Void Analysis
Find what a market lacks: compare an area's measured demand against references such as analog areas, competitor networks, or your own stores, then validate each gap with real movement.
Void analysis finds what a market could support but does not have. An absence leaves no direct trace in the data, so the method works by comparison: measure the demand in a place, and use a reference that shows what equivalent demand supports elsewhere. The reference changes with the question; the method does not.
1. The four parts
Every void analysis is built from the same parts:
- A demand signature for the target area or catchment: visit volumes, the resident / worker / visitor mix, audience composition, and travel distance (how far the catchment's people already travel for what they have, from trade areas). This is what makes places comparable.
- A reference that shows what such demand sustains: analog areas with matching signatures, a competitor's network, or your own network elsewhere.
- The gap: what the reference supports minus what the target already has, sized by the reference's visit volumes rather than by intuition. What the target has is an inventory: the venues of each category already operating there, straight from the places directory.
- Validation through measured behavior: the strongest evidence for a void is that the catchment's people already travel for the missing thing. Journeys show it directly.
2. The void questions
Four versions of the question, each with a different reference and a different reader:
| Question | Reference | Who runs this |
|---|---|---|
| Market void: what is this area missing or underserved on? | Analog areas with matching demand signatures | Developers, landlords, and leasing teams building a tenant-mix case or filling a vacancy; municipalities asking what their district underserves |
| Brand white space: where does my brand lack presence, or lose to a core competitor? | The competitor's network, plus the signatures of your own strongest catchments | Retail and restaurant expansion teams, franchise development |
| Fill vs. cannibalize: how much of a candidate site's demand is unmet, and how much transfers from my own nearby stores? | Your own network's catchments overlapped with the candidate's, plus the area's leakage | Network planning and real-estate committees at multi-site operators |
| Capacity relief: when is transfer from my own site the goal? | Your own network's utilization | Capacity-constrained operators (fitness, clinics, childcare, leisure), where a full site turns demand away and pulling visitors from it is relief, not loss |
On fill vs. cannibalize: a new site's visits always come from somewhere. The share drawn from your own stores' catchments is transfer; the share matching the area's measured leakage is new to your network. Estimating the split before committing is what separates an expansion case from a hope. For capacity businesses the same arithmetic flips sign: transfer away from a full site is the value.
3. Choosing the reference
The reference is the biggest judgment call in the analysis, so make it explicit:
- Analog areas should match on the signature dimensions that matter for the question (demand level, visitor mix, audience), not on geography or familiarity. State the matching rule.
- Competitor references carry the competitor's strategy with them: their absence from an area is evidence, but weaker than their presence.
- Co-tenancy patterns are a third reference: which categories operate alongside what the area already has, elsewhere. Visitor journeys measure the demand side of this directly, the categories an area's visitors already combine on one trip. References built from what operators already do carry their judgment with them, good and herd-like alike.
- The places directory alone answers a narrower question with no reference at all: which venues of your type already cover the market, and where a competitor has just opened. A competitor opening in an area your screen flagged is evidence in both directions: the demand is real, and the void is closing.
Whichever reference you choose, a reference supporting a category is not proof of demand in the target. It is a hypothesis to validate with leakage.
4. Reading the gap
- An obvious void may already have been rejected. An absence every operator has noticed may be one someone investigated and declined. Measured demand traveling out of the area is what separates a real void from an unfilled one.
- Presence is not success. A category being present in the reference says it survives there, not that it thrives. Size gaps with visit volumes, not store counts.
- A gap needs a space that fits it. Category gaps say nothing about whether the available floor plates, parking, or lease terms suit that category's format. Check the shortlist against the property facts before sharing it.
- Validate before sizing. Rank gap categories by the reference's volumes, then check each against the catchment's journeys. The categories people already leave the area for are the ones to lead with.
From a validated gap, the next step is a store profile of the reference locations that fill it elsewhere, or, when the question is which of several areas to pursue, an area identification screen.
Examples
Grocery penetration block by block in Denver
Trade areas times store visits, joined in DuckDB: captured visits, the leading grocer, and saturation per block group, ending in a headroom shortlist.
Mapping Sprouts' white space in Denver
The brand white-space variant in Python: profile Sprouts' strongest catchments, screen the competitor network for look-alike areas the brand has not entered (16 candidates in Denver, 2025), then test each against measured journeys.
Related metrics
Visitor Journey (place)
Sequences of places visited before and after a target place. Reveals cross-shopping, shared catchments, and complementary venues.
Foot Traffic w/ Visitor, Worker & Resident (area)
Foot-traffic at the area level split by visitor / worker / resident roles. Lets you separate transient activity from baseline residential activity.
Visitor Profile (area)
Aggregated profile of visitors entering an area.
Visitor Demographics (area)
Demographic breakdown of visitors to an area.
Trade Area (area)
The geographic area that contributes the most visitors to a target area.
Related guides
Area Identification
Score every area in a market on explicit criteria (activity, mix, momentum, seasonality, timing, audience, presence) and combine them into a ranked shortlist.
Analog Modeling: Look-Alike Site Selection
Let your own results set the criteria: profile the locations where your stores perform, then screen a market for look-alike locations you haven't entered.
Match your locations
Bring your own list of stores or sites and match them to Pine59's location identifiers so you can query our data using your IDs.