Short-form video research and trend library

For

Social media strategists and content teams researching short-form video

Solves

Trend, competitor and creator research is scattered across several subscriptions, so findings are hard to compare, cite or reuse.

Delivers

A searchable, permissioned research library linked to source evidence

Built in

about 4 weeks of creation time, MVP in 4 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce research time while keeping a citable record of what was found.

1. Track short-form video across TikTok, Instagram Reels and YouTube Shorts.
2. Collect views, engagement and hook-level performance data.
3. Identify and monitor viral trends by niche and period.
4. Monitor competitor accounts and their content strategies.
5. Search large video and hook libraries with AI-assisted queries.
6. Generate tailored content strategy drafts from research and goals.
7. Suggest optimal posting times from observed engagement.
8. Surface relevant hashtags and trending niches.
9. Profile creators and audience demographics for influencer discovery.
10. Measure audience response to content for brand perception.
11. Support customizable queries that scope the research.
12. Save hooks and videos into organized collections.
13. Refresh tracked content and metrics daily.
14. Expose saved hooks to AI assistants through an MCP connection.
15. Manage hundreds of videos, accounts and creators in one workspace.
16. Provide API access, custom integrations and support for large organizations.
17. Store brand positioning, audience and visual guidelines as product profiles.
18. Provide an infinite canvas and asset library for content production.
19. Compare the reviewed result with the recorded baseline and value assumptions.
20. Capture corrections and named-owner approval before consequential use.
21. Export a versioned, source-linked research brief with unresolved questions.

Everything these tools do, in one app

• Short-form video tracking Track short-form video content across platforms like TikTok, Instagram Reels, and YouTube Shorts.Found in Hookest, Shortimize, Virlo and 2 more
• Performance metrics Access detailed performance data such as views and engagement for videos or hooks.Found in Hookest, Shortimize, Virlo
• Trend analysis Identify and monitor viral trends to understand what content resonates with audiences.Found in Virlo, AdAnt AI, Syncly Social
• Competitor monitoring Track competitor accounts and analyze their content strategies and performance.Found in Hookest, Shortimize, Syncly Social
• AI-powered search Use AI to search through large libraries of viral videos or hooks for inspiration.Found in Hookest, Shortimize
• Content strategy generation Generate tailored content strategies based on research and goals.Found in AdAnt AI
• Optimal posting times Get suggestions for the best times to post to maximize audience engagement.Found in Virlo
• Hashtag and niche insights Discover relevant hashtags and trending niches to position content strategically.Found in Virlo
• Creator intelligence Get demographic profiling and insights on creators to discover authentic influencers.Found in Syncly Social
• Brand perception measurement Measure how audiences respond to content to understand brand perception.Found in Syncly Social
• Customizable queries Tailor the scope of social listening or research with customizable queries.Found in Syncly Social
• Saved collections Organize and save hooks or videos into collections for later review.Found in Hookest
• Daily updates Receive fresh content and data updates daily.Found in Hookest
• MCP integration Access saved hooks directly within AI assistants like Claude, ChatGPT, or Gemini.Found in Hookest
• Scalability Manage hundreds of videos, accounts, and creators in one place.Found in Shortimize
• Enterprise features Integrated API, custom integrations, and dedicated support for large organizations.Found in Shortimize
• Product profiles Save brand positioning, audience, and visual guidelines for reference in content creation.Found in AdAnt AI
• Infinite canvas and asset library Use a visual creation space with an asset library for content production.Found in AdAnt AI

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted platform data, competitor account lists, creator profiles, brand guidelines and research queries

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted platform data

4. 3

   Competitor lists

5. 4

   Creator profiles and brand guidelines

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   A searchable, permissioned research library linked to source evidence

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated research modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Platform data collection must respect each platform's terms and permitted access; final strategy and brand judgments remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Research query builder, Library and trend board, Brief and export. Use a filterable table for tracked videos and accounts, a trend timeline with saved collections, and a right-hand panel for metrics, creator profile and source links. Let users compare videos, hooks and periods side by side. Display draft, reviewed and approved states. Provide a shareable brief link with citations anchored to the relevant video. Make the task-specific outcome a searchable, permissioned research library linked to source evidence visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source versions, saved queries, approval states, usage allowances, query limits, export history and a rights record for collected material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Permitted platform data sources, brand asset storage, spreadsheet and document export, and AI assistant access through MCP. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   4 days

   One buyer segment, one recurring use case; first modules: track short-form video across TikTok, Instagram Reels and YouTube Shorts; collect views, engagement and hook-level performance data. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   5 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   9 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will social media strategists and content teams researching short-form video use it to solve "trend, competitor and creator research is scattered across several subscriptions, so findings are hard to compare, cite or reuse"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted research briefs per analyst hour and reuse of saved findings.
4. Measure, then decide. Track accepted research briefs per analyst hour and reuse of saved findings; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One platform set and one niche; final strategy and brand judgments remain human. Implement one approved input format, a bounded representative case set and the first two task modules: track short-form video across TikTok, Instagram Reels and YouTube Shorts; collect views, engagement and hook-level performance data. Support the third module with operator review: identify and monitor viral trends by niche and period. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported platforms and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around a searchable, permissioned research library linked to source evidence. Retain the explicit scope boundary: One platform set and one niche; final strategy and brand judgments remain human.

What the build depends on. Source data access and refresh, asynchronous collection jobs, editable version history, reviewer access and tested export formats. High-fidelity research requires qualified analyst review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One platform set and one niche; final strategy and brand judgments remain human.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined research package. Offer a monthly research allowance after repeat demand. Quote complex multi-brand or enterprise integration work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded searchable, permissioned research library linked to source evidence. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce research time while keeping a citable record of what was found. Demonstrate a concrete searchable, permissioned research library linked to source evidence using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Social media strategists and content teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample searchable, permissioned research library linked to source evidence from a small authorized input set, with a transparent calculation of accepted research briefs per analyst hour and reuse of saved findings and no promised savings.

The first 30 days

1. Week 1: interview five social media strategists and content teams researching short-form video and inspect a recent example of scattered trend, competitor and creator research.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted research briefs per analyst hour and reuse of saved findings, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted research briefs per analyst hour and reuse of saved findings. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted research briefs per analyst hour and reuse of saved findings; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs a searchable, permissioned research library linked to source evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved queries, trend examples and reviewer corrections, together with reliable delivery for a narrow research niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for social media strategists and content teams researching short-form video. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Hookest, Shortimize, Virlo, AdAnt AI and Syncly Social, plus manual platform research and spreadsheets. Compare this product with the buyer's present method on accepted research briefs per analyst hour and reuse of saved findings. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Data collection and API access, storage, reviewer hours, client revision rounds and licensed source material. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of a searchable, permissioned research library linked to source evidence. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, platform terms, creator rights and usage permissions. Named analysts approve substantive strategy changes and publication scope. One platform set and one niche; final strategy and brand judgments remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.