Uber-Like Negotiable Service for Mobile Car Washing
A Negotiable Service Platform for Mobile Automotive Detailing
UBER
BACKGROUND
The Why
Mobile services are the future of local commerce. However, trust and reliability are major blockers. With gig economy models working well for transportation and food, the same principles can apply to car washing—with added flexibility and safeguards.
The Process
RESEARCH
Desk Research
Based on sources, in particular The Digital Project Manager, here were the three main pain points:

Missing Trust Mechanisms
Needing to switch platforms frequently broke user flow.

Rigid Pricing Structure
The absence of a dynamic negotiation or counter-offer model limits flexibility and discourages user engagement.

Poor Geolocation Relevance
Lack of state- or region-specific filtering reduces match accuracy and leads to irrelevant service listings.
Gig Economy Trends
There’s a growing demand for on-demand services outside traditional verticals like ridesharing and food.
Trust in Peer Services
Trust is the leading factor when booking mobile services. Features like ratings and media significantly increase conversion.
User Retention Factors
Customers who engage in flexible negotiation stay longer due to perceived control and fairness.
RESEARCH
Competitor Analysis
We benchmarked against industry-leading retailers with modern omnichannel platforms:
Spiffy
Pros
Professional branding
Streamlined service booking
Cons
No negotiation features
Only fixed pricing
Washer
Pros
Real-time booking
Mobile app ease of use
Cons
No provider vetting
Lacks dispute process
MobileWash
Pros
Real-time booking
Mobile app ease of use
Cons
No provider vetting
Lacks dispute process
Synthesis
User Persona
To stay grounded in the real-world needs of my target audience, I created a user persona based on research interviews and common patterns I observed. This helped me make product and engineering decisions with a clear user in mind. The following persona represents a typical mobile detailing business owner who would use the platform day-to-day.
Carlos Rivera
LOCATION
Phoenix, AZ
EDUCATION
Associate Degree in Business Management
EXPERIENCE
+6 Years
Goals
Expand business reach without hiring salespeople
Needs
A platform that gets him new jobs, protects against no-shows
Pain Points
Difficulty in building trust with new customers, waste of time on fake requests
Synthesis
User Journey
Carlos Rivera
Scenario:
Carlos signs up for the platform to streamline his daily operations and increase bookings.

Starting
Signs up and uploads past work photos

Trying
Gets notified of a nearby client offer

Conflicting
Client counters his price offer with a lower one

Quitting
Sends a new counteroffer and lands the deal
IDEATION
Developing a Solution .1
Features Created
Scam prevention measures added
To complete an order, service provider must provide before and after pictures
Users are protected by being allowed to dispute if a job was not done.
Users are protected by being allowed to dispute if a job was not done.
Guarantee payment to service provider by pre authorizing customer credit card
Daily payouts
Daily cron jobs to check who is eligible to get paid out - email sent out to those getting paid out
User Bot Prevention
Utilized Google SSO to filter out bots
Rate Limit protection
Profile Building
Service providers can showcase their past work
Show reviews from past customers on the platform
Display services offered and general price
Chat Rooms and Privacy Protection
Allow to quickly chat with each other without exposing each others phone numbers to each other
Business Own-Employee Management
Allow businesses to give Users “employee” level access, allowing them to only accept offers / give counter offers
Negotiation
Allow users to compete for a better price.
Allow businesses to adjust prices based on their day.
During the negotiation phase, businesses can add-on more products and services and build a complex deal just for one customer – allowing businesses to have upsell opportunities.
Multi State Backend Abstraction
Handle requests handled by different State-Level Frontend Applications
Reason: Isolate areas to state level to allow communities to build up properly with relevant information related to where they live / do business.
Multi Business Types Backend Abstraction
Using the same business model, can apply it to the same backend, apply it to other verticals, eg: Dog Grooming, and Boat Washing
IDEATION
Developing a Solution .2
Order Flow
1. Negotiation Phase
2. Client creates an offer, selecting some common services provided by all service providers
3. Backend receives and sends out an Email using AWS SES to all relevant service providers
4. Service providers
Accept the offer / Sends Counter Offer
5. Client
Sends counter offer
Accepts and goes through pre-authorization flow with Stripe
6. Service Phase
7. Service provider
a) Completes the job - Provides Evidence
b) Reports the job - Provides Evidence → gets 50%
c) Contact client via chat room
8. Client receives email that job is completed
Client receives email that job is completed
9. Review Phase
10. Client can leave a review
11. Business can use previous work media on their business profile to show off
Flow Chart
Code Snippet
IDEATION
Future Explorations - AI

Voice Assistant Integration
Voice-enabled booking via Alexa or Google Assistant

Drone-Based Pre Inspection
Use camera drones to preview vehicles for large fleets or premium services

Loyalty Program Gamification
Points and tiered rewards to incentivize repeat bookings