Custom data collection
Web Data Collection Services
Custom data collection and structured datasets, assembled from the sources that actually answer your question.
Overview
The dataset you need rarely exists in one place
A useful dataset is usually a join. Store locations from one source, catchment demographics from a statistical agency, road geometry from an open mapping project, opening hours from map listings. Each piece is easy; making them agree on identifiers, geography and time is where projects stall.
We start from the decision you are trying to make and work backwards to the smallest dataset that supports it. That keeps scope honest and avoids paying for fields nobody will use.
The output is a documented dataset: a schema, a source note per field, a collection date and a validation report. If you later want it refreshed, extended to another country or joined to your own systems, the structure is already there.
Sample output
The same data, mapped
A static preview rather than an embedded map SDK, so the page stays fast. Interactive maps are built on request as part of a visualization project.
Scope
What a delivery includes
Every custom dataset ships with the same set of artefacts.
Schema definition
Field names, types, units, coordinate system and allowed values, agreed before collection starts.
Source register
Where each field came from, when it was collected and any access conditions that apply.
Primary dataset
The records themselves, in the formats and destinations you specified.
Geocoded coordinates
Latitude and longitude in WGS 84 for any record with an address, with match quality recorded.
Validation report
Completeness by field, duplicate handling, outliers detected and records excluded.
Coverage summary
What the dataset does and does not cover, by geography, category and time.
Change log
For recurring projects, the added, removed and modified records since the previous run.
Reproducible pipeline
The collection can be re-run on demand rather than rebuilt from scratch.
Output formats
Delivered the way your stack expects
- CSV
- Flat delivery for spreadsheets, BI tools and quick statistical work.
- Excel
- Multi-sheet workbook including the data dictionary and coverage notes.
- JSON
- Nested structures for records with repeating groups or variable fields.
- GeoJSON
- Geographic delivery for anything with coordinates or geometry.
- Database or warehouse
- Direct load into PostgreSQL/PostGIS, BigQuery, Snowflake or object storage.
Use cases
What clients use it for
- Trade area datasetsCombine locations, road networks and population to describe who can reach a site.
- Data enrichmentAdd coordinates, categories or catchment attributes to a list you already own.
- Research corporaAssemble documented, citable collections for academic or policy analysis.
- Model training inputsProduce consistently labelled, versioned datasets for internal models.
Sample dataset
What you actually receive
Sample project data. Geocode quality is always returned so you can filter on match confidence rather than trusting every coordinate equally.
| Site ID | Address | Latitude | Longitude | Geocode quality | Population 15 min | Competitors 1 km |
|---|---|---|---|---|---|---|
| SITE-001 | 412 W Broadway, Vancouver BC | 49.26346 | -123.10389 | Rooftop | 184,200 | 12 |
| SITE-002 | 980 Granville St, Vancouver BC | 49.27906 | -123.12481 | Rooftop | 231,800 | 27 |
| SITE-003 | 3105 Main St, Vancouver BC | 49.25774 | -123.10088 | Interpolated | 148,600 | 9 |
| SITE-004 | 2288 Kingsway, Vancouver BC | 49.24463 | -123.06821 | Rooftop | 126,400 | 6 |
| SITE-005 | 1490 Lonsdale Ave, North Vancouver BC | 49.32819 | -123.07214 | Rooftop | 88,300 | 4 |
How it works
Five steps, every project
- Step 01
Tell us what data you need
Describe the decision first. The field list follows from it.
- Step 02
We define the data scope
We propose sources, a schema and a coverage definition, then agree the acceptance criteria.
- Step 03
We collect and process the data
Sources are collected, standardised, geocoded where relevant and joined on agreed keys.
- Step 04
We validate the dataset
Completeness, duplicates, ranges and spatial sanity checks run before anything is delivered.
- Step 05
We deliver the final result
Dataset, documentation and validation report, in your formats and destinations.
Projects are quoted on record volume, number of sources, enrichment depth and refresh frequency. Describe the dataset you need and you get a fixed price against a written scope.
FAQ
Questions we get asked
What sources do you combine?
Publicly available web pages, open government and statistical data, open geospatial datasets such as OpenStreetMap and national mapping agencies, map listings, and any data you provide or are licensed to use. Each field's source is recorded in the delivery.
Can you work from a list we already have?
Yes, and it is often the cheapest starting point. We clean and deduplicate your list, geocode it, then add the attributes you are missing. You keep your identifiers so the result joins straight back into your systems.
How do you measure data quality?
Against criteria agreed before collection: field completeness thresholds, duplicate rates, geocoding match quality and, where a reference total exists, coverage against it. The validation report states the achieved numbers rather than claiming perfection.
Can the dataset be updated later?
Yes. Projects are built as repeatable pipelines, so a refresh is a re-run rather than a rebuild. Refreshes include a change log of added, removed and modified records.
How do you handle personal data?
We avoid collecting personal data unless it is strictly necessary and lawful for your stated purpose. Business contact details published by the business itself are treated as business data. We do not build datasets about private individuals.
What if a field turns out to be unavailable?
We tell you during scoping if we can already see the problem, and during the pilot batch if it only appears at scale. The field is either dropped from scope with a price adjustment or replaced with the closest reliable proxy, with your agreement.
More services
Often combined with
Street View Data
Large-scale street view imagery collection, processing and structured dataset delivery.
Learn MoreSemantic Segmentation
Pixel-level image analysis that turns imagery into counted, measured classes.
Learn MorePOI Data
Business and point-of-interest records with categories, coordinates and attributes.
Learn MoreKeep exploring
Where to go next
Related services
- Web ScrapingCollect structured data from websites and public sources, on a schedule you control.
- POI DataBusiness and point-of-interest records with categories, coordinates and attributes.
- Geospatial DataLocation, road, boundary and land-use datasets, cleaned and projected correctly.
- Location IntelligenceLocation-based market, catchment and competitor analysis that ends in a recommendation.
Related reading
- How to Build a Geospatial Data PipelineMost spatial pipelines work perfectly once. The design decisions that matter are the ones that keep them working on run twenty.
- Street View Data Collection Platforms ComparedTen platforms in five families, compared for real data collection work. Coverage, documented access, quotas, licensing and permitted delivery determine whether a source can support a city-scale or global project.
Next step
Have a specific data requirement?
Tell us the geography, the fields and the cadence you need for data collection. You get a scoped plan, a sample and a fixed price before any work starts.