# Location and scope

A place narrows which organisations are collected before any research money is spent, so it is the highest-leverage line in a search. Widening it does not return proportionally more good prospects: it returns more candidates competing for the same research budget, each getting a thinner pass. A city usually beats a country on both count and quality of what you can actually write to.

- **Status:** Available
- **Audience:** both
- **In the app:** #/prospects
- **Last verified:** 2026-09-10
- **Canonical:** https://connectbyjbrh.com/docs/prospects/location-scope/

## What a place is taken to mean

A location is read as the area a business serves or trades in, taken from what that business publishes about itself — a listed address, a stated service area, a regional office. It is not a coordinate lookup, and Connect does not assert a distance it cannot source.

That has one consequence worth knowing up front: a business that operates in your city but publishes only a head-office address elsewhere is collected under the head office. This is a limit of public sources rather than a judgement, and it is why a trade with many franchise operations often reads oddly against a tight area. Where the evidence is ambiguous the ambiguity is recorded rather than resolved by assumption — see [Evidence on a prospect](/docs/prospects/evidence/).

## The real cost of a wide area

The instinct is that a wider area is strictly better: same work, more results. It is not, because research spend is finite and routed. A candidate set ten times larger does not get ten times the budget; it gets the same budget spread thinner, and the router responds by running the deeper pass on fewer of them.

| Effect | Narrow area | Wide area |
|---|---|---|
| Candidates collected | Fewer, mostly relevant | Many, mixed relevance |
| Depth of research per candidate | Deeper on more of them | Shallow on most, deep on a few |
| Contactability rate | Higher — local sources are richer | Lower — thinner sources per business |
| Fit reasons | Specific and checkable | Generic, because less was read |
| Time to a first usable message | Shorter | Longer, with more to triage |

The counter-case is real: a niche trade that has four practitioners in one city has to be searched regionally or it returns nothing. Widening is the right move when the population is genuinely thin, and the wrong move when you are trying to make a list longer.

## Choosing an area

1. Start with the area you would actually serve, deliver to or visit.
   - Result: Every prospect that comes back is one you could accept if it said yes, so nothing in the list is wasted attention.
2. Read the first ten fit reasons before widening anything.
   - Result: If they are specific, the area is working. If they are vague, the problem is the trade wording, not the size of the map.
3. If the run is thin, widen once, by one step — a district to a city, a city to its metropolitan area.
   - Result: You can attribute the change. Widening two things at once tells you nothing about which one mattered.
4. Keep separate areas as separate searches rather than one large one.
   - Result: Each keeps its own counts, its own fit reasons and its own budget, and a bad market can be retired without disturbing a good one.

## Places that behave badly

**A city name that exists in several countries** — Add the region or country. Without one, collection includes the wrong hemisphere and qualification spends money proving it.
**A district nobody publishes** — Businesses list the city, not the neighbourhood, so a district filter matches almost nothing. Use the city and let qualification weigh the rest.
**A whole country** — Legal for the search, expensive in practice: a national population dilutes research per candidate and the contactable share falls.
**An area with a different working language** — Sources exist but are read less well, and the fit reasons show it. Treat a language boundary as a separate search rather than a wider one.

> **Careful** Widening the area is the most common reaction to a disappointing run and the least likely to fix it. If the businesses that came back were the right kind and simply had no address, the constraint is contactability, not geography — see [A good prospect has no address](/docs/troubleshooting/prospect-no-email/).

## Questions

### Does a wider area cost more money, or the same money spread further?

The same budget, spread further. Research spend is routed to where it can change a decision, so a larger candidate set means the deeper pass runs on a smaller share of it. The bill does not jump; the average depth per candidate falls.

### Can I search one area and exclude part of it?

Exclusions belong in the criteria as disqualifying properties rather than as geometry. Naming what disqualifies is more reliable than carving a shape, because a business is matched on what it publishes about itself and it may not publish anything that resolves to your carve-out.

### Why did a business in my city not appear?

The usual reason is that its published address is elsewhere — a head office, a registered office, or a parent company. Adding it directly keeps the record and the research; see [Uploading your own list](/docs/prospects/prospect-upload/).

## Related

- [Describing who you want to reach](https://connectbyjbrh.com/docs/prospects/discovery-criteria/)
- [Collecting candidates](https://connectbyjbrh.com/docs/prospects/candidate-collection/)
- [What prospecting costs](https://connectbyjbrh.com/docs/prospects/prospect-costs/)
- [Prospecting in Connect](https://connectbyjbrh.com/docs/prospects/)
- [Spending research budget where it changes a decision](https://connectbyjbrh.com/research/research-cost-routing/)
- [Discovery returned nothing](https://connectbyjbrh.com/docs/troubleshooting/no-prospects-found/)

## What this page is based on

- docs-source/sources/CHANNELS.md §4 — discovery, collection and cost routing
- `docs-source/facts.py` — CAPABILITY_STATUS prospect_discovery
- Connect capability registry (docs-source/facts.py)
