Vera Fill My Books
Turning a legacy subscription into a performance-based revenue engine — designed end-to-end across 5 platforms as sole designer.
* $6M projected by Vagaro finance team based on moving businesses from 6 → 8 new customers/month at 20% fee.
The Opportunity
Vagaro had two underutilized assets sitting next to each other with no product connecting them: thousands of empty appointment slots across their business network, and 25 million consumers in their platform who had never booked with any business.
The existing solution — Get Featured — charged businesses $10/month for passive marketplace visibility. Revenue was flat, capped, and completely disconnected from actual bookings. No incentive alignment between Vagaro's success and the business's success.
Before — Get Featured
- —$10/month flat subscription
- —Passive listing placement only
- —Revenue capped regardless of bookings
- —No incentive to drive outcomes
After — Vera Fill My Books
- —No subscription — pay per result
- —20% fee on new customer bookings
- —5% fee on last-minute bookings
- —Revenue scales with business success
This isn't a UX redesign. It's a revenue model transformation that required designing an entirely new product category.
My Scope
I was the sole designer on this project from kickoff through launch — owning every surface across every platform, and every design decision that shaped how the product worked, not just how it looked.
Product Surfaces
- —Onboarding + configuration flows
- —Dashboard & performance reporting
- —Payment & deposit flows (VMS)
- —Automated promotional email system
- —Web, iOS, Android, Tablet, Paydesk
Cross-Functional Partners
- —2 VP-level engineering orgs (US + India)
- —Payments & VMS team
- —Security & compliance
- —QC — provided test case artifacts
- —Finance — revenue model validation
The Hard Parts
Two strategies, one product
"Get New Customers" and "Fill Last-Minute Openings" target different audiences, have different fee structures, and run on different logic — but share overlapping settings. How do you support two independent strategies without making the product feel fragmented or forcing businesses to configure everything twice?
Trust in attribution
Businesses needed to trust where bookings came from and why they were being charged. The moment attribution felt unclear — "did Vera actually send this customer?" — the feature gets turned off. The dashboard wasn't just reporting. It was the trust mechanism that kept businesses engaged.
Payment logic I didn't initially understand
Revenue collection was tied to deposit type (0%, 50%, 100%), timing of payment, and when Vagaro collects its fee — a matrix of interdependent states I had to fully map before I could design them honestly. Misrepresenting this in the UI would create real financial discrepancies.
Scope change with a fixed deadline
Mid-project, the promotional email system shifted from generic weekly campaigns to personalised targeting based on user behaviour, location, and booking history. The timeline didn't move. This forced an explicit P0/P1 prioritisation decision while core flows were still in progress.
Key Decisions
Enable both goals on by default
Unified configuration, not separate products
I pushed for the dashboard — it wasn't in the PRD
Mirror existing Reports patterns for trust
Build a source-of-truth for payment logic
Scope the personalised targeting to P1
The Solution
View I — Dashboard
“Is Vera making me money?”
Four top-level metrics answer the only question a business owner asks: Revenue from Vera, New Customers, Appointments Booked, Lifetime Revenue. A date filter lets businesses compare periods — except Lifetime Revenue, which intentionally ignores the filter (explained via tooltip) to prevent misattribution. The revenue breakdown shows which service categories Vera is driving.
View II — Settings
Two goals, one surface
Both “Get New Customers” and “Fill Last-Minute Openings” are on by default and configured in a single view. Each goal is independently togglable. Fee structures surface directly in each section — not in a help article.
View III — Payment Flows (VMS)
Three deposit scenarios — 0%, 50%, 100% — each with distinct fee timing and revenue collection logic. The most critical flows for Vagaro's revenue model working correctly.
Scenario 1 of 5
Business has no Vagaro Merchant Services. Vagaro takes a fixed booking deposit (Fill My Books fee). The business collects the remaining balance directly at appointment via their own processor. Vagaro never touches the remaining amount.
What I'd Change
Start with the deposit flow
The deposit × fee matrix is the most financially critical part of the product. I treated it as a later-stage design problem. In hindsight I'd align on the full payment logic in week one — misunderstanding it late created compounding rework across teams.
Validate dashboard hierarchy earlier
I made assumptions about which metrics matter most to a salon owner vs. a gym vs. a spa. I'd test whether "Revenue from Vera" or "New Customers Acquired" is actually the primary signal — the hierarchy shapes the entire trust model.
Document decisions as they happen
Other teams have since referenced patterns and artifacts from this project. The payment logic tables became QC documentation. I'd make design rationale a first-class artifact from day one — not a retrospective write-up.
What This Taught Me
Designing complex systems isn't primarily about interaction patterns. The hardest decisions were about what to show vs. hide, how to frame cost vs. value, and when to push back on scope vs. absorb it.
This was the first time I owned a feature of this commercial and technical complexity end-to-end — across 5 platforms, two engineering organisations, and a payments system with real financial consequences. It changed how I think about what “product design” means at a senior level: less about crafting the perfect UI, more about making the right decisions at every layer of a system, and building the trust that lets other teams move with confidence.
Vera AI Orchestrator
Fill My Books is one of several AI-powered features designed under Vagaro's Vera platform — an orchestration layer that brings AI-driven automation to every part of running a service business.
Auto-Create
AI generates services, memberships, and packages from natural language.
Reports Agent
Conversational insights over your own data — revenue, bookings, staff performance.
Support Agent
Context-aware support responses outperforming the existing Zendesk AI integration.
Business Health
Proactive surface surfacing anomalies, opportunities, and benchmarks.
Full case study available on request.