Voice Fit Finder

For

Marketing leads at ecommerce brands and consumer startups

Solves

You spend hours scrolling feeds and pasting links into spreadsheets, only to pay for reach that never converts.

Delivers

Ranked shortlist of under 30 micro voices with plain English fit reasons

Built in

about 4 weeks of creation time, MVP in 4 days

Investment

$8,000 for the MVP, $30,000 for the full product

Run it

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

For marketing leads at ecommerce brands and consumer startups, turn product briefs, customer profiles and campaign tone into a ranked shortlist of micro voices with plain English fit reasons.

1. Describe product, customer and campaign feeling in a structured brief.
2. Crawl public social profiles across platforms.
3. Score each voice on audience overlap, comment intent and style alignment.
4. Rank voices with a one paragraph plain English fit reason.
5. Filter and sort by platform, score or audience size.
6. Export a shareable memo for team or agency.

What goes in, what comes out

The workflow

1. In
   Start with

   Product brief, customer profile, campaign tone, platform scope

2. 1

   Create a brief

3. 2

   Set platform scope

4. 3

   Run the scan

5. 4

   Review ranked voices

6. 5

   Read fit reasons

7. 6

   Filter to a shortlist

8. 7

   Export the memo

9. Out
   Finish with

   Ranked shortlist of under 30 micro voices with plain English fit reasons

AI does the heavy lifting, people stay in charge

Use language models to read months of timeline content, scoring tone, credibility and purchase signals in comments. Use vision models to assess visual style and brand fit from post images. A person checks the fit reasons and shortlist before anything is sent to a client or used in a campaign.

What your team sees

Key screens: Brief builder, voice discovery, fit scores, shortlist review. Use a dashboard with a brief form on the left, a results grid in the middle showing ranked voices with fit scores, and a detail panel on the right for the plain English reason. Filter by platform, audience overlap and tone. Save shortlists and export as a shareable memo. In this product, the first view is brief builder, followed by voice discovery, fit scores and shortlist review.

Accounts and administration

Brief ownership, scan history, saved shortlists, export logs, user roles, approval states for final shortlists, and an audit trail of scoring changes.

Integrations and data access

Public social APIs (Instagram, TikTok, X), CSV export, and later CRM and campaign management tools.

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. 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 marketing leads at ecommerce brands and consumer startups use it to solve "you spend hours scrolling feeds and pasting links into spreadsheets, only to pay for reach that never converts"?
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. Run a paid pilot with 10 ecommerce brands; baseline is their current agency shortlist quality and conversion.
4. Measure, then decide. Track shortlist to campaign conversion rate and cost per acquired customer from shortlisted voices. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One platform, one buyer type (ecommerce marketing leads), first two modules are brief builder and voice discovery with manual review of fit reasons.

After the MVP. Automate fit reason drafting, add cross-platform deduplication, and introduce a retainer tier with scheduled rescans for monthly campaigns.

What the build depends on. Access to public social data, language and vision model APIs, and a compliance layer for platform rules.

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 pricing at $1,500 per brief for a complete shortlist, with a $3,000 monthly retainer for brands running ongoing campaigns.

Message to test

Stop paying for reach you never get. Get a shortlist of micro voices who actually move your customers.

Where to find buyers

LinkedIn, ecommerce communities, influencer marketing forums, and direct outreach to marketing leads.

Lead magnet

A free sample shortlist for one platform with three ranked voices and fit reasons.

The first 30 days

1. Week 1: Build brief builder and single platform crawler.
2. Week 2: Implement scoring models and fit reason drafting.
3. Week 3: Build shortlist review and export.
4. Week 4: Test with 5 brands and refine scoring.

Paid pilot

Run a paid pilot with 10 ecommerce brands; baseline is their current agency shortlist quality and conversion. Decision to expand if 7 of 10 report a better fit and lower cost per acquisition.

Success metrics

Shortlist to campaign conversion rate and cost per acquired customer from shortlisted voices.

Retention and expansion

Monthly rescans and fresh shortlists for retainer clients, plus a history of voice performance to improve future recommendations.

Why clients would pick it

The scoring models improve with every brief and outcome, and the crawl history builds a proprietary map of audience quality that competitors cannot easily replicate.

Alternatives and positioning

Manual scrolling, agency lists, influencer platforms with follower counts. This differs by using AI to read real content and intent signals, not vanity metrics.

Main delivery costs

Cloud compute for crawling and inference, model API costs, and a small data compliance review per platform.

Limit crawling to public data, respect platform rate limits and terms, require human approval on all shortlists, and block any use of private or non-consented data. Must not scrape private accounts or share personal data without consent.