FitCycle Shoe Rotation

For

Operations leads at fashion rental and subscription services

Solves

Shoe subscriptions fail because sizing is unreliable and returns are costly.

Delivers

Personalised monthly shoe rotation, size-matched recommendations, managed swap logistics

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,500 for the full product

Run it

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

For operations leads at fashion rental and subscription services, turn foot photos, style preferences and wear context into a personalised monthly shoe rotation with size-matched recommendations and managed logistics.

1. Extract foot measurements from photos.
2. Predict size across brands from profile.
3. Suggest three pairs based on calendar and weather.
4. Schedule pickup and next delivery.
5. Track keep or return decisions.
6. Update profile from every outcome.

What goes in, what comes out

The workflow

1. In
   Start with

   Foot photos, style quiz answers, calendar and weather data

2. 1

   Upload foot photos

3. 2

   Complete style quiz

4. 3

   Receive size profile

5. 4

   Review monthly suggestions

6. 5

   Approve three pairs

7. 6

   Wear and swap

8. 7

   Settle keep or return

9. Out
   Finish with

   Personalised monthly shoe rotation, size-matched recommendations, managed swap logistics

AI does the heavy lifting, people stay in charge

Use vision models to estimate foot dimensions from photos and language models to interpret style quiz and calendar context. A human reviewer checks size predictions against known brand charts and confirms logistics details before dispatch.

What your team sees

Key screens: Foot scan upload, size profile dashboard, monthly rotation queue, swap scheduler, keep or return review. Use a guided upload flow for foot photos and style quiz, a profile view showing predicted sizes across brands, a queue of three recommended pairs with event and weather context, and a scheduler for pickup and delivery. Show swap status and keep or return decisions. In this product, the first view is foot scan upload, followed by size profile dashboard and monthly rotation queue.

Accounts and administration

User profiles, size prediction versions, swap history, keep or return records, logistics audit trail, and approval states for each dispatch.

Integrations and data access

Calendar apps, weather APIs, shoe brand size databases, courier and logistics systems, and payment processing.

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

   2 days

   One buyer segment, one recurring use case; first modules: foot scan upload and size profile dashboard. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

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

4. 4

   Full product

   6 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 operations leads at fashion rental and subscription services use it to solve "shoe subscriptions fail because sizing is unreliable and returns are costly"?
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. A paid pilot with one clothing rental service proves it by measuring return rate and keep rate over three months against their current baseline.
4. Measure, then decide. Track return rate per pair and keep rate per member. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One buyer, one use case: operations lead at a clothing rental service. First two modules: foot scan upload and size profile dashboard. Manual review of size predictions and swap scheduling.

After the MVP. Automate pickup scheduling, inventory forecasting, and brand-specific size corrections after the paid pilot.

What the build depends on. Vision model for foot measurement, size database across brands, logistics API, and inventory management system.

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 USD 49 per month for the rotation, plus a margin on shoes kept.

Message to test

Never buy another shoe that pinches.

Where to find buyers

Social media ads targeting busy professionals, partnerships with clothing rental services, and fashion subscription comparison sites.

Lead magnet

Free foot scan and size profile for 50 brands.

The first 30 days

1. Week 1: Build foot scan upload and size profile dashboard.
2. Week 2: Integrate brand size database and style quiz.
3. Week 3: Build swap scheduler and logistics API connection.
4. Week 4: Pilot with one rental service and manual review.

Paid pilot

A paid pilot with one clothing rental service proves it by measuring return rate and keep rate over three months against their current baseline. Decision to expand if return rate drops by 20 percent and keep rate rises by 15 percent.

Success metrics

Return rate per pair, keep rate per member.

Retention and expansion

Monthly rotation fee and margin on kept shoes keep earning after the first delivery.

Why clients would pick it

The size prediction model gets more accurate as more users keep or return shoes, and the logistics coordination data becomes harder to replicate.

Alternatives and positioning

People buy shoes online with size charts and free returns, or use generic clothing rental services. This differs by combining foot scanning, brand-specific size prediction and swap coordination in one loop.

Main delivery costs

Shoe inventory, reverse logistics, cleaning, vision model inference, and support staff.

Limit swaps per month, require photo quality checks, restrict access to size profile data, and log all logistics actions. Must not share foot measurements without consent.