What is mobility data and what is it used for?

Mobility data measures how people move through territory — how many pass a point, at what time, where they come from and how long they stay — using anonymous, aggregated signals from mobile devices. It is used to choose store locations, measure a store's real trade area, calculate cannibalization between branches, match staffing to a location's real rhythm, and estimate how much visitation a competitor receives. In Mexico it is also called foot traffic or visitation data.

Where does mobility data for Mexico come from?

From mobile device panels: anonymous, aggregated signals that allow movement patterns to be reconstructed without identifying anyone. BlackPrint's panel observes more than 60 million devices per month with national coverage in Mexico. The key difference from international providers is the panel's country: a United States panel does not walk Mexican sidewalks.

How reliable is mobility data?

It depends on three things the provider must declare: the panel's size and country; the denominator (a device is not a person nor a buyer, and expansion factors must be in writing); and temporal stability (good data validates against patterns that repeat — if the same point gives erratic week-over-week results without cause, the panel is too small for that area). A provider that will not answer those three questions in writing is selling faith.

Does mobility data identify people?

No. The layer is aggregated by design: it delivers counts and patterns by polygon, time band and origin zone, never individuals or personal trajectories. There is no personal data to hand over because the unit of analysis is the group, not the person.

BlackPrint · Guides · Data layers

Mobility data in Mexico

The layer that turns a static map into behavior: how many people pass a point, at what hour, which days and where they come from. Measured with an own panel of more than 60 million devices per month in Mexico — always aggregated and anonymous.

Updated September 4, 2026 · BlackPrint Team

60M+devices observed per month in Mexico

The essentials, in 20 seconds

Own panel of 60M+ devices per month in Mexico, always aggregated and anonymous
Four dimensions: volume, hourly rhythm, origin and dwell — by polygon or by point
The rule that makes it auditable: device ≠ person ≠ buyer, declared in writing

01 · What it is OWN PANEL · MEXICO

Not how many people are there. How many pass by, and when.

Demographics count who lives there. Mobility counts who passes through — which, for a business that lives on flow, are different things and sometimes opposite ones.

4dimensions: volume, timing, origin and dwell

What the layer contains

Variable	What it holds	Resolution
Volume	Devices observed inside a polygon or in front of a point	Daily and hourly
Hourly rhythm	Distribution across the day and the week	Hour bands · 7 days
Origin	Where visitors come from (aggregated origin zone)	Block / neighborhood
Dwell	How long they stay and how often they return	Per visit

▲ READINGAn example of what this layer sees and a directory cannot: measuring five shopping centers for a month (973,828 devices), Tuesday was the weakest day in all five, 12.9% to 16.2% below each center's own average. Large centers peak from 12 to 15 h; small ones from 17 to 21 h.

02 · What it is for REAL DECISIONS

Five decisions that are made blind without mobility.

Each with a published guide and measured numbers, so the method can be audited before buying.

5decisions this layer resolves

Questions it answers

The question	Who asks it	How the layer answers
How many people pass this corner?	Retail, restaurants, franchises	Volume and hourly rhythm of the candidate polygon
Where do my customers come from?	Multi-unit chains	Real origin — not a drawn radius
Does the new store steal from mine?	Expansion	Shared visitors between the two points — from 91.7% to 0.7%
How many people enter the competitor's mall?	Real estate and retail	Volume of a third-party polygon, no permission needed
How do I schedule staff?	Operations	Rhythm by day and hour — the real peak hour

03 · Where it comes from SOURCES AND LIMITS

Where it comes from, and what it cannot tell you.

No territorial data is perfect. These are this layer's limits, stated before you discover them.

3limits worth knowing before using it

Sources, refresh and what it cannot say

Point	How it works here
Source	Anonymous, aggregated mobile-device signals; own panel with national coverage
Refresh	Continuous; typical analysis windows are 30 days
Limit 1 — the denominator	Device ≠ person ≠ buyer. Some people carry two devices and many pass without entering. Expansion factors are declared in writing
Limit 2 — sample size	In very low-density areas the panel thins and week-over-week readings get noisy
Limit 3 — not identity	The layer says who nobody is. It is aggregated by design; there is no personal data to hand over

▲ READINGThat first limit is the one the industry keeps quietest. If a provider shows you "monthly visitors" without saying what fraction of the real population its panel represents, the number cannot be audited.

04 · How you receive it 3 WAYS

Platform, data delivery or API.

Same layer; what changes is how you consume it. The right route depends on whether you will look at it, join it with your own data, or feed it to a model.

3ways to consume the same layer

Which route fits

Route	When	What you get
In the platform	You want to see it on the map and decide with it	The layer switched on over your area, with the others on top
Data delivery	You will join it with your own information in your tools	Geospatial files by area or nationwide, with a data dictionary
API	You will feed it to a model or your product	Query by parcel, polygon or coordinate

▲ READINGBefore contracting any data layer — ours included — apply the four-question checklist in the category map: what they publish that you can audit, which country the data is from, whether they declare their denominator, and whether you can see a measured case.

Sobre tu territorio

Este análisis es del municipio. El tuyo es de tu esquina.

Si tienes una decisión enfrente —dónde abrir, a quién rentarle, contra cuánta competencia llegas— la medimos con los datos de tu zona exacta, no con promedios municipales.

Agenda 30 minutos O escríbenos a Gilberto@blackprint.ai