Store directory

Store #49 · Midwest · Standard (~2,300 sq ft, modeled)

Easton Town Center, OH

4066 The Strand East Space 512, Columbus, OH 43219 · Hours vary — see store page. Sales reporting: 30 trading days · Traffic reporting: 30 days with valid door counts. Aug 30 – Sep 28 compared with this store’s own Jul 31 – Aug 29.

Aug 30, 2026 to Sep 28, 2026 · 30 calendar days

Net retail sales

$167.1K

-1.5%

Store entries

3,182

-0.6% per valid day (30 vs 29 days)

Transactions per entry

32.5%

-0.1 pts

Avg retail ticket

$162

+0.3%

Service revenue

$7.0K

-1.8%

Daily retail sales and transactions

Aug 30 – Sep 28

Services and data coverage

Address, hours and phone verified from the store list. Services and coverage below are simulated.

  • Alterations & Tailoring
  • Personal Styling
  • Fitting Room
  • Ship-from-Store
  • Buy online, pick up in store
  • Community events

Simulated reporting availability · not live connections

POS (sim.)Entrance traffic (sim.)Bookings (sim.)Staff schedules (sim.)UNTUCKit customer account (sim.)
Store page on untuckit.com

Estimated hourly pattern (modeled)

Average open day, estimated hourly split of simulated daily totals (local time) — not measured hourly data. Staffing shown only where (simulated) schedule data is available.

Modeled busiest hour (estimate): 5pm. 3.5 entries per scheduled labor hour at peak — compare with off-peak before drawing staffing conclusions.

Merchandise mix and comparable peers

Peers: 19 comparable Standard stores, retail + tailoring/styling (format and services simulated)

  • Shirts48.5% -1.1 pts
  • Polos & tees18.2% +1.5 pts
  • Pants & shorts20.4% -2.3 pts
  • Outerwear & accessories12.9% +1.9 pts

This store: 32.5% transactions per entry · peer group: 31.0%

Hourly & weekly · this store

When this store is busiest

Local time (Eastern). Trading hours: Hours vary — see store page — unlisted days use typical UNTUCKit hours. Modeled hourly distribution: each store-day's reported totals are split across that store's trading hours (local store time) and add back exactly to the daily figures.

Modeled peak hour (est.)

5pm–6pm

estimated hourly pattern, by entries

Busiest weekday

Saturday

avg entries per date · quietest Tuesday

Weekend vs weekday

+34%

entries per date, Sat–Sun vs Mon–Fri

Modeled peak share (est.)

37%

of entries in the 3 busiest hours (5pm, 12pm, 1pm)

Busiest date

Sep 19

154 entries per reporting store

Quietest date

Sep 15

81 entries per reporting store

Hour by hour · this store (average day)

Modeled hourly distribution: each store-day's reported totals are split across that store's trading hours (local store time) and add back exactly to the daily figures. Two reporting cohorts: "All trading stores" columns include sales-only stores and days without valid counts; "Matched" columns use only store-days with valid door counts, and Txns / entry = matched transactions ÷ entries.

Local hourTransactions
all trading stores
Net sales
all trading stores
Entries
matched
Transactions
matched
Txns / entry
matched
Rev / entry
matched
10am2$309.006234.1%$51.82
11am3$542.0010332.3%$52.48
12pm4$662.0013431.6%$51.44
1pm4$648.0013433.1%$51.85
2pm3$537.0010332.1%$51.60
3pm3$553.0011332.2%$52.37
4pm4$625.0012432.6%$51.80
5pm4$728.0014432.7%$53.65
6pm3$528.0010331.7%$52.30
7pm3$438.008333.8%$56.92

Weekday × hour heatmap

Hatched = closed; dash = open but no valid door count

10am11am12pm1pm2pm3pm4pm5pm6pm7pm
Mon
Tue
Wed
Thu
Fri
Sat
Sun

lowhighclosed (no store open)–open, no valid countLocal store time. Average per calendar date of that weekday; hover for values.

Day-of-week performance

Per calendar date; rate from same-day overlap

WeekdayDatesEntries / date (matched)Txns / date (all trading)Net sales / date (all trading)Txns / entry (matched)
Monday59029$4.6K32.3%
Tuesday48829$4.6K32.8%
Wednesday49029$4.8K32.4%
Thursday49832$5.1K32.6%
Friday411739$6.3K33.3%
Saturday413643$7.1K31.2%
Sunday512341$6.6K33.0%

Weekend rows shaded. A period can contain unequal numbers of each weekday, so values are per calendar date. "All trading" includes sales-only stores; "matched" uses only store-days with valid door counts, and Txns / entry is matched transactions ÷ entries.

Weekly trend · this store

Aug 30 – Sep 28

Weekly summary · generated from the selected data

Latest week (Sep 22 – Sep 28): comparable net retail sales -0.2% week over week across 1 store; transactions -1.3%, average ticket +1.0%. Traffic per valid day -1.9% and transactions per entry +0.20 pts, using 1 store with valid counts in both weeks (7 vs 7 valid store-days). Sales were essentially flat.

Week (Tue–Mon)DaysNet salesWoWTransactions (all trading)Entries (matched)Traffic WoWTxns / entry (matched)Δ ptsAvg ticketRev / entryCoverage
Aug 30 – Aug 31Partial2$11.7KPartial70212–33.02%–$167$55.142/2 valid days
Sep 1 – Sep 77$38.7K-3.8%236720-5.8%32.78%+0.3 pts$164$53.777/7 valid days
Sep 8 – Sep 147$40.0K+3.3%253766+6.4%33.03%+0.3 pts$158$52.237/7 valid days
Sep 15 – Sep 217$38.4K-4.0%239749-2.2%31.91%-1.1 pts$161$51.277/7 valid days
Sep 22 – Sep 287$38.3K-0.2%236735-1.9%32.11%+0.2 pts$162$52.137/7 valid days

Weeks are 7-day blocks ending on the as-of date (Tuesday–Monday). If the period is not a multiple of 7 days, its first block is partial and has no week-over-week change. Sales, transaction and ticket changes use stores trading through both weeks; traffic and per-entry changes use only stores with valid counts in both weeks, compared per valid day. Rates are pooled from summed transactions and entries. Weekly rows add up to the selected-period totals. Partial weeks are shown for totals only and are excluded from every growth claim. Hours are each store's own local opening hours (from its published schedule) in its local time zone; days are local calendar days, so a daylight-saving change shifts no counts between days. Hourly figures are estimates that split simulated daily totals and are not measured.

Weather & context · this store

Local weather alongside traffic

Illustrative weather (deterministic demo series, not observed). Matched to this store's geocoded address. Simulated retail performance is independent of it; associations only.

Daily weather alongside traffic

Illustrative weather (deterministic demo series, not observed). Entries per valid store-day uses traffic-covered stores only. Aug 30 – Sep 28.

Last 7 days

Illustrative weather · entries shown only on valid-count days

DateConditionHigh / lowPrecipEntriesNet sales
Tue Sep 22Clear74° / 51°F089$4.5K
Wed Sep 23Rain71° / 49°F0.45"85$4.3K
Thu Sep 24Clear69° / 49°F0105$5.7K
Fri Sep 25Rain69° / 49°F0.08"123$6.3K
Sat Sep 26Clear75° / 52°F0129$7.2K
Sun Sep 27Cloudy75° / 56°F0116$6.0K
Mon Sep 28Clear69° / 51°F088$4.3K

Traffic by weather condition · this store

Aug 30 – Sep 28 · versus this store's own same-weekday average, Aug 2 – Aug 29 (before period) · simulated weather

Illustrative comparison: the traffic index (entries vs each store's own same-weekday average, Aug 2 – Aug 29) was +0.9 pts on wet days compared with dry days (9 wet and 21 dry store-days). Weather and performance are both simulated, so this describes the demo data only — not UNTUCKit behavior, statistical significance or a causal effect.

ConditionStore-daysStoresDatesTraffic indexTxns / entryRev / entry
Clear14114100.432.6%$52.72
Cloudy717101.532.3%$53.51
Rain616101.332.3%$51.53
Storm313n<4––
Snow000No days––
All wet days919101.732.4%$51.35
All dry days21121100.832.5%$53.01
Hot (high ≥ 90°F)000No days––
High < 90°F30130101.132.5%$52.52
Mon–Thu · wet616100.231.8%$50.54
Mon–Thu · dry11111104.332.9%$52.47
Fri–Sun · wet313n<4––
Fri–Sun · dry1011098.232.2%$53.43

Traffic index: Σ entries ÷ Σ expected entries × 100, where expected is each store's own average for the same weekday over valid-count days in the 28 days before the period (Aug 2 – Aug 29, ≥3 valid same-weekday days); compared days fall in Aug 30 – Sep 28. Weather and performance are simulated. 100 = typical for that store and weekday. Rates are pooled. Groups with fewer than 4 store-days are not reported.

Service utilization

From bookings and modeled capacity — never derived from door counts

Tailoring utilization

84.9%

203 completed of 219 booked · 3 no-shows

Training seat fill

66.7%

9 new enrollments · 78 session attendances