AI and machine learning >

Whocanfixmycar.com

Whocanfixmycar.com is the UKs no1 car repair comparison site. Its a web app for garages to win work and drivers to compare prices, reviews and availability and then book in with garages.

We partner and intregrate APIs from affiliates including:

    Website traffic

  • 1m+ Driver visits per month
  • 16k+ Garages per month

Growing conversion and revenue

I was hired as the first UX/UI designer at whocanfixmycar.com. I installed a user centric design process and methodologies to increase KPIs and revenue. I work on creating a culture of feedback, iteration and a user centered design focus.

My Role: Lead Product Designer

Duties: User research, UX design, UI design, Interaction design, Lead and establish user centric processes

    Acheivements to date

  • Funnel conversion +44%
  • Revenue from product +102%

Installing user centric design processes

I set up a user a user centric design processes to product development, continuous iteration, idea generation and involving the whole company in creating a customer focused product, you increase user satisfaction, increase conversion and lifetime value.

EmpathiseIterateDefinePrototypeTest

Empathise, Define, Iterate, Repeat

Using small releases, MVPs and research I increased user engagement and thus increased revenue in a measurable and defined manner.

Empathise and discovery
  • Talking to users
  • Guerilla research
  • Real personas
  • User testing (remote and in person)
  • Interviews
  • Surveys
Define and analyse
  • User stories
  • Problem statements
  • Affinity diagrams
  • Workshops, brainstorms, mind maps
  • Prioritisation matrix
  • Define KPIs

"Talk to users, define and prioritise improvements, set metrics to measure success"

Main processes
Design, prototype and iterate
  • Sketch on paper
  • Userflows
  • Interaction design
  • Wireframes
  • Prototypes
  • UI design
Measure success
  • Google analytics, hotjar
  • Customer Satisfaction tracking
  • Data analysts
  • KPI and conversion monitoring
  • A/B testing
  • User testing, feedback and review

Planning and communication

Using the research we have gathered over time I create a backlog of tickets that then get prioritised using a prioritization matrix. These range from quick wins and small iterations, to larger projects that require a MVP, prototyping and iterate on. Liasing with the devs is with Jira and Teams as a communication tool.

“With 12 developers based in Kiev communication alongside defined specs and project understanding are important. We use jira and teams for communication and management.”

Communication

Using data in product design

I use data to monitor closely how the product and release are performing and to define improvements. It allows us to monitor all areas of the site and performance and watch out for shifts in behaviour and usage. The product team knows an any point how close we are to hitting targets and how tests are performing.

"KPIs, funnel performance, product improvements and measuring sucess are all part of our product design processes"

Measure success

Data to define improvements

Product design works closely with the data department to get reports and findings of releases and iterations.

  • Granular data reports
  • Usage of features
  • Data analyst team

Data to Measure success

Tracking sucess is easy if you set up early what you are aiming for.

  • Google analytics, hotjar
  • Customer Satisfaction tracking
  • KPI tracking

Leading product design

As the sole product designer in the product team its my job to keep the user at the center of focus not only within my team but also within the company. Creating an atmosphere of feedback learning with also balancing business and user needs.

Company buy in

  • Workshops
  • Beers and ideas
  • Learn it lunches

Feedback culture

  • Hands up meetings
  • Show and tell
  • All teams involved in feedback

Combine goals

  • Business goals
  • User needs

Design system

    • Keep designs unified
    • Speed up dev deliverables

“I have installed a culture of iteration, continuous feedback and testing”

Design culture

Key Milestones

We are constantly interating and refining

AI and machine learning

Give 86% of jobs posted 5+ instant accurate price (Currently 35%) and to increase acceptance rate to 25% View more details

“Give drivers an instant and accurate quote, and allow garages to view and edit their quotes at any time.”

Problem statement
  • Jobs with a quote generated +140%

Reduce leakage in the funnel

One of the areas of leakage we have identified in the funnel is receiving a quote from a garage and then clicking choose a garage. View details

"Allow drivers to book in with a garage based on their availability"

Problem statement:
  • Acceptance rate +30%
  • Refund rate -80%

Increase funnel conversion

We originaly had one core funnel, after introducing 70+ new funnels are setting individual targets we saw a increase in posting rates.

  • Core Funnel conversion +44%
  • Smaller funnels +14% - +25%

Increase acceptance rates

With extensive A/B testing and reworking flows and quote tiles we saw a rise in acceptance rate.

  • Acceptance rate +30%

Conversion increases

Increases in the product KPIs to date.

  • Funnel conversion +44%
  • Jobs generated +89%
  • Acceptance rate +30%
  • Quotes provided +127%
  • Product related revenue +102%
AI and machine learning >
© Will Forsyth