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© TARS

Change one sign out front.
See exactly what it did.

Get the overview

Store analytics

TARS uses a small edge camera by your door
to count who passes, who pauses, and who walks in.

  • Passed1,284
  • Stop rate7.9%
  • Walk-in29%
  • Video storedNO
Sample data

Setup without construction

Mount the camera by the door, plug it in,
and counting begins.

  1. Edge camera
  2. Power
  3. Counting starts

AI that only counts your side

Monocular depth estimation measures distance,
so people at your door and across the street are counted apart.

  • Your sidewalkYES
  • Far sideEXCLUDED
  • Face recognitionNO
  • Video storedNO
  • Re-identificationNO

Reports you can act on

Charts plus a plain-language note on
what to try next week.

Foot traffic by hour (weekdays)

Sample data
8a10a12p2p4p6p8p10p
Rainy days-18%range -24 to -11%

Line above bar: 90% interval

This week out front

Sample data
  • Foot traffic held steady (avg. 410 per hour).
  • Stop rate rose 4.2 pts during the lunch special.
  • Next week, try putting the sign out at dinner, too.

Key features

Use sidewalk data to decide your next move.

Foot traffic

Traffic by day and hour, split by weather and holidays.

  • Q.Is the sidewalk busier at lunch or at dinner?

  • Q.How much does rain cut foot traffic?

Foot traffic by hour (weekdays)

Sample data
8a10a12p2p4p6p8p10p
Rainy days-18%range -24 to -11%

Line above bar: 90% interval

Stop & walk-in rates

Passed → paused → walked in: see what share makes it to each next step.

  • Q.Lots of people walk by — why don’t they come in?

Storefront funnel (this week)

Sample data
  1. Passed1,284(1,210–1,360)
  2. Paused101 · 7.9%(6.9–8.9%)
  3. Walked in29 · 29%(24–34%)

Bar: share of the previous step that moved on · Black line: 90% interval

Before / after tests

Compare two weeks before and two weeks after a new sign, menu-board spot, or lunch special — with ranges.

If the ranges overlap, we say so plainly: not conclusive yet.

  • Q.Did the new sign actually work?

  • Q.Should we keep the lunch special?

Stop rate, before vs. after (2 wks each)

Sample data
6.1%Before8.4%AfterNew signClear effect7%Before7.4%AfterMenu-board spotNot conclusive yet6.5%Before10.7%AfterLunch specialClear effect

Line above bar: 90% interval

Queue walk-aways

See what share of people give up and leave at each line length.

  • Q.At what line length do people give up?

Walk-away rate by line length

Sample data
Jumps at 612345678910Line length (people)

Neighborhood benchmarks

Line your store up against similar shops nearby to see where you lead and where you lag.

Benchmarks become available once enough stores in the same area are measured.

  • Q.How does my store compare with the neighborhood?

Versus the neighborhood

Sample data
Passersby per hour420
Walk-in rate2.3%
Your storeNeighborhood range

Plenty of traffic, but your walk-in rate trails the neighborhood.

Pilot stores

We're building the first case studies with early stores.

Apply for the pilot

Site surveys

Before you sign the lease,
count who actually walks by.

We place a portable sensor kit outside a candidate space for 1–2 weeks,
then deliver a full-year foot-traffic estimate — with ranges.

Request a site survey

How it works

  1. 01 · Day 1

    Install

    A portable sensor kit goes up outside the candidate space. No construction needed.

  2. 02 · 1–2 weeks

    Measure

    We record traffic by day and hour, walking direction, and dwell patterns. No video is stored.

  3. 03 · After

    Extrapolate

    We combine the sample with public population data, weather, and the holiday calendar to estimate a full year.

  4. 04 · Delivery

    Report

    You get a report where every estimate comes with a 90% interval.

Report contents

  1. 1Summary: how many people pass this spot each day
  2. 2Foot traffic by day and hour
  3. 3Walking direction: where people come from and go
  4. 4Dwell patterns: who stops, and for how long
  5. 5Side-by-side with nearby competitors
  6. 6Full-year estimate with 90% intervals
  7. 7Measurement conditions and limits (weather, holidays, nearby construction)

Full-year estimate: daily passersby

Sample data

2,34090% interval 2,050–2,640

MeasuredJanAprJulOctDec

What each team gets

First-time founders

  • Real foot-traffic numbers before you sign
  • Whether the spot suits a lunch or dinner business
  • Evidence to weigh rent and key money

Commercial brokers

  • Turn "great foot traffic" into numbers
  • A report you can attach to a listing
  • Compare listings on the same yardstick

Franchise site-development teams

  • Compare candidate sites on one standard
  • Benchmark against your existing stores
  • Ranged estimates ready for site-approval reviews

Storefront analytics for the ten feet that matter

Make your next call with data, not hunches.

Get the overview