Retail IntelligenceConnect store visits with retail sales to see where traffic, conversion and basket size changed, and which stores to look at first.
Aug 30, 2026 to Sep 28, 2026 · 30 calendar days
Sales reporting: 71 stores · Traffic reporting: 39 stores with valid door counts (39 equipped)
Tap a region to explore.
Connections are illustrative, not live feeds · Open map
Unique stores
71
70 U.S. + 1 Canada
Alterations
68
stores · simulated
Personal Styling
63
stores · simulated
Fitting Room or Ship-from-Store
13
either, counted once
In-store pickup
54
stores · simulated
Traffic coverage
39
of 71 · simulated
Store attributes for all regions · service availability and traffic-sensor coverage are simulated store attributes, not verified UNTUCKit data · Fitting Room or Ship-from-Store counts each store once (13 Fitting Room, 13 Ship-from-Store) · they follow the region filter, not the period.
Aug 30, 2026 to Sep 28, 2026 · 30 calendar days · All regions · 71 stores in view
Aug 30 – Sep 28 vs Jul 31 – Aug 29 (prior 30 days) · all regions · 71 stores reporting sales, 39 with entrance counts · changes vs prior use 71 comparable stores (0 new stores excluded) · traffic changes use 39 stores with entry counts in both periods, compared per valid day (1,151 vs 1,152 valid store-days; 17 missing-count days excluded, not zeroed)
Net retail sales
$14.5M
Store entries
172.1K
Retail transactions
92.7K
Transactions per entry
29.8%
Avg retail ticket
$157
Retail revenue per entry
$47.19
Service revenue
$537.4K
Reporting coverage
55%
Connections are illustrative, not live feeds · Open map
Executive brief
Recalculated for the selected period and region
1. What changed
In 39 comparable stores with door counts, average daily entries moved -1.9% and retail transactions -2.2%. Transactions per entry moved -0.12 pts to 29.8%, and average retail ticket +0.1% to $157.
Observed change in measured figures. Explains what moved, not why.
Next step: Review which store groups drove the gap before setting targets.
Open supporting analysis2. Who contributed most
Comparable-store net retail sales were $14.5M (-1.6% vs the prior period). Southeast carries the largest share of the change. Largest single-store move: Mall of Georgia, GA (-$27.1K).
Observed association: these regions, stores and categories account for the change arithmetically; that does not prove they caused it.
Next step: Open the Southeast region to compare store groups with similar format and services.
Open supporting analysis3. What to investigate next
2 stores kept daily entries within 6% of their own prior period, yet transactions per entry fell 2 pts or more. Recovering 1 pt would equal about $12.0K of retail sales over the selected 30 days - an illustrative scenario, not a forecast.
Illustrative scenario, not a forecast. A lower rate is a signal to investigate, not a proven cause.
Next step: Start with The Mall at Green Hills, TN: its rate fell 2.4 pts while traffic held steady, the largest drop in this group. Check peak-hour staffing (where schedules exist), queue times and local events before acting. A lower rate alone does not prove understaffing.
Open supporting analysisStores
Net retail sales from all reporting stores; changes from comparable stores; per-entry rates from overlap days in traffic-covered stores. Select a region or store to drill in.
| Region | Stores | Net retail sales | vs prior | Txns per entry | Change | Avg ticket | Service revenue |
|---|---|---|---|---|---|---|---|
| West | 16 | $3.2M | -1.3% | 26.6% | -0.1 pts | $157 | $128.0K |
| Southwest | 10 | $2.1M | -1.3% | 29.9% | -0.0 pts | $159 | $85.8K |
| Midwest | 11 | $2.3M | -1.1% | 28.7% | +0.1 pts | $153 | $83.2K |
| Southeast | 18 | $3.6M | -2.6% | 30.9% | -0.3 pts | $158 | $135.1K |
| Northeast | 16 | $3.4M | -1.2% | 31.9% | -0.2 pts | $157 | $105.3K |
Aug 30 – Sep 28 vs Jul 31 – Aug 29 · comparable stores only
2 stores on the conversion watchlist
Share of net retail sales, current vs prior period
Each sale counted once by order channel and fulfilment
Walk-in store purchases Used for per-entry metrics | $12.9M |
Buy online, pick up in store Store-fulfilled; excluded from per-entry | $808.5K |
Curbside pickup Store-fulfilled; excluded from per-entry | $269.5K |
Same-day delivery Store-fulfilled; excluded from per-entry | $495.1K |
Online, ship to home Not attributed to stores | $1.6M |
Channel split is modeled for demonstration.
Services
UNTUCKit-operated services, reported separately from retail. Service availability is a simulated store attribute; counts overlap and are never added together.
Service revenue
$537.4K
Tailoring utilization
79.1%
Fitting Room occupancy
68.8%
Service-to-retail attachment
29.4%
All regions · stores offering each service — simulated; counts overlap
Sources: service figures here are simulated bookings and capacity. In a live deployment they would come from UNTUCKit's tailoring, styling, fitting-room and appointment systems where connected. Anonymous entrance counts cannot tell why someone visited, so bookings are never divided by store entries.
Hourly & Weekly
Hourly figures are modeled estimates that add back to simulated daily totals; partial weeks are excluded from week-over-week growth.
Modeled peak hour (est.)
5pm–6pm
estimated hourly pattern, by entries
Busiest weekday
Saturday
avg entries per date · quietest Monday
Weekend vs weekday
+40%
entries per date, Sat–Sun vs Mon–Fri
Modeled peak share (est.)
35%
of entries in the 3 busiest hours (5pm, 12pm, 1pm)
Busiest date
Sep 12
203 entries per reporting store
Quietest date
Sep 15
118 entries per reporting store
Weather & Context
Illustrative weather (deterministic demo series, not observed), compared with each store's average over the 28 days before the period.
Store Network
Search, filter, zoom and select stores; open any store for its full detail. On desktop, click the map to enable wheel zoom; on phones, use the + / − buttons and tap markers so the page keeps scrolling.
Community
Shown separately from retail: event donations and partner revenue are not UNTUCKit retail sales. Figures are modeled.
Participating locations
64
In-store events
326
Event RSVPs
539
In-store pickup locations
54
Methodology
Store list and locations are real; sales, services, door counts and weather are simulated. Each store counts once; services are store attributes. Changes use comparable stores; per-entry metrics use same-store, same-day overlap; missing counts are unavailable, never zero. Nothing here is a live connection.
Powered by Dôr
Dôr measures one thing: anonymous door entries at the main entrance — no cameras, no images, no personal data. It does not identify individual customers and does not determine why anyone visited. Sales, service bookings, UNTUCKit customer account and staff schedules come from UNTUCKit's own POS, booking, loyalty and scheduling systems; the dashboard lines those up with measured entries for the same stores and days.
Proposed next step
A pilot across selected stores
For example, a mix of retail-only, tailoring/styling and Fitting Room stores across two regions, measured against each store's own baseline. Scope, timing and terms to be agreed together.
How this demo works