Demo build on sample data

Stations, drivers and distributors in one view for a fuel retailer

A station network view, a customer agent, forecourt tools and lubricants reorders, built so leadership could click through it before anything touched their systems.

This is a demo build. It runs on sample data. We keep the company's name private.

At a glance

Demo build, sample data

Business
Fuel retail and lubricants
What we built
  • A station network view
  • Working tools to try
  • Lubricants and fleets
Fuel retail demo build: station network view with stations, pumps available, oil changes and customer rating, stations by region and a list of stations with their status. Station names blurred.
Station network, fuel retail demo.Demo build, sample data.

The problem

A large fuel retailer is really three businesses. There are the drivers who call, message and leave reviews. There are hundreds of stations, each with its own staff and forecourt. And there's a lubricants side that sells through distributors and fleet accounts.

Each runs on its own reports. Head office sees fuel volume weeks later. Calls go unanswered after hours. Most drivers who are due for an oil change are never asked at the pump. Distributors find out they're short when the shelf is already empty.

What we built

A station network view

Every station in one list with fuel against plan, its customer rating and a simple status: running well, or needs a visit. Stations are grouped by region, with a short summary of what customers praise and what they ask for.

Working tools to try

A customer agent, forecourt cameras, staff coaching, a morning report and phone-based training for new hires, each with a sample run in the demo.

Lubricants and fleets

Each distributor's stock shown as days left, a suggested reorder and a one-click reminder. Fleet customers can place an order by chat message.

What's in it

  • A ranked list of where to start, like offering oil changes at the pump, filling quiet car wash hours and keeping distributors stocked.
  • Customer agent for calls and chat: oil change bookings, fleet orders and complaints, with anything sensitive passed to a person.
  • Forecourt cameras that spot the vehicle at the pump and suggest the right service to the attendant on a tablet.
  • Staff coaching: each customer interaction gets a gentle score so managers know who to support.
  • Morning report sent to managers' phones at 7:00.
  • Review replies for every review.
  • A 90-day pilot plan: the customer agent and morning report at a small group of stations first, then forecourt tools, then lubricants, with a review together at the end.

What it would take to go live

Time with the teams. Retail, operations and lubricants, to see how stations are run, how orders come in and which reports people actually use.

Their own data. Station, sales, review and distributor data in place of the sample data, with the tools they don't need taken out.

A first version in about 10 days at a handful of stations, then out from there.

The company owns its data and the system.

See also AI for energy and utilities and the AI phone agent.

Run a station network?

Book a call and we'll show you the demo, from the network view to a distributor reorder.