Personalized Entertainment Recommendations across Netflix, Hulu, Disney+, HBO Max, Apple TV+, Peacock, Paramount+, and more. Tells you exactly what to watch, builds watchlists across all platforms, and sends "last chance" alerts before content expires.
Streaming Stack cuts through the chaos of 15+ streaming services to tell you exactly what to watch tonight. You describe your mood, available time, who's watching, and what you've already seen. It recommends specific shows, builds a unified watchlist across all your platforms, tracks expiration dates, and sends alerts before content leaves a service.
User spends less time deciding what to watch and more time watching things they'll actually love. They discover cross-platform content they never knew existed. They stop paying for streaming services they don't use.
You answer 4 questions: mood (relaxed / thrilling / thoughtful / fun), time available (30 min / 1hr / 2hr+ / no limit), group size (solo / couple / family / friends), and what you've already watched (optional). Agent generates a ranked list of 3β5 specific shows/movies with: title, platform, why you'll love it, and a one-line synopsis. Not generic β specific to you.
Add anything to your unified watchlist regardless of which platform it's on. The watchlist shows: title, platform(s) where it's available, expiration warning if content is leaving soon, and a "where to watch" quick link. Filter by: platform, genre, duration, mood.
Agent monitors content leaving Netflix, HBO Max, Disney+, and others. When something on your watchlist is about to expire (within 7 days), you get an alert via email or Telegram. "Last chance: 'The Grand Budapest Hotel' leaves Netflix in 3 days." Never miss something you meant to watch.
For TV series: agent builds a "binge schedule" β how to watch a show optimally in one weekend or distributed over weeks. Shows: how many hours total, episodes per day to finish by your target date, which episodes are filler vs. critical plot.
Weekly email: "10 great things leaving your streaming services this week." Curated by humans (or vetted AI) for quality β not algorithmic churn. This is the hook that drives discovery and signups.
Premium feature: invite friends to a watch party. Syncs watchlists, suggests a movie based on group preferences, and sends a reminder. "Friday 8pm β Movie Night with Alex and Jordan: voting on 3 options now."
Monthly: "You watched 34 hours across 5 platforms. Top genre: thrillers (60%). We noticed you started 8 shows but only finished 3. Here are the incomplete ones we think you'd actually finish." Personal viewing analytics that surface patterns.
Once a quarter, agent analyzes: what did you actually watch on each service vs. how much you pay. Generates a "streaming audit": "You're paying $45/month for content you barely watch on Peacock. You'd get more value swapping it for Paramount+."
| Tier | Price | Includes |
|---|---|---|
| Free | $0 | 10 recommendations/month, basic watchlist (20 items), weekly "leaving soon" email |
| Pro | $5/month | Unlimited recommendations, unlimited watchlist, expiration alerts, binge scheduling, monthly viewing report |
| Household | $8/month | Up to 4 profiles, group watch recommendations, watch party coordination |
| Data Revenue | Free | Anonymized viewing trend data sold to studios/networks (secondary revenue, ethically sourced) |
Content licensing is not needed β we recommend content that's already on platforms the user subscribes to. The value is curation, not content ownership.
| Metric | Why It Matters |
|---|---|
| Watchlist Utilization | Are users actually watching what they add, or is it a wishlist that never gets touched? |
| Recommendation CTR | Did users click the "watch now" link? Low CTR means recommendations aren't matching mood. |
| Expiration Alert Conversion | Do users act on last-chance alerts? This is a unique feature β measure it. |
| Service Audit Saves | How many users cancel a service based on the quarterly audit? Directly shows ROI. |
| NPS | "Would you recommend Streaming Stack to a friend?" Best acquisition channel is word of mouth. |
| Risk | Mitigation |
|---|---|
| Content expiration data is hard to track | Use JustWatch API as primary source; supplement with manual monitoring for top 20 titles/week |
| Recommendations feel generic | Invest in the mood/moment matching. The "why" explanation is as important as the recommendation itself. |
| Data privacy concerns with viewing data | Explicit opt-in for all tracking; anonymize all analytics; make data deletion easy |
| Content APIs are expensive at scale | JustWatch API has usage-based pricing; cache aggressively; build proprietary metadata layer |
| Studios/networks don't want to share data | We're not their competition β we're driving more watch time on their platforms. Position as discovery layer. |