert OTT (Over-The-Top) platform usage and streaming behaviour research for telecommunications and ICT organisations, broadcasters, streaming services, advertisers, and content owners. Our evidence-driven insights help teams reduce churn, increase viewing time, optimise catalog value, and design monetisation strategies that scale.

We combine rigorous quantitative measurement, qualitative user research, advanced analytics and domain expertise to deliver action-ready findings. Share your project brief for a tailored quote — contact us via the on-page contact form, click the WhatsApp icon, or email [email protected].

Why OTT usage and streaming behaviour research matters now

Streaming ecosystems are increasingly fragmented across devices, platforms and business models. Small changes in UX, content mix or pricing can shift viewer behaviour and revenue quickly. Organisations need:

Accurate measurement of cross-device consumption and session behaviour.
Deep understanding of drivers of discovery, binge behaviour and churn.
Evidence to design content acquisition, promotional and pricing strategies.

Traditional web analytics alone are insufficient for OTT. You need specialist measurement, robust sampling, and behavioural segmentation to move from data to decisions. That is what we deliver.

Our OTT research services (what we do)

We cover the full research lifecycle from measurement design to strategic recommendations. Our services are modular and can be combined into multi-phase programmes.

Audience measurement & reach estimation — Reliable viewership size, demographics, reach, frequency and cross-platform overlap.
Content performance & catalogue analytics — Title-level performance, content affinity, lifecycle, and ROI per title.
User experience (UX) research & journey mapping — Friction points in discovery, onboarding, playback and billing flows.
Churn & retention diagnostics — Predictive models, segment-specific retention levers and win-back strategies.
Pricing & monetisation optimisation — Subscription, ad-supported, hybrid and transactional pricing experiments.
Ad effectiveness & ad-recall studies — Campaign lift, viewability, completion and brand metrics for AV and display ads.
Live events & concurrency analysis — Technical and behavioural impact of live-streamed events.
Device and app performance analytics — Buffering, start time, crashes, codec and ABR impacts on engagement.
Competitive benchmarking & positioning — Comparative metrics across competitors and strategic gaps.
Forecasting & revenue modelling — Scenario modelling for content investments, churn improvements and ARPU optimisations.
Custom research & qualitative studies — Interviews, FGDs, diary studies and in-app feedback loops.

Each service is delivered with clear objectives, KPIs, data sources, and an actionable roadmap that your product, content and commercial teams can execute.

Sample deliverables

Comprehensive KPI scorecard and executive summary.
Interactive dashboards (Tableau, Power BI, Looker) with filters by device, cohort, region and plan.
Title-level analytics and recommendation matrix for catalogue pruning or promotion.
UX heatmaps and recorded session highlights with prioritized usability fixes.
Statistical models predicting churn and revenue uplift by proposed interventions.
A/B test design, implementation support and post-test analytics.

Methodologies and data sources we use

We design research to be defensible, replicable and privacy-compliant. Typical data sources and methods include:

Server-side logs & CDN data — Ground-truth stream starts, bitrate, buffer events, session duration and concurrent viewers.
In-app SDK telemetry — Page/Screen events, play/pause, seek, error codes and device metadata.
Passive metering panels — Representative households or device panels to measure cross-platform viewing behaviour.
First-party analytics — Google Analytics, Amplitude, Mixpanel for user events and funnels.
Surveys & attitudinal measurement — Subscriber satisfaction, willingness-to-pay, ad-tolerance and content preference polls.
In-depth interviews & focus groups — Contextual insights into motivation, discovery and payment barriers.
A/B and multi-armed bandit tests — Experimentation for UI changes, content promos and pricing variants.
Partner datasets — Telco usage, billing systems and third-party ad servers for unified measurement.
Public and syndicated data — Industry benchmarks, Nielsen/Comscore-style data where available.

We treat each data source’s strengths and limitations explicitly in analysis and triangulate across sources to reduce bias.

Comparison: common data sources at a glance

Data source	Granularity	Latency	Strengths	Limitations
CDN / server logs	Session and chunk-level	Near real-time	Accurate playback metrics, concurrency	Limited attitudinal data
In-app SDK telemetry	Event-level, user-linked	Near real-time	Rich interaction and device context	Implementation variance across apps
Passive metering (panel)	Household/device-level	Daily	Cross-platform measurement, representative	Cost, sample size limits for small segments
First-party analytics	User journey funnels	Minutes–hours	Funnel and retention insights	May miss cross-device identity
Surveys / interviews	Attitudes, intent	Days–weeks	Motivation and qualitative context	Self-report bias
Syndicated/third-party	Broad benchmarks	Weekly–monthly	Market comparatives	May not align with your definitions

Research design and how we work

We follow a structured research process to reduce risk and accelerate impact. Every engagement includes these stages:

Discovery & scoping
- We align on business objectives, target audience segments and success metrics.
- We audit available data sources and gaps to determine measurement needs.
Measurement design
- We map events, KPIs and instrumentation requirements (SDKs, log exports).
- We design sampling frames and panel recruitment where needed.
Data collection & integration
- We ingest logs, SDK events, billing systems and survey results to a secure data warehouse.
- We perform data quality checks and construct harmonised identifiers and timelines.
Analysis & modelling
- We apply descriptive analytics, segmentation, funnel analysis and causal inference.
- We build churn models, propensity scores, title recommendation models and revenue forecasts.
Validation & triangulation
- We validate findings via A/B tests, panel cross-checks and, where applicable, AB tests.
- We present confidence intervals, effect sizes and sensitivity analyses.
Actionable reporting
- We deliver executive summaries, strategic recommendations and implementation playbooks.
- We provide dashboards, raw data extracts and annotated code for reproducibility.
Implementation support & measurement
- We support rollout of interventions, measurement plans and iterative optimisation.
- We help set up automated reporting and KPI tracking for long-term monitoring.

Key metrics and KPIs we track

We align metrics with your commercial and product goals. Core KPIs include:

Reach & MAUs/DAUs — Total unique viewers and active users by time window.
Average Viewing Time (AVT) — Minutes watched per session and per user.
Completion Rate — Percentage of titles or episodes viewed to completion.
Time to First Play — Onboarding friction measured by time from signup to first play.
Churn rate — Subscriber or active user attrition per period.
Retention cohorts — Day-1, Day-7, Day-30 retention curves.
ARPU / ARPPU — Average revenue per user or paying user.
Ad metrics — Ad impressions, completion, viewability and ad lift.
Buffering & QoE metrics — Startup time, rebuffering frequency, bitrate switches.
Content ROI — Spend per title vs. viewership and subscriber contribution.

KPI comparison table

KPI	Why it matters	How we measure
MAU / DAU	User base size and engagement	Device/user IDs, deduplicated across platforms
AVT	Core engagement and stickiness	Session-level durations aggregated by cohort
Churn rate	Revenue loss indicator	Billing records, inactivity thresholds
Retention cohorts	Long-term growth and LTV	Cohort analysis by acquisition channel
Buffering	Experience directly affecting churn	CDN logs, client SDK telemetry
Content ROI	Investment decisions for acquisitions	Production/acquisition cost vs. attributable revenue

Use cases and industry applications

Our OTT research helps a wide range of organisations make better decisions:

Streaming platforms (SVOD/AVOD/TVOD) — Improve catalogue productivity, reduce churn, and optimise ad load and targeting.
Telcos & ISPs — Measure streaming traffic patterns, design bundled offers and negotiate peering/CDN capacity.
Broadcasters & Media Houses — Understand cross-platform migration and monetise digital audiences.
Advertisers & Agencies — Evaluate OTT ad campaigns for reach, frequency and brand outcomes.
Content studios & distributors — Prioritise distribution channels and revenue-share strategies.
Smart TV & Device OEMs — Improve app experiences and preloaded recommendations to increase device engagement.
Platform aggregators & FAST channels — Curate programmatic ad strategies and scheduling to maximise monetisable impressions.

Each use case gets a tailored research plan aligned with commercial KPIs and technical constraints.

Privacy, compliance and data security

We design and operate research with privacy-first principles. Our processes include:

Full adherence to applicable laws and regulations including POPIA (South Africa) and GDPR where relevant.
Consent-based measurement for panel and survey respondents, with transparent data usage and retention policies.
Pseudonymisation and anonymisation of personal identifiers in analytic outputs.
Secure data handling: encrypted data in transit and at rest, role-based access controls, and regular audits.
Data processing agreements and vendor assessments for third-party integrations.

We avoid personally-identifiable reporting unless you explicitly request and legally justify it for business purposes.

Pricing models and timelines

We offer flexible commercial models to suit R&D budgets and ongoing measurement needs:

Project-based research — Fixed fee for discrete projects (e.g., catalogue audit, churn diagnostics).
Retainer & managed services — Monthly retainers for continuous measurement, dashboarding and optimisation.
Shared-risk / outcome-linked — Fee structures tied to uplift in predefined metrics (selected on a case-by-case basis).
Hourly consulting — For ad-hoc advisory, test design or bespoke modelling.

Typical timelines:

Short diagnostic project (4–6 weeks): exploratory audit, quick wins, dashboard proof-of-concept.
Full measurement setup + pilot (8–12 weeks): instrumentation, panel recruitment, pilot analysis.
Continuous monitoring (monthly): ongoing KPI reporting, A/B tests and monthly insight workshops.

We will provide a detailed timeline and phased quote after a discovery call. Share your project brief via the contact form or email [email protected] to get started.

Why clients choose Research Bureau

We combine deep technical skills with telecom and media industry experience to produce insights that convert to commercial impact.

Domain expertise — Senior analysts with experience across telcos, broadcasters and digital-native streaming products.
Rigorous methods — Statistical best practices, causal inference, and reproducible code.
Commercial focus — We translate analytics into specific product, content and pricing actions.
End-to-end delivery — From instrumentation to dashboards and implementation support.
Local and international perspective — Proven projects across Africa, Europe and APAC, with a focus on market-sensitive recommendations.
Flexible engagement — Tailored scope, transparent reporting, and knowledge transfer to your teams.

We treat every engagement as a partnership: delivering outcomes, not just reports.

Example insights we deliver (realistic, anonymised)

After instrumenting SDK telemetry and CDN logs, we identified that reducing median startup time from 6s to 3s raised 7-day retention by 9% for a mid-sized SVOD service.
A content affinity model revealed that promoting complementary niche titles during onboarding increased next-30-day consumption by 14% and reduced trial churn by 6 percentage points.
For an ISP bundling strategy, cross-analysis of streaming traffic and subscriber ARPU showed a profitable zero-rating offer that increased net-new subscriptions by 5% with minimal incremental CDN cost.
An A/B test of ad pod length on an AVOD yielded a 22% lift in completed ad views with only a 3% impact on session abandonment, informing an optimised ad-load policy.

These are examples of the actionable, measurable outcomes we aim to deliver for clients.

Case studies (anonymised)

Case study 1 — Reducing churn for a regional SVOD

Problem: High trial-to-paid churn and low Day-30 retention.
Approach: Combined cohort analysis, in-app surveys and A/B testing of onboarding promos.
Outcome: A targeted onboarding sequence increased Day-30 retention by 12% and reduced refund requests by 18%.

Case study 2 — Content curation for a FAST channel network

Problem: Low average view time on curated FAST channels.
Approach: Title affinity mapping, scheduling experiments and live telemetry analysis.
Outcome: Revised programming and promotion increased average view time per session by 27%, boosting ad revenue per 1,000 impressions.

Case study 3 — Telco streaming bundle optimisation

Problem: Unclear uplift from zero-rating offers and high CDN costs.
Approach: Traffic attribution, cohort LTV modelling and offer experiments.
Outcome: A tiered bundle design improved net ARPU by 6% while controlling CDN cost growth.

Want the full PDF versions of these case studies? Contact us and we’ll share templated reports relevant to your sector.

Tools, platforms and technical stack

We work with common industry tools and can integrate with most stacks:

Data ingestion: AWS Glue, BigQuery, Airflow pipelines.
Storage & processing: Snowflake, Redshift, BigQuery.
Analytics & modelling: Python (pandas, scikit-learn), R, SQL.
Visualisation: Tableau, Power BI, Looker.
Experimentation: Optimizely, in-house AB frameworks.
Panel & recruitment: Proprietary panels, third-party panel providers, and telco partnerships.

If you have legacy systems or a bespoke stack, we tailor an integration plan and provide clean, documented exports.

Frequently asked questions

Q: How do you ensure cross-device identity without violating privacy?

We use hashed, consented identifiers and probabilistic matching techniques where allowed. Where identity is restricted, we rely on panel-based de-duplication and cohort-level analysis.

Q: Can you work with partial instrumentation or missing logs?

Yes. We design hybrid measurement plans that triangulate across available data, supplementing with panels or targeted surveys to fill critical gaps.

Q: How granular can your forecasting get?

Forecast granularity depends on data volume and signal quality. We regularly produce forecasts at monthly, weekly and per-title levels with uncertainty bounds.

Q: Do you provide implementation support for A/B tests?

Yes. We design tests, help instrument, and analyse results. We also advise on governance for experiment prioritisation.

Q: Will we receive raw data and reproducible code?

Yes. Project deliverables commonly include anonymised raw datasets, model code notebooks and documentation for internal reuse.

How to engage — next steps

Share a brief: Use the contact form on this page to tell us about objectives, timelines and key contacts.
Schedule a discovery call: We’ll scope the project, agree on metrics and propose a phased plan.
Receive a tailored quote: We’ll deliver a detailed proposal with timelines, costs and deliverables.

For a fast response, click the WhatsApp icon on the page to message us directly, or email [email protected] with your project summary.

Contact us

Email: [email protected]
Contact form: Use the form on this page to upload briefs or RFPs.
Quick chat: Click the WhatsApp icon on this page for immediate enquiries.

Tell us:

Your primary business objective (e.g., reduce churn, increase ARPU, measure ad effectiveness).
Available data sources (logs, SDKs, billing).
Desired timeline and budget constraints.

We’ll respond within one business day to schedule a discovery call and provide a customised quote.

Final assurance

Research Bureau delivers privacy-conscious, commercially-driven OTT platform usage and streaming behaviour research grounded in robust methodology and industry experience. Whether you need a quick diagnostic or a long-term measurement platform, we help you turn viewer behaviour into competitive advantage.

Contact us now via the contact form, WhatsApp icon, or email [email protected] to request a quote and begin your next research programme.