Methodology

How OneGoodArea scores an area.

Every score is built from real data. Same postcode, same answer. This page is the plain-English record of what the engine reads, what it weighs, and what the AI layer is (and isn't) allowed to do.

Data sources

Seven public sources, one report.

Every report is built from seven live UK government and open data sources, fetched in parallel at the time of request. No cached data. No estimates. No surveys.

Postcodes.ioONS / Royal MailPoint lookup

Geocoding (latitude/longitude), LSOA code and name, local authority, ward, constituency, and region. Acts as the entry point for all other lookups.

Police.ukHome Office1 mile

Street-level crime incidents from the last 3 months, broken down by category (theft, violence, burglary, and so on). Includes monthly trend data for direction-of-travel analysis.

ONS / IMD 2025MHCLG via ArcGISLSOA boundary

Index of Multiple Deprivation. Ranks 33,755 Lower Super Output Areas across income, employment, health, education, and living environment. Decile 1 = most deprived, decile 10 = least deprived.

OpenStreetMapOverpass API500m to 2km

Nearby amenities: schools within 1.5km, food and shops within 1km, transport stations within 2km, bus stops within 500m, parks and healthcare facilities.

Environment AgencyDefra3km / 5km

Flood risk zones within 3km, active flood warnings within 5km, and identified rivers at risk. Data is fetched live per request.

HM Land RegistryPrice Paid DataPostcode district

Actual sold prices from the last 12 months via SPARQL query. Median and mean prices, year-on-year change, property type breakdown (detached, semi, terraced, flat), tenure split, and price range.

OfstedDepartment for Education1.5km

School inspection ratings (Outstanding, Good, Requires Improvement, Inadequate). England only.

Intent types + dimension weights

Four intents. Different priorities.

The intent determines which dimensions are scored and how they are weighted. Different use cases care about different things. Moving prioritises safety and schools. Business prioritises foot traffic and spending power.

Weights are calibrated internally and are not published.

movingMoving· Residential relocation
  • Safety
  • Schools
  • Transport
  • Amenities
  • Cost of Living
businessBusiness· Commercial viability
  • Foot Traffic
  • Competition
  • Transport
  • Spending Power
  • Commercial Costs
investingInvesting· Property investment
  • Price Growth
  • Rental Yield
  • Regeneration
  • Tenant Demand
  • Risk Factors
researchResearch· General area profile
  • Safety
  • Transport
  • Amenities
  • Demographics
  • Environment
Scoring functions

How each dimension becomes a number.

Each dimension has a dedicated scoring function. Inputs go in, a number between 0 and 100 comes out. No randomness. No AI-generated numbers. Below is a plain-English breakdown of what each function considers.

Core dimensions
SafetyMoving · Research

Uses the last 3 months of police.uk crime data. Rising crime is penalised, falling crime is rewarded, and violent crime concentration is weighted appropriately.

TransportMoving · Business · Research

Rail and bus connectivity combined into a single accessibility score. Benchmarked against area type so rural postcodes are judged against other rural postcodes.

SchoolsMoving

School and educational facility density nearby, with a diminishing returns curve. One good school matters more than many middling ones.

AmenitiesMoving · Research

Weighted composite across education, food and drink, healthcare, retail, and green spaces. Each category normalised against area-type benchmarks.

DemographicsResearch

Official deprivation indices (IMD for England, WIMD for Wales, SIMD for Scotland). Maps decile ranking to a score that reflects the socioeconomic profile of the neighbourhood.

EnvironmentMoving · Research

Combines flood risk zones, active flood warnings, and green space availability. Areas with no flood risk and good park access score highest.

Cost of LivingMoving

Uses Land Registry sold prices as the primary input. Scored as a ratio of local median to national median. Falls back to deprivation data when price data is unavailable.

Business intent · derived dimensions

Business reports use derived scores that combine transport, amenity, and deprivation data into commercially relevant metrics.

Foot Traffic

Transport connectivity combined with commercial activity density. Strong rail, bus, and retail presence indicates higher natural footfall.

Competition

Measures commercial saturation nearby. Lower density scores higher. Useful for identifying underserved areas with unmet demand.

Spending Power

Derived from deprivation indices as a proxy for local disposable income. Correlates with footfall quality, not just volume.

Commercial Costs

Uses Land Registry property values as a proxy for commercial rents and overheads. Higher local property prices mean higher commercial costs.

Investing intent · derived dimensions

Investing reports combine deprivation data, transport connectivity, crime statistics, and flood risk into investment-focused metrics.

Price Growth

Real year-on-year price changes from Land Registry. Moderate growth scores highest, sharp declines and flat markets score lower.

Rental Yield

Uses Land Registry median prices as the yield denominator. Adjusts upward for strong local amenities and transport that drive tenant demand.

Regeneration

Development potential. Higher-deprivation areas with good transport links score highest. Already-developed premium areas score lower.

Tenant Demand

Composite of transport connectivity, local amenities, bus coverage, and commercial activity.

Risk Factors

Crime and environmental risk combined into a single downside metric. Active flood warnings or elevated crime see significant reductions.

Role of AI

What our AI engine does (and doesn't).

The numbers on a report are computed. The words around them are written. Those are two different jobs, and our AI engine only does the second one.

The pipeline
01
Fetch data

Seven APIs queried in parallel for the target location.

02
Compute scores

Every dimension scored from 0 to 100 by its own function.

03
AI narrates

The AI engine receives the scores and the raw data, and writes the report.

04
Numbers protected

Any AI-generated numbers are replaced server-side with the computed scores before the report is saved.

AI does / AI doesn't
AI does
  • Writes the executive summary
  • Authors the detailed analysis sections
  • Generates actionable recommendations
  • Interprets raw data points in context
  • Explains what the scores mean for your use case
AI doesn't
  • Sets or modifies any numerical score
  • Chooses dimension weights
  • Invents data points or statistics
  • Overrides the scoring engine
  • Influences the overall OneGoodArea score
Numbers protected server-side

Even if the AI model returns different numbers in its response, the server replaces them with the pre-computed scores before the report is saved. The numbers you see are always the output of the scoring engine.

Overall score

One number, keyed to your intent.

The overall OneGoodArea score is a weighted average of all dimension scores for the selected intent. Each dimension contributes proportionally to its internally calibrated weight. The result is a single 0 to 100 number representing how well the area suits your stated purpose.

How it works
  • Each dimension is scored independently from 0 to 100.
  • Dimensions are weighted according to the selected intent.
  • The weighted scores are combined into a single overall score.
  • The same postcode with the same data always produces the same number.
Score scale

Green, amber, red. Three bands.

Scores are colour-coded using a Red / Amber / Green system across every report. This applies to both dimension scores and the overall OneGoodArea score.

70 – 100Strong

The area performs well in this dimension. A strong foundation with no major concerns. For overall scores, this indicates a highly suitable location for your stated intent.

45 – 69Moderate

The area is adequate but has room for improvement. Some trade-offs to consider. Worth investigating further before making decisions.

0 – 44Weak

The area underperforms in this dimension. Significant challenges identified. Does not necessarily disqualify the area, but indicates a specific weakness worth understanding.

A note on interpretation

A low score in one dimension does not make an area unsuitable. Context matters. A business location with a low competition score (meaning heavy saturation) might still succeed with strong differentiation. Read the narrative sections alongside the numbers.

See the engine in action.

Run a free report for any UK postcode. Read the numbers, read the reasoning, decide.

Try a postcodeRead the API docs