Google Maps extractor: what a full extraction run involves

How do you run a Google Maps extraction?

Lead Finder runs an extraction in six steps, and the order matters more than the tool. First, choose the search term the way a customer would type it rather than the way the industry names itself. Second, set a grid over the target area, finer where businesses are dense. Third, let the sweep run, with progress saved per cell so a dropped connection resumes rather than restarts. Fourth, repeat with alternate terms, because category labelling is inconsistent and each term returns a set the others miss. Fifth, merge everything and remove duplicates on place ID. Sixth, clean: drop permanently-closed rows, normalise phone numbers, and segment before anyone makes contact. Steps four and six are the ones commonly skipped, and they are where most of the difference between a usable list and a mediocre one lives.

Choosing terms, and why one is never enough

Businesses pick their own primary category, and they pick inconsistently. A firm doing plumbing and heating appears under whichever label its owner chose, so a sweep for one term returns a confident-looking list missing whatever share of the market chose the other. The fix is mechanical: run each plausible term as its own pass and merge.

Think in customer language rather than trade language. People search for what they want done, and businesses name themselves to be found that way, so the term a customer would type usually returns more of the market than the formally correct industry term.

Grid resolution, the setting that decides completeness

Because each search stops at roughly 120 results, the grid decides how much of a city you actually see. A coarse grid over a dense category returns a plausible list that is badly short, and nothing in the output indicates the shortfall.

Resolution should follow density rather than convenience. Plumbers or restaurants in a large city need finer cells than opticians or coworking spaces in the same city, and categories that sit in residential areas rather than the centre need the grid extended outward rather than concentrated.

The cleaning step everyone underestimates

A raw merged export is not a working list. Permanently-closed flags need filtering, phone numbers need normalising to a single format, and duplicate rows that survived the place ID merge because they are genuinely separate listings, chain branches, practitioner listings, delivery storefronts, need a deliberate decision rather than an automatic rule.

That decision is the one that most affects results, and it differs by what you sell. Collapsing by address is right when the buying unit is the premises and wrong when it is the individual. Getting it backwards removes most of the addressable list while leaving the file looking tidier than before.

Related reading: choosing a grid cell size , how the three tool models differ .