You think you have a content problem, but actually you have findability issues. 

Viewers sit down with the best of intentions, open your app, scroll past a wall of tiles, search once, sigh, and wander back to a never-ending social feed. That’s a loss you feel in watch time, in retention, and eventually in revenue.

Meanwhile, the pie keeps shifting. In May 2025, streaming alone grabbed 44.8% of all TV usage, that is more than broadcast and cable combined, which is terrific for OTT and brutal for “browse and hope” interfaces. When attention is this fragmented, the winner is whoever gets people to the right thing fastest. 

And the “right thing” today isn’t just a title. Social platforms are training audiences to expect instant relevance and mood-level precision - short, sharp, and eerily on point. That gravitational pull is real; it’s pulling time and ad budgets toward creator video. 

Here’s the awkward chart no one wants to show the board: even as video quality improved in the first half of 2025, higher bitrates, faster starts, engagement slipped in some regions. People aren’t quitting video; they’re quitting friction. 

So, let’s remove the friction.

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What intelligent search really means

Forget buzzwords. Think of intelligent search as three simple promises:

First, it understands what people mean. If someone types “uplifting sci-fi with a found-family vibe,” they shouldn’t have to guess your genre taxonomy. Modern search matches by meaning, not just matching the exact words. It’s the difference between “please the algorithm” and “please the audience.” (If you’re curious how the grown-ups do it, Netflix openly discusses how it personalizes search and blends ranking with taste. The punchline: it works.) 

Second, it searches inside the media. Every spoken word in a show or press conference becomes searchable and clickable to the exact second. Objects and on-screen text can be found, too, so “the post-match interview where the striker mentions the injury” actually takes you there. Azure’s Video Indexer and Google’s Video Intelligence ship this kind of indexing today, which means you can, too. 

Third, it respects personal taste. Two people can search for “comedy” and want entirely different nights, the best systems re-rank results based on what this viewer tends to finish, binge, and ignore. Netflix has published reams on this, and you don’t need their scale to borrow the playbook. 

When you put those three together, the app feels less like a directory and more like a concierge. And audiences react the way you’d expect: across digital products, people who search and find convert and engage far more than casual browsers—often around 2× (and sometimes more). Yes, most of the public data is from commerce, but intent is intent.

Why this moves the numbers you care abou

Time-to-first-play shrinks. Natural language works. Autocomplete helps. Empty results disappear. Viewers start watching sooner, with less second-guessing.

Sessions stretch out. Showing the exact moment that matches “Play from 12:41” turns long-form into snackable long-form. That matters on the big screen, which still dominates in-home video.

The back catalog wakes up. Smart retrieval can surface a 2017 gem that keyword tags forgot. A healthier long tail is also a quieter churn curve.

Search stops fighting recs. It joins them. You’re ranking by fit as much as by match, which feels like magic to the user and sanity to your KPIs. (If you need a sanity baseline for funnel math, Unbounce pegs the cross-industry median landing conversion rate at ~6.6%; serious search should outperform “average page” performance by a significant margin.)

How to make it real (without rebuilding your platform)

Start with the dull, important stuff: give every asset a clean, universal ID and consistent metadata. EIDR keeps versions and edits from multiplying like gremlins, and IPTC’s Video Metadata Hub 1.6 (released July 2025) adds rights fields and explicit markers for AI-created content. Boring? Absolutely. Also, the difference between “almost found it” and “found it.” 

Next, make every word searchable. Run transcripts across your catalog and keep the timestamps. Suddenly, a search for a name, line, or topic becomes a jump button, not a haystack. 

Then teach the system to see. Index on-screen text, logos, and objects so viewers can find “goal celebrations,” “blue sedan,” or “panel with Dr. Kim” even if nobody ever tagged them. This isn’t sci-fi, it’s shipping software. 

Finally, personalize the ranking. Start lightweight - boost recency and the genres a viewer actually finishes - then get fancier over time. Netflix’s public research is a practical north star for this.  

Measure the right things as you go: how many searches result in a play within 60 seconds; how long it takes to start the first stream; and how much of the viewing comes from outside your top-10% titles. If those lines trend up, you’re on the path.

A pilot that fits in a quarter

Select three to five high-value collections, sports press conferences, a talk-show archive, and a couple of evergreen series. Index the transcripts. Roll out a search that shows matching lines with “Play from…” links. Watch search-to-play jump.

In month two, add visual signals (logos, objects, scenes). Light personalization is fine; you don’t need a PhD model to move the needle. In month three, expand to the full catalog and, if desired, add a simple “ask the library” chat that provides answers with citations and timestamps, so nobody is left guessing where the information came from. Azure even ships a “prompt-ready” format for this, so you don't start from an empty page.

Where Omnisearch fits

Omnisearch was built for this exact job. It indexes video, audio, images, and documents; makes every spoken word and on-screen detail searchable; and drops you at the exact second the match occurs. It plugs into modern media stacks without a platform rewrite, and yes, it plays nicely with the metadata you already have. If your library is a city, Omnisearch turns it into a subway map with clear lines, sensible transfers, and no dead ends.

The point

In an infinite-scroll world, intent is your moat. Give people a search that understands meaning, looks inside your media, and remembers taste. They’ll reward you with the only metrics that matter: more starts, longer sessions, and a back catalog that finally pulls its weight.

Sources

• Nielsen, The Gauge™: streaming hit 44.8% of all TV usage in May 2025 (more than broadcast + cable combined). Nielsen
• Deloitte, Digital Media Trends 2025: social/creator platforms are the new center of gravity for attention and ad spend. Deloitte+1
• NPAW, Video Streaming Industry Report H1 2025: quality up; engagement down in some regions (North America details included). NPAWTV Tech
• Ofcom, Media Nations 2024: TV remains the primary in-home screen; YouTube rising on TV sets. www.ofcom.org.uk
• IPTC, Video Metadata Hub v1.6 (July 10, 2025): updated rights fields and generative-AI content markers. IPTC+1
• EIDR, the universal media identifier: de-dupe titles/edits across catalogs. eidr.org+1
• Microsoft Azure Video Indexer: time-coded transcripts; prompt-ready insights; multimodal summaries. Microsoft Learn+1
• Google Cloud Video Intelligence: labels, objects, OCR, shot changes to power visual search. Google Cloud
• Netflix research on search & personalization: from search personalization to in-session recommendations and foundation models. research.netflix.com+1Netflix Tech Blog
• Conversion context: on-site searchers convert ~2×+ vs. non-searchers (directional benchmarks). AlgoliaYahoo Finance
• Unbounce, 2024 Conversion Benchmark Report: cross-industry median landing page conversion ≈ 6.6%; useful as a baseline for funnel math. Unbounce
• Omnisearch product pages and posts: multimodal search; exact-moment playback; interactive transcripts. omnisearch.ai+2omnisearch.ai+2

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