How ready is this household for an EV?
Band A-E with the reasons.
Automotive & fleet · open data insight
Who can charge at home, what they pay at their nearest pump, which dealer they can actually reach. The data to answer all of that has always been in UK open data. Hyper-Geo's algorithms turn it into answers and append them to every driver on your list, so each campaign speaks to their situation, not an average.
WF2 9AA
Fleet depot, Wakefield
21
Insights for this sector
Each with its own confidence
20+
UK data sources
Official and public, combined into one view
1.8m
Live UK postcodes
England, Wales, Scotland, Northern Ireland
100k
Contacts per job
Insight appended in minutes
Open data, brought to life
Type it in plain English. We will tell you straight whether we can answer it from UK open data, how our algorithms work it out, and exactly what gets appended to every contact.
Or pick insight we already append
Built for
The reality
Car buyers are not one audience. A detached house with a driveway and two cars is a different conversation from a city flat with on-street parking. Without that context, campaigns default to the same message for everyone and the budget follows.
01
Pushing home charging to people in flats wastes the spend and the goodwill.
02
Postcode radius ignores motorways, rivers and the actual drive. Customers go to the one that is easiest to reach.
03
A 15,000 mile driver saves very differently from a 5,000 mile one. Most lists cannot tell them apart.
What it changes
01
Lead with the households most likely to switch, and give the rest a reason that fits them.
02
Allocate every contact to the showroom they can reach fastest, by real drive time.
03
Quote what switching would save a year, worked out from local fuel prices and their likely mileage.
04
Find multi-car households, long commuters and high-mileage areas before you brief a campaign.
The insight we append
Each one is built from UK open data by our own algorithms. Swipe through them and open any to see where it comes from, how our algorithms work it out, step by step, and the model we use. Every answer arrives with its own High, Medium or Low confidence, and you pay only for the insight you tick.
Band A-E with the reasons.
Likely, Possible or Unlikely, from driveway likelihood.
Pounds per year versus local petrol prices. Negative means EV costs more.
Good, Patchy or Poor, plus the nearest rapid charger.
% of homes with solar.
Needs your dealer list.
Nearest forecourt, drive time and local average E10 price.
Band A-E.
Yes, Maybe or No.
Yes or No, from Census car ownership.
Census average.
Yes or No, from households with children.
Yes or No, 30%+ aged 65 or over.
Yes or No.
Yes, Likely or Unlikely.
Gigabit, Ultrafast, Superfast or Slow.
Band.
High, Medium or Low.
Yes or No, 25%+ commuting 30km or more.
High, Some or Low.
Good, Mixed or Weak, from indoor 4G across all four networks.
A real example
Three real postcodes run through the platform. Every answer sits next to its confidence. A negative saving would mean an EV costs that household more.
| postcode | ev_ready | home_charging | ev_saving_gbp | nearest_dealer | dealer_min | mileage_band | confidence |
|---|---|---|---|---|---|---|---|
| LS17 0AD | B | Likely | 1,700 | Leeds showroom | 28 | 15,000+ mi | High |
| GU1 3JR | A | Likely | 1,190 | London showroom | 44 | 10,000 to 15,000 | High |
| M14 6ZT | C | Unlikely | 10 | Leeds showroom | 61 | 5,000 to 10,000 | High |
Scroll the table sideways on a phone. The full file has one column per insight and one confidence column for each.
How it works
01
CSV or Excel, up to 100,000 contacts. Names and postcodes are all we need. Anything else you carry through stays yours.
02
Pick your sector and tick the questions you want answered. We have already worked out how to answer each one. Choose how closest is measured: straight line, road distance or drive time.
03
Your file back in minutes with the insight added to every contact, each answer next to its confidence, ready for your CRM or campaign tool.
Your own locations
Upload your dealer or service centre list with your customer list. Hyper-Geo finds the closest to every driver, by straight line, road distance or real drive time, and appends the details you choose. Route every lead to the right dealer and name it in the message.
| contact | branch_1_name | branch_1_drive_min | branch_1_miles | branch_1_phone | branch_2_name | branch_2_drive_min |
|---|---|---|---|---|---|---|
| Sarah Holt | Leeds North | 14 | 6.2 | 0113 496 0000 | Harrogate | 21 |
| James Barker | Guildford | 9 | 3.4 | 01632 960 000 | Woking | 17 |
Closest, measured properly
For one in five UK postcodes, the closest petrol station by road is a different one from the closest as the crow flies. Rivers, estuaries and motorways see to that. Choose how closest is measured, job by job.
As the crow flies. Fast and fine for broad targeting. Drive times shown are estimates.
The nearest place by the actual distance you would drive, on the full UK road network.
The nearest place by how long it takes to get there. The most accurate answer to "closest".
Try it now
The same data a fleet or fuel card job uses. Five free checks a day.
Five checks a day per visitor. These are the real numbers, from the same data a paid job uses.
Where the insight comes from
Access is by approved work domain. Tell us who you are and we will set up your company, agree a rate and append insight to your first 200 contacts free.
Request access