You have the funding. We show you exactly where to spend it.

You’re targeting 200 neighbourhoods with limited budget. Pick wrong and you waste public money on low-impact areas — and you can’t justify it to your funder. We score every neighbourhood in your area and hand you a ranked shortlist, with the evidence your board needs, within 24 hours.

Get your free ranking →

6,800+ areas scored 24hr turnaround First one free

6,800+ neighbourhoods scored across England

What you get

This is what your targeting decision looks like.

Greater Manchester, retrofit priority. Instead of guessing or spreading funding evenly, you see exactly which neighbourhoods need it most — and why. Every score is backed by published data your funder can verify.

#	Neighbourhood	Priority score	Key factors
1	Coldhurst & AlexandraOldham	94	Fuel poverty 28%, pre-1919 housing 47%, EPC E–F dominant
2	Milkstone & DeeplishRochdale	91	Fuel poverty 26%, solid-wall construction, high vulnerability index
3	HalliwellBolton	87	Fuel poverty 24%, pre-1919 terraces, EPC D–E band
4	Ashton St Peter’sTameside	84	Fuel poverty 22%, low-income concentration, ageing stock
5	BroughtonSalford	79	Mixed tenure, retrofit investment gap, fuel poverty 20%
6	ScholesWigan	72	ECO-eligible stock, housing age profile, fuel poverty 17%
7	EastBury	65	Moderate need, mixed EPC profile, some newer stock
8	Bramhall SouthStockport	41	Lower priority, post-1980 housing, fuel poverty 9%

Get this for your area — free →

Two decisions we solve

Different questions, same answer: a ranked shortlist that replaces guesswork with evidence.

Retrofit targeting

“We have WH:LG funding but we don’t know which neighbourhoods to prioritise.”

You get a ranked list of every neighbourhood in your area, scored by fuel poverty, housing age, EPC ratings, and vulnerability. The top 20 are where your funding will have the most measurable impact — with the evidence to prove it to DESNZ.

For local authorities, housing associations, and retrofit installers.

Site selection

“We’re expanding but we don’t know which locations will perform.”

You get a ranked list of potential locations, scored by catchment population, accessibility, competitor density, and growth trends. The top picks are where your next site is most likely to succeed — before you sign a lease.

For operators, franchise groups, and commercial property teams.

Why the numbers hold up

Every score is built from published government data — the same sources your funder or board already trusts. No black boxes, no proprietary indices. You get the methodology and the raw numbers so anyone can verify.

ONS Census 2021 EPC Register BEIS fuel poverty IMD 2019 OS OpenData DLUHC housing stats DfT accessibility

Built by Jules Buckland

Spatial analyst, Manchester. Background in causal impact evaluation and neighbourhood-level data modelling.

Buro Happold spatial analytics — causal evaluation of pedestrian footfall using difference-in-differences with matched comparison sites
Full-stack data pipeline: Python spatial processing, R statistical modelling, interactive dashboards
PPE, University of Manchester