Fynd × NMIMS Hyderabad · case C29 · for the MBA team
An empty chair is money walking out of the salon. Refill gives a cancelled slot to the next waiting customer who fits it, only messages people who said yes, and never books two people into one chair.
On a phone, the app can be installed: browser menu → "Install app" or "Add to Home Screen".
| Rubric row | Pts | What judges look for |
|---|---|---|
| Customer and choice | 15 | One clear customer and payer, and why this is the right opportunity. |
| Business model and unit economics | 20 | Price, cost to serve, contribution per location, base and downside case, every number labelled. |
| Growth plan and experiment design | 15 | A 30-day plan with a success threshold and a stop rule; the five-role-player experiment run and recorded. |
| Product direction and delivered change | 20 | One change you asked for, that engineering actually shipped, with before and after evidence. |
| Negotiation, recruitment and team building | 15 | A log of what you asked, offered, countered and agreed, including how you joined this team. |
| Pitch and defence | 10 | Six slides, four minutes, then three minutes of questions. |
| Contribution and conduct | 5 | Each of you answers one question about your own work. |
Judges compare what you inherited with what changed because of your decisions. A polished product does not earn business points on its own. Your choices do.
For the owner
Today’s appointments per stylist. Mark a cancellation; the app says how much notice was given (under two hours is "late"). It lists who fits the empty slot, who does not and why, and sends offers only after the owner approves.
For the customer
A short message on the phone: the slot, the stylist, the service and price. Book, Not today, or Stop messages. If someone else booked a moment earlier, it says so and the customer keeps their place in the queue.
Trust
Every customer’s consent is yes, no or "not asked". "Not asked" is never treated as yes. Every action is logged with a reason and can be exported for the owner, or for an auditor.
The case card says your change is: "add service-duration and staff constraints before outreach." In version 1 the app knows how long each slot is and what kind of service it was booked for (hair, nails, skin). It does not yet know which stylist is actually in today, or that a stylist who does hair can also do a facial. So:
Check this yourself in the app, decide whether it matters to a real owner, and then ask for it (or for something better) through a GitHub issue. Engineering will reply with scope, an offer or a counter-offer.
All figures below are secondary sources or assumptions. Quote a number only with its source, or mark it "unverified".
| Product | Who it is for | Waitlist today | Price as given (verify) |
|---|---|---|---|
| Mangomint | Mid-to-large salons and spas | Express booking, virtual waiting room | $165–375/month by team size |
| Vagaro | Multi-staff salons, barbers | Waitlist tracking, email/SMS add-ons | From $30/month per calendar |
| Fresha | Independent stylists, salons | Self-booking, reminders, marketplace | Low base plus transaction and message fees |
| Zenoti (Hyderabad) | Chains and enterprise | Automated waitlist management | Custom pricing; one anecdote ~₹15k/branch/month |
| Dingg, Zylu, Salonist | Indian salons | Booking and CRM suites | ~₹1.5–3.5k/month (Dingg, vendor blog); Zylu $19–249 |
| TutorBird, Calendly | Tutors, general booking | Make-up slots on a portal; weak backfill | $10–30/seat |
So the pitch cannot be "we have a waitlist". Several do. Ours: the app checks consent, length and staff before any message, shows why each person was skipped, never double-books, and costs a flat fee per location rather than per seat.
Meta requires opt-in before business-initiated WhatsApp marketing messages. India's DPDP Act expects consent that is explicit, recorded and easy to withdraw. Refill records who said yes, when and how, and honours STOP at once. For an owner, that is less risk of a blocked WhatsApp number or a complaint.
Fill Templates/Unit_Economics.csv (Item, Unit, Base, Downside, Source or status, Formula). A starting structure:
Recovered revenue / month = refillable cancellations per week × share Refill fills × average ticket × 4.3| Input | Where to get it | Mark as |
|---|---|---|
| Refillable cancellations per week | Ask 2–3 salon owners or reception staff | observed (if asked) / assumption |
| Share Refill fills | Your role-play results; then a pilot | assumption until piloted |
| Average ticket | Salon menus (our demo uses ₹500–4,500) | source: link |
| Cost per WhatsApp message | Meta's published India rates | source: link, or unverified |
| Price per location | Your decision, anchored to recovered revenue | hypothesis |
Rule of thumb to test, not a fact: if one refilled slot is worth about ₹800, filling two or three a month pays a modest monthly fee. Your job is to find out whether owners agree.
"Test opt-in waitlist messages with five consenting role players. Record who was approached, the response and what would count as a useful result."
| If the shock is… | Trade-off to discuss | Business consequence to quantify |
|---|---|---|
| Late cancellation | Offer it urgently and accept a lower fill rate, or charge a late fee | Revenue still recoverable vs fee income vs customer goodwill |
| Staff absence | Move their bookings to other stylists, or cancel and refill later | Lost revenue per absent stylist-day; why staff-aware matching matters |
| Different service duration | Never squeeze a longer service in, or offer shorter services only | Smaller tickets refilled vs empty chair |
| Consent withdrawn | Respect it instantly, even mid-offer | Compliance risk avoided; trust as a selling point |
Synthetic demo. Kesar Salon and every person in it are invented. No real message is ever sent. Engineering guide