7+ years as a Business Analyst. MA in Media & Communication. Now bridging the gap between how great content is decided and how it actually gets to audiences.
"I bridge the business of content and the systems that deliver it."
Every skill I've built over 7 years translates directly into OTT/media operations. This isn't a pivot from scratch — it's a context shift with the same underlying discipline.
Each piece demonstrates a specific OTT competency — built to show hiring managers exactly how my BA background applies to content strategy and operations.
I'm Praveen Saki — a Business Analyst with 7+ years of experience and an MA in Media & Communication from the University of Hyderabad. I'm making a deliberate move into the OTT and media industry, specifically into Content Strategy & Operations roles.
At Williams Lea, I own the end-to-end product backlog for automation transformation programmes across 5–10 global enterprise clients. I run discovery workshops, conduct market and competitor analysis, build product roadmaps, and lead all Scrum ceremonies for teams of 15+ across 10+ sprints. I don't hand off and walk away — I stay accountable from the first workshop to final UAT sign-off.
My interest in OTT isn't recent. My MA research was grounded in media business models, audience theory, and content economics. I led creative operations for global live media events at CoProTech. I built content roadmaps for product launches at Valor PayTech. The analytical rigour is from BA. The media instinct is from everything else.
What I bring specifically to OTT: I'm Tamil and Telugu fluent, South India-based, and I understand those markets from the inside. Regional language content is where Indian OTT's next subscriber wave will come from — and I'm positioned at exactly that intersection.
That a rigorous BA background, an MA in Media & Communication, and a deep understanding of South Indian content markets is exactly what OTT content operations teams need.
India's OTT audience universe has reached 601.2 million people (Ormax, 2025). Non-Hindi content now accounts for over 50% of all OTT viewership. Yet both Netflix India and Amazon Prime Video remain structurally over-indexed on Hindi originals. The South Indian market — Tamil, Telugu, Malayalam, Kannada — represents the single largest underserved growth opportunity on either platform.
This analysis compares Netflix India and Amazon Prime Video's content strategies through the lens of regional language representation, genre depth, and audience demand alignment. Using publicly available library data, Ormax audience research, and platform press announcements, I identify a structural mismatch between what both platforms offer and where actual Indian subscriber demand is growing.
The core finding: Amazon Prime Video leads Netflix in regional content depth — particularly Tamil and Telugu — but neither platform has built a cohesive, sustained South Indian originals strategy. The market is waiting for the platform that commits. This analysis recommends three acquisition moves that could close that gap.
Netflix India launched its India originals strategy in earnest with Sacred Games (2018) and Delhi Crime (2019). Its strength is premium quality and international co-production (like The Elephant Whisperers, Oscar-winning documentary). It offers 15,000+ titles in India, with dubbing and subtitles in 62+ languages. However, its Tamil and Telugu original series slate remains thin — Navarasa (anthology) and a handful of films constitute most of its South Indian original output. Netflix announced six Tamil and Telugu originals in October 2025, signalling recognition of the gap — but not yet a sustained strategy.
Amazon Prime Video India has invested more consistently in regional content. It leads with Tamil originals (Suzhal, Modern Love Chennai) and Telugu productions (Modern Love Hyderabad, Dhootha). Its 18,000+ India title library includes a stronger Bollywood catalogue. In March 2025, Amazon announced 36 Indian original shows and films — its single largest India content drop — signalling aggressive intent. It also offers Tamil and Telugu UI navigation, a product signal of serious regional investment.
The following comparison is based on JustWatch India library data and platform press releases as of Q1 2025:
| Dimension | Netflix India | Amazon Prime Video | Gap / Insight |
|---|---|---|---|
| Total India Titles | ~15,000+ | ~18,000+ | Amazon leads on volume |
| Hindi Originals | Strong (Delhi Crime, Sacred Games, Scoop) | Strong (Mirzapur, The Family Man, Panchayat) | Both platforms well-served |
| Tamil Originals (Series) | Navarasa, Kathal (film) | Suzhal, Modern Love Chennai, Vadhandhi | Amazon leads significantly |
| Telugu Originals (Series) | Rana Naidu (co-prod), limited | Modern Love Hyderabad, Dhootha, Farzi Telugu | Amazon leads significantly |
| Malayalam Content | Licensed films, minimal originals | Licensed films, some originals | Both platforms thin |
| International Content | Extensive (Korean, Spanish, US) | Moderate | Netflix leads clearly |
| Documentary (India) | Strong — The Elephant Whisperers, Fabulous Lives | Moderate | Netflix leads |
| Reality / Non-Fiction India | Indian Matchmaking, Fabulous Lives | Limited | Netflix leads on format |
| Language UI Support | Hindi, English, limited regional | Tamil, Telugu UI available | Amazon product signal is stronger |
The demand signal is unambiguous. Regional-language content now accounts for over 50% of all Indian OTT viewership (Fortune India, 2025). ZEE5 reported in December 2025 that regional languages outside Hindi account for more than 50% of its paid subscriptions. Investments in Tamil, Telugu, Kannada, Bengali, and Malayalam content are expected to exceed ₹5,000 crore annually by 2028.
Yet the two largest global OTT platforms in India have built originals strategies that remain predominantly Hindi-led. The audience-content mismatch is clearest in three segments:
Aha, a South India-focused OTT that launched in 2020, attracted over 20 million users within a few years — nearly entirely on the strength of Telugu and Tamil originals. Neither Netflix nor Amazon has matched this depth in a sustained way. The demand is validated. The supply gap is structural.
The following three content acquisition moves would materially close the South Indian gap for either platform:
Recommendation 1: Commission a Tamil crime anthology series (6–8 episodes, two seasons greenlit simultaneously). The Suzhal model proved this audience exists and pays. A platform that commits to two seasons from announcement signals confidence in the market — which in itself drives subscriber acquisition. Target: urban Tamil audiences aged 25–40, proven OTT users, high willingness to pay. KPI: 40%+ completion rate, 15% new subscriber attribution in Tamil Nadu and Tamil diaspora markets.
Recommendation 2: Acquire a high-profile Telugu family drama series from an established production house. License it exclusively for 18 months before any theatrical window. Telugu content has demonstrated strong Tier-2 city penetration in Andhra Pradesh and Telangana — subscriber segments that neither Netflix nor Amazon has cracked at scale. Target: Telugu-speaking households aged 28–50 across AP, Telangana, and Telugu diaspora (US, Middle East). KPI: 25% MAU lift in Telugu-speaking states within 90 days of launch.
Recommendation 3: Build a South India-specific content track within the originals slate — not one-off productions, but a visible programmatic commitment. Brand it internally (e.g. "Prime Tamilagam" or "Netflix Naadu") with dedicated marketing budgets and multi-language UI localisation. The product signal matters as much as the content itself. Audiences make subscription decisions partly based on whether a platform "sees" them. A named regional track communicates that. KPI: Brand sentiment improvement in Tamil and Telugu language markets (measured via Ormax brand tracker), sustained 3-year subscriber growth in South Indian states.
This workflow was built using the same As-Is/To-Be process mapping methodology applied across 3+ automation delivery programmes at Williams Lea, adapted to an OTT content pipeline context. The stages, decision gates, and stakeholder touchpoints are based on publicly available content operations frameworks and OTT industry job description analysis.
Most conversations about OTT content strategy focus on what to acquire. Far fewer focus on what happens after the acquisition decision is made. In practice, the gap between "deal signed" and "content live on platform" is where subscriber-critical releases get delayed, metadata errors slip through to launch, and localisation quality creates poor first-impression viewing experiences.
For a platform releasing 36 Indian originals in a single year (Amazon Prime, 2025 announcement), the content operations workflow is not a back-office function — it is a direct business risk. Each delayed release has a subscriber acquisition and retention cost. Each metadata error affects discoverability and recommendation algorithm performance.
This document maps the end-to-end content operations pipeline, identifies the four most common failure points, and proposes structural improvements for each.
Content team presents acquisition brief to business affairs and senior leadership. Decision criteria: audience fit, competitive positioning, licensing cost vs projected subscriber impact. Output: signed acquisition mandate with budget approval.
Legal and business affairs negotiate and finalise the licensing agreement. Key parameters: exclusivity window (typically 12–24 months for Indian originals), territory rights, sub-licensing restrictions, language dubbing rights, sequential release windows. Output: executed agreement with content delivery schedule.
Studio delivers master files per technical specifications: video codec, audio tracks, subtitle files (SRT/VTT format), promotional assets (key art, thumbnail images). This stage is a frequent failure point — studios often deliver files not meeting spec, requiring re-delivery and causing scheduling delays. Decision gate: technical specification check before acceptance.
Content is ingested into the platform's CMS. Technical QC checks: video quality (bitrate, resolution, artefact detection), audio sync, subtitle timing accuracy. Automated tools handle volume; human QC team reviews flagged files. Output: QC-passed content ready for metadata.
Metadata team tags content with: title, synopsis (in all supported languages), genre, sub-genre, cast, director, language, certificate rating, keywords for search and discovery. Classification errors at this stage directly damage recommendation algorithm accuracy and search discoverability. This is the most commonly under-resourced stage in content operations.
For Indian OTT, localisation is not optional — it's audience reach. Content must be accessible in at minimum Hindi, Tamil, Telugu, and English subtitle/dubbing options. Dubbing quality is a viewer experience issue — poor sync or quality affects completion rates. Decision gate: localisation quality sign-off before proceeding to editorial QC.
The content team and editorial lead review the complete content package on the platform's staging environment. This mirrors the UAT process in a software delivery context: does the title display correctly? Are episode sequences accurate? Is the thumbnail displaying correctly across device types? Are all metadata fields complete? Output: editorial sign-off or remediation list.
Confirmed launch date is set in the publishing calendar. Marketing assets (social, in-app banners, email campaigns) are scheduled in coordination. At go-live, platform team monitors: initial viewer response, technical streaming issues, social sentiment. First-72-hour completion rate is the primary early signal of content performance.
Based on analysis of OTT content operations job descriptions, industry reports, and content delay patterns observed from public platform announcements:
| Failure Point | Where It Occurs | Business Impact | Structural Fix |
|---|---|---|---|
| Studio file spec mismatch | Stage 3 — Content Delivery | Re-delivery adds 2–4 weeks to schedule; launch date missed | Mandatory pre-delivery technical checklist issued to studio at contract signing |
| Metadata errors at ingestion | Stage 5 — Metadata Tagging | Discoverability damage; wrong content served to wrong audience segments | Metadata QC checklist with mandatory dual-approval before publishing unlock |
| Localisation quality failures | Stage 6 — Dubbing / Subtitles | Viewer experience damage; completion rate drop; negative social sentiment | In-house language reviewer sign-off; no AI-only dubbing for originals without human review |
| Editorial-marketing sync breakdown | Stage 7–8 boundary | Marketing assets ready but content delayed; or content live without marketing support | Shared release calendar with 72-hour buffer zone built into scheduling protocol |
A well-functioning content operations pipeline has three characteristics that most Indian OTT platforms are still building toward:
This workflow design directly mirrors the As-Is/To-Be process mapping methodology I apply at Williams Lea across automation transformation programmes. The vocabulary is different — "stages" instead of "sprints," "editorial sign-off" instead of "UAT" — but the underlying discipline is identical: map current state, identify failure modes, design improved flow, define accountability at each handoff.
Vera OTT is a hypothetical South Indian streaming platform targeting Tamil, Telugu, and Malayalam audiences aged 22–45, across Tier 1 and Tier 2 cities. Q3 2025 is the platform's growth quarter — subscriber acquisition target is +35% over Q2, driven by three tentpole releases anchored to Onam (September) and Independence Day (August 15).
Q3 in South India is a high-intent content consumption quarter. Onam (September) is the single biggest streaming moment for Malayalam audiences — historically platforms see 30–40% viewership spikes during the festival week. Independence Day (August 15) is a cross-language opportunity for patriotic or socially resonant content. Ganesh Chaturthi (late August) speaks to Telugu and Tamil urban audiences.
Vera OTT's Q3 strategy is built on three pillars: anchor originals (high-investment tent-poles driving subscriber acquisition), catalogue releases (licensed films building engagement between originals), and non-fiction formats (building daily active user habits between drama series releases).
Content mix target for Q3: 40% Tamil, 35% Telugu, 15% Malayalam, 10% bilingual/crossover. Genre balance: 35% thriller/crime drama, 25% family drama, 15% non-fiction/documentary, 15% comedy, 10% action.
| Week | Date | Title (Fictional) | Format | Language | Genre | Strategic Rationale |
|---|---|---|---|---|---|---|
| W1 | Jul 4 | Kadal Meipadu (Sea of Truth) | Series — 6 eps | Tamil | Crime Thriller | Q3 anchor original — launch week high intent; hooks subscribers early in quarter |
| W1 | Jul 6 | Nadam (Heartbeat) | Film acquisition | Telugu | Family Drama | Catalogue weekend release; cross-audience reach while anchor drives conversation |
| W2 | Jul 11 | Pesam (The Discourse) | Documentary — 4 eps | Tamil/Telugu | Non-Fiction | Bridges audience between drama releases; builds daily active user habit |
| W3 | Jul 18 | Eeramai (Damp Earth) | Series — 8 eps | Telugu | Rural Family Drama | Telugu anchor — Tier 2 Andhra/Telangana audience; proven genre demand |
| W4 | Jul 25 | Iru Nilai (Two States) | Film acquisition | Tamil/Telugu bilingual | Comedy | End-of-month light content; retains casual subscribers; cross-language event |
| W5 | Aug 1 | Veli (Boundary) | Series — 6 eps | Tamil | Psychological Thriller | Month 2 anchor; premium genre for urban Tamil audience; drives paid upgrade intent |
| W6 | Aug 8 | Ottam (Run) | Short Film Collection | Malayalam | Drama anthology | Malayalam audience engagement; builds Onam anticipation; format variety |
| W7 | Aug 15 | Tholvi Illai (No Defeat) | Film — Independence Day release | Tamil | Historical Drama | Independence Day tentpole; broad audience reach; social media amplification moment |
| W7 | Aug 15 | Veeram (Courage) | Documentary | Telugu | Military/Social | Aug 15 dual release — serves Telugu audience independently on national holiday |
| W8 | Aug 22 | Mudhal Paarvai (First Look) | Reality/Non-Fiction — 10 eps | Tamil | Industry Reality | Post-tentpole engagement bridge; weekly release model builds DAU habit through Aug |
| W9 | Aug 29 | Ganapathi (The Remover) | Film acquisition | Telugu | Devotional Drama | Ganesh Chaturthi timing; Telugu devotional audience; community content moment |
| W10 | Sep 5 | Kaadu (The Forest) | Series — 8 eps | Malayalam | Thriller | Onam build-up; Malayalam audience priming; premium original signals platform commitment |
| W11 | Sep 12 | Oruvan (The One) | Film acquisition — Onam premiere | Malayalam | Family Drama | Onam tentpole — biggest single-title event of the quarter; Malayalam subscriber spike driver |
| W12 | Sep 19 | Namma Veetu Kadhai (Our Family Story) | Series — 6 eps | Tamil | Family Drama | Post-Onam engagement retention; family content for Tamil audience returning to routine |
| W13 | Sep 26 | Q4 Teaser Drop | Promo Content | All languages | Marketing | End-of-quarter subscriber retention; creates anticipation for Q4 slate before churn risk window |
| Dimension | Q3 Split | Rationale |
|---|---|---|
| By Language | Tamil 40% · Telugu 35% · Malayalam 15% · Bilingual 10% | Reflects audience size distribution; Malayalam weighted up for Onam quarter |
| By Format | Series 45% · Film acquisitions 30% · Non-Fiction 15% · Shorts 10% | Series drives subscription loyalty; films drive one-time acquisition peaks |
| By Genre | Thriller 35% · Family Drama 30% · Non-Fiction 20% · Comedy 10% · Other 5% | Thriller drives premium subscriber intent; family drama retains casual subscribers |
| Originals vs Acquisitions | 55% Original · 45% Acquired | Originals justify subscription; acquisitions reduce content gap between originals |
| Tentpole Events | 3 (Independence Day · Ganesh Chaturthi · Onam) | Each anchored to a culturally resonant moment; marketing budgets front-loaded to these |
Why two releases on Independence Day (Aug 15): A Tamil historical drama and a Telugu documentary serve two separate audience segments without cannibalising each other. The national holiday creates an elevated content consumption moment — it's worth doubling down, not treating it as a single-title event.
Why Onam gets a two-week build-up (W10 + W11): The W10 Malayalam thriller series builds audience anticipation for the Onam premiere in W11. Subscribers who engaged with the series are more likely to watch the Onam film — reducing churn through the festival week and increasing time-on-platform metrics.
Why the Q4 teaser at W13: End-of-quarter churn risk is real. Subscribers who've finished the content they signed up for will evaluate whether to continue. A teaser of the Q4 slate in the final week of Q3 converts this from a churn window into a renewal incentive.
This is a mock Content Acquisition Brief — the OTT equivalent of a Business Requirements Document — prepared to demonstrate how BA-style structured thinking applies to content investment decisions. It is designed as if being presented to a content leadership team for sign-off on a Tamil psychological thriller series acquisition.
Recommended acquisition: An original Tamil-language psychological thriller series, 6–8 episodes, for exclusive streaming rights targeting South Indian OTT audiences.
Business case in one sentence: The Tamil psychological thriller genre has demonstrated high subscriber acquisition potential (validated by Suzhal on Amazon Prime), while both major global OTT platforms remain structurally under-invested in this format — creating a first-mover acquisition window for a committed platform.
Recommended investment range: ₹8–15 crore for a 6-episode series, depending on cast tier and production house. Exclusive streaming rights, 18-month window, Tamil Nadu + global Tamil diaspora territory.
| Dimension | Profile |
|---|---|
| Primary Audience | Tamil-speaking OTT subscribers aged 25–42, urban and semi-urban, Tamil Nadu and Pondicherry |
| Secondary Audience | Tamil diaspora — UAE, Malaysia, Singapore, UK, USA (estimated 8–10 million Tamil speakers outside India) |
| Gender Split | 55% male, 45% female (psychological thriller skews slightly male but has strong female viewership — Suzhal data) |
| Platform Behaviour | High completion rate on thriller genre (65–70% vs 50% average); high social sharing behaviour; second-screen discussion on Twitter/X |
| Willingness to Pay | Above-average — Tamil OTT subscribers who pay for regional platforms (Aha, SunNXT) demonstrate paid subscription comfort in the ₹99–199/month range |
| Discovery Behaviour | Word-of-mouth and trailer virality driven; IMDb rating and Letterboxd discussion matter for urban segment; family recommendation for 35+ segment |
India's OTT audience has reached 601.2 million people (Ormax, 2025). Non-Hindi content accounts for over 50% of all OTT viewership nationally. Tamil Nadu alone has approximately 75 million Tamil speakers, with an OTT penetration rate growing faster than the national average due to Jio and mobile broadband expansion in Tier 2–3 cities.
The psychological thriller genre has specific market validation in Tamil content. Suzhal (Amazon Prime, 2022) — a Tamil crime thriller — became one of the most-watched Indian regional originals on the platform, generating significant subscriber acquisition impact in Tamil Nadu and among global diaspora. It demonstrated that quality Tamil thriller content travels beyond its primary language group, with dubbed and subtitled versions performing well in non-Tamil Indian markets.
Despite this validation, as of Q1 2025, neither Netflix India nor Amazon Prime Video has a Tamil psychological thriller series in active production. The competitive window is open. A platform that moves now — with a committed 2-season investment — can claim this genre positioning before a competitor does.
| Platform | Tamil Psychological Thriller Originals | Gap |
|---|---|---|
| Netflix India | Navarasa (anthology, 2021) — limited thriller segment; no dedicated crime drama series | Significant — no active production in this genre |
| Amazon Prime Video | Suzhal (2022), Vadhandhi (2022) — two strong entries, but no confirmed successors as of 2025 | Moderate — has precedent but not sustained slate |
| Disney+ Hotstar | Tamil content mostly licensed films; no psychological thriller original series | Significant |
| SunNXT | Primarily film acquisitions; limited original production | Regional player, not direct competition for premium originals |
| Aha (Tamil) | Growing Tamil slate but positioned more in action/romance; thriller space not dominant | Moderate — regional competitor but lower production values |
| Specification | Requirement |
|---|---|
| Language | Tamil (primary); Hindi and English subtitles mandatory; Hindi dub for national reach |
| Episodes | 6–8 episodes, Season 1; 2-season commitment preferred at greenlight |
| Episode Length | 40–55 minutes per episode (optimised for OTT; not broadcast-length) |
| Production Quality | Theatrical-grade cinematography; minimum ₹1.5–2 crore per episode production budget |
| Tone | Grounded, psychologically complex; not supernatural; urban or semi-urban Tamil setting |
| Cast Tier | One established Tamil actor (A or B list) + strong ensemble; diaspora-recognisable preferred |
| Director | Proven Tamil OTT or film director; prior thriller experience preferred |
| Script | Original screenplay or adaptation of established Tamil literary source; not remake of existing IP |
| Shooting Format | 4K HDR; streaming-first editing style (not broadcast paced) |
| KPI | Target | Measurement Window |
|---|---|---|
| Episode 1 Completion Rate | ≥ 65% | First 7 days post-launch |
| Series Completion Rate | ≥ 45% | 30 days post-launch |
| New Subscriber Attribution | ≥ 12% of launch-month new subscribers cite series as primary acquisition driver | 30 days post-launch |
| Tamil Nadu MAU Lift | ≥ 20% month-on-month in Tamil Nadu state | Launch month vs prior month |
| Social Sentiment Score | ≥ 75% positive (Twitter/X + YouTube comments) | First 14 days |
| Non-Tamil viewership (dubbed) | ≥ 15% of total views from non-Tamil language users | 60 days post-launch |
| Season 2 Trigger Threshold | If completion rate ≥ 50% AND MAU lift ≥ 18%, Season 2 greenlit automatically | 45 days post-launch |
This analysis applies a standard BA framework — problem definition, stakeholder mapping, user stories, gap analysis, and improvement recommendations with acceptance criteria — to a feature most users interact with daily without thinking about. The Top 10 rail on Netflix India is a product decision with significant content discovery, subscriber satisfaction, and regional language representation implications.
Netflix's "Top 10 in India" rail displays the ten most-watched titles on the platform in India in the current week, ranked by total viewing hours. It appears prominently on the homepage for all Indian subscribers. Netflix publishes the underlying data publicly at top10.netflix.com, updated weekly.
The problem the feature was designed to solve: Subscriber content discovery. Netflix has 15,000+ titles available in India. The recommendation algorithm is personalised but can feel opaque — users don't always trust it because they don't understand why a title is being recommended to them. The Top 10 rail solves for social proof: "other Indians are watching this" is a simpler, more trusted discovery signal than a personalised algorithm recommendation.
Where the feature falls short for Indian audiences: The Top 10 rail is a single national ranking. India has 22 scheduled languages and distinct regional media cultures. A Tamil subscriber in Chennai and a Hindi subscriber in Delhi see the same Top 10 — which is structurally biased toward the language with the largest absolute viewership base (Hindi). Tamil, Telugu, and Malayalam content that performs exceptionally well within its language group rarely appears in the national Top 10, making the feature an incomplete discovery tool for regional language audiences — who now represent over 50% of Indian OTT viewership.
| Stakeholder | Interest in This Feature | Current Pain Point |
|---|---|---|
| Tamil / Telugu / Regional Subscribers | Discover content in their language that others are watching | Top 10 rarely reflects regional content performance; feels irrelevant |
| Hindi-speaking Subscribers | See what's trending in India | Feature works adequately; no significant pain point |
| Netflix Content Team (India) | Drive viewership of new originals; surface regional content | Regional originals get lower organic discovery despite strong within-language performance |
| Netflix Marketing Team | Create social media moments around trending content | Top 10 data drives press coverage — regional titles rarely get this amplification |
| Production Houses / Studios | Their content's Top 10 appearance drives follow-on deal leverage | Regional production houses rarely benefit from Top 10 PR value |
| Netflix Platform / Product Team | Feature drives engagement and time-on-platform | Feature may be reducing engagement for 50%+ of user base (regional language users) |
Recommendation 1: Add a language-specific "Top 10 in [Language]" rail alongside the national Top 10.
Users whose primary language preference is Tamil, Telugu, Malayalam, Kannada, or Bengali see a language-specific trending rail as a secondary carousel on the homepage, immediately below the national Top 10. This requires minimal engineering change — the data infrastructure already exists (Netflix publishes language-specific Top 10 data at top10.netflix.com). It's a product and UX decision, not a data infrastructure challenge.
Acceptance criteria:
Recommendation 2: Implement language preference collection at onboarding for new subscribers.
New subscribers are asked "What language do you prefer to watch content in?" during the first-launch experience (similar to Netflix's existing genre preference screen). This data immediately informs which Top 10 variant they see, solving the cold-start problem for regional language subscribers.
Acceptance criteria:
Recommendation 3: Apply recency decay weighting to the Top 10 ranking algorithm.
Modify the ranking methodology to weight recent viewing hours (last 7 days) at 70% and trailing viewing hours (8–28 days) at 30%, rather than cumulative total. This prevents launch-week-dominant titles from occupying Top 10 positions for multiple weeks after peak viewership.
Acceptance criteria:
These user stories and acceptance criteria are written in the exact format used in my Williams Lea sprint backlogs — the language and structure are identical. The only difference is the product domain. This is the core argument for my OTT pivot: the BA methodology doesn't change. What changes is the problem I'm applying it to.