heywatt - Going electric

heywatt - Going electric

heywatt - Going electric

Timeline

2025

Team

French market stakeholders, 2 devs, 1 PM (Nathalie), Head of Product; input from other markets for future portability

Client details

heycar is a European digital platform for buying and selling used and nearly-new cars. It connects buyers with selected dealerships, prioritizing inspected vehicles with verified history and warranty to deliver a simple and transparent purchase experience. Founded in Germany and later expanded to other countries, it stood out for raising quality standards in the market and for being backed by Volkswagen Financial Services.

Overview

With new government legislation on the horizon and growing EV interest in France, heycar saw an opportunity to become the go-to EV destination—not just to improve the user experience, but to compete in a space dominated by larger incumbents.

Problem

heycar wasn’t originally built for EVs. What shoppers look for in an EV (and how they evaluate it) differs from ICE vehicles, and much of that data wasn’t available, reliable, or surfaced in the UI. There was no easy way to search for EV-specific features, and key decision inputs (e.g., range, running costs, subsidies) weren’t prominent. The French team proposed a phased approach to grow into a credible EV hub.

Approach

  • Cross-market alignment for an MVP. Partnered with PM (Nathalie) and French stakeholders (with Amélie as our primary counterpart) while validating portability to other markets. Broke the vision into a scoped MVP with a clear path to Phase 2.

  • User signals first. Identified the must-know information users need before committing to an EV: range, running cost, trust signals, and how finance/subsidies change the total cost to own.

  • Data feasibility. Audited 3rd-party data providers to confirm what we could reliably ingest and display ([info needed: providers used]).

  • Information architecture & copy. Defined where EV content lives (landing → browse → PDP), wrote plain-language labels and explanatory microcopy, and planned progressive disclosure for technical/legislative details.

Experiments

We ran a survey with ~200 French users (UserTesting.com) to understand EV intent, perceptions, and information needs.

What we learned: 


  • Low trust in older/1st-gen second-hand EVs; higher trust in newer-gen EVs and hybrids.

  • Range is the top decision driver.

  • Running costs matter (electricity vs. fuel, maintenance).

  • Reviews (expert/user) and friends’ opinions influence decisions.

  • Finance and government subsidies help close the gap.

Solution

MVP (Phase 1)


  • A dedicated EV landing page as the journey entry point—initially a focused gateway, evolving into an EV hub with articles, videos, promos, and benefits.

  • PDP EV section that surfaces what matters: range, estimated running cost, battery/age signals, and clear pointers to subsidies/finance. Included a cost comparison against a user’s current car.

  • Content & taxonomy groundwork for later EV browse/search enhancements.


Planned Phase 2 (direction)


  • EV-specific filters and tags (e.g., battery size, WLTP range bands, charging type).

  • Education modules (charging basics, battery health, winter range).

  • Tools (TCO calculator, subsidy eligibility checker).

  • Cross-market rollout plan.

What I did

  • Led the MVP definition with PM and stakeholders; translated the vision into flows, IA, and scope.

  • Ran the data audit with engineering to confirm feasible EV attributes and safe defaults.

  • Designed the EV landing and PDP EV module, with plain-language copy and progressive disclosure.

  • Set up the content model (hub structure, article types, promo placements) for ongoing EV education.

  • Defined the measurement plan and Phase-2 backlog (filters, tools, content).

Learnings & Next

  • Trust is fragile in second-hand EVs; surface range, running costs, and credible signals early.

  • Subsidies and finance context reduce uncertainty—place them where decisions happen (browse/PDP), not just in articles.

  • Data quality (freshness, coverage) dictates UX; bake in fallbacks for missing/ambiguous EV attributes.

  • Once the MVP is stable in FR, iterate per market to match local regulations, incentives, and user behaviour.

Notes

Although heycar.com/fr is currently online, FR market has since been wound down by VWFS so full implementation has been disabled and data on results unavailable.

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That's all for now

Need to get in touch?

All rights reserved.

Site made by me from scratch with Framer.

That's all for now

Need to get in touch?

All rights reserved.

Site made by me from scratch with Framer.