Aggregate “high foot traffic” labels destroy operators — Bondi Junction requires block-level thinking. Interchange passengers compress around station exits; Oxford converts movement into window impressions only when sightlines and category fit align; secondary strips borrow spill at lower velocity but sometimes higher conversion for appointment-led models. Below: how to read flows without mistaking motion for money.
Three traffic layers — station, mall edge, secondary spine
Weekday vs weekend — do not average blindly
Saturday surfaces can flatter forecasts — model March weekday separately from January beach peaks. Hospitality wage rules punish gaping Tuesday afternoons harder than rent spreadsheets admit.
Competitor density within 500m — saturation that matters
Generic café counts mislead — score competitors in your price tier and daypart. Oversupply at $16 brunch tickets differs from undersupply at $12 fast weekday lunch.
From counts to covers — rough throughput bridge
If plausible passing capture sits far below rent-implied covers, the strip rejects your category regardless of aggregate pedestrians — adjust frontage, ticket, or suburb.
Bind foot traffic assumptions to an address — not a postcard.
Foot-traffic-aware analysis →Tools first — then a full report for your address
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