Why an EV Suitability Tool Was Worth Betting On

4 MINS

The EV Suitability Tool we shipped at Verizon Connect — the one that won the 2024 autoXreport Innovator Award — looked like an obvious feature in hindsight. It wasn't obvious going in. The first version of the pitch nearly got killed in roadmap review. Here's what actually got it through, and why I'd take the same bet again.

The problem nobody was asking us to solve

Most fleet customers were not asking us for an EV tool. They were asking for cleaner reporting, better routing, and fewer false alerts. EV suitability was a quiet, secondary concern — buried under "we'll think about it next year" energy.

But underneath the surface, three things were converging:

Regulatory pressure in California (CARB, SMOG) was about to make EV planning a board-level question.

Total cost of ownership for fleet vehicles was shifting fast, and managers had no good way to model it.

The data was already in our platform — driving patterns, idle time, route distance, dwell — we just hadn't connected it to a buy/replace decision. Customers don't always know to ask for the right feature. Sometimes the data tells you before they do.

The wrong way to pitch this

The first deck I wrote was framed as "an EV recommendation engine." It died in review. Rightly. It sounded like a science project.

The deck that survived reframed the same product as a fleet decision tool: "Help our customers identify which vehicles in their fleet should *not* be replaced by an EV yet." That negative framing — telling them what *not* to do — was suddenly something a fleet manager could imagine using on a Monday morning.

Same model. Same data. Different story. Different fate.

What I learned from the launch

Once it shipped, three things surprised me:

Adoption was driven by curiosity, not urgency. Managers used it to explore, not to decide. That's still useful — exploration drives the next decision.

The award helped sales more than marketing. A third-party "innovator" badge gave AEs a reason to bring the topic up cold. We underestimated that.

The first +15 DAU were not the buyers. They were operations leads who wanted ammunition for their next budget conversation. That changed who we built the next iteration for.

The lesson I'm carrying forward

Most product bets fail the same way: we build for the loudest user request and then wonder why nobody opens the feature twice. The EV Suitability work taught me to look at the *quietest* customer concerns — the ones nobody is escalating yet — and ask whether the platform already has the data to answer them.

If the answer is yes, that's usually where the next interesting feature lives. Not in the support backlog. In the silence.

From OMS Consultant to Product Owner — What Actually Transferred

Projjal skipped presentations and built real AI products.

Projjal Dhar was part of the March 2026 cohort at Curious PM, alongside 17 other talented participants.