Competitors (Concern 1): Confirmed accurate. Tel Aviv 167 / Modi'in 7 / Ashdod 10 hold under PRODUCT_LINE_HIERARCHY_3 IN ('asian','sushi'). Broader Asian pool (adds japanese, chinese, korean, ramen, noodles, poke, thai, vietnamese, bowl) brings TLV to 181 and HaSharon to 56 — added as supporting column.
Impression share (Concern 2): 2.44% in TLV is mathematically correct given a 167-venue pool — but the missing context is FU Sushi ranks #3 of 182 in Tel Aviv Asian/sushi venues by 90d session impressions (behind Giraffe TLV and Shi-Shi). NOOCH is #9, Studio TLV is #19. Added "rank in city pool" column.
Avg position (Concern 3): Replaced King/Ace tier with numeric average from F_SESSION_DISCOVERY_EVENTS.SECTION_ITEM_INDEX. Ensō best at 2.07, FU Sushi at 4.34, Studio TLV worst at 5.57 — investigate Studio's home-feed placement.
Heatmap restyle (Concern 5): DOW & hour tables now use a red→white→green gradient, per-row normalised. Peak cells outlined in green for instant scanning.
New viz (Concern 6): Added per-venue mini sparkline-style bars showing DOW and hour share at-a-glance, with peak day/hour callouts. Toggle to switch heatmap ↔ minibars.
NOOCH city investigation — VENUE_CITY is the Wolt marketplace, not the postal city
NOOCH's physical address is הסייפן 31, רמת השרון (Sayfan 31, Ramat HaSharon) · lat 32.1347, lng 34.8382 · postcode 4724831 — clearly in Ramat HaSharon, not Tel Aviv. Yet D_VENUES.VENUE_CITY = "Tel Aviv". Investigated:
What VENUE_CITY actually represents: the Wolt operational marketplace, not the postal/administrative city. There is no separate MARKETPLACE_NAME or CITY_NAME column in D_VENUES; VENUE_CITY is the marketplace label, full stop. Address-city lives only in VENUE_ADDRESS (free-text) and lat/lng / postcode.
Ramat HaSharon is split across two marketplaces: querying every venue whose VENUE_ADDRESS mentions Ramat HaSharon returns 229 in "Tel Aviv", 8 in "HaSharon", 2 in "Herzliya - Ramat Hasharon". Southern Ramat HaSharon (Glilot / NOOCH's area) is Wolt's Tel Aviv marketplace; northern Ramat HaSharon is HaSharon.
NOOCH's delivery polygon confirms it: the polygon spans lat 32.10–32.20 — almost entirely Tel Aviv (Ramat Aviv, Bavli, North TLV). It competes against the Tel Aviv Asian/sushi pool of 182 venues, not the HaSharon pool of 57.
Conclusion: the "Tel Aviv" label is correct from a competitive/marketplace perspective — leave NOOCH in the Tel Aviv pool. The user's address-based intuition is right too; the two facts coexist because Wolt's Tel Aviv marketplace extends into southern Ramat HaSharon. Source field to trust for "where does it compete?" → VENUE_CITY. Source field to trust for "where is the storefront physically?" → VENUE_ADDRESS + lat/lng.
Executive summary for brand management
FU Sushi and NOOCH generate 39% of brand orders but trail brand FTU by ~3.3pp — invest acquisition spend on these two flagships first.
FU Sushi is rank 3 of 182 Asian/sushi venues in Tel Aviv by impressions — share looks small (2.4%) only because Tel Aviv is the largest, most fragmented Asian market on Wolt ISR.
Studio | Tel Aviv has the worst average position (5.57) and rank 19/182 despite a 19.3% FTU rate — fix discovery placement before adding media spend.
Friday is the weakest day for 6 of 8 venues; Sazanca and Ni-Shi peak Saturday — run Friday lunch + Saturday-night sustain campaigns.
Ensō (Modi'in) and Kisu (Petah Tikva) already dominate their cities (rank 1–2 with 7–17% impression share) — protect leadership; don't over-invest in awareness.
Sazanca (Ashdod) 42.7% FTU rate, only 6.4k orders on a tiny 11-venue pool — pure volume opportunity, not acquisition.
Pool = same VENUE_CITY · asian + sushi (current logic). Rank uses the broader Asian pool (asian+sushi+japanese+chinese+korean+ramen+noodles+poke+thai+vietnamese+bowl).
Venue
City
Orders
FTU rate
vs brand
Competitors curr / broad
Impr (90d)
Impr share
Rank in city
Avg position
Ad tier
FTU rate by venue (%)
Dashed line: brand average 17.6%
Brand impression share by city
Brand venue share of city Asian/sushi impression pool (90d)
Top 10 Asian/sushi competitors — by city (90d impressions)
Brand venues highlighted in brand blue. Pool = same VENUE_CITY · broad Asian (asian, sushi, japanese, chinese, korean, ramen, noodles, poke, thai, vietnamese, bowl). Source: F_SESSION_VENUE_PATHS.VENUE_IMPRESSION_COUNT · 90d. Switch cities ↓
Day-of-week distribution — per venue (% of venue orders)
Each row sums to ~100% (row-normalised). Peak day outlined green. Hover bars/cells for the exact value.
peakmidweakest
Per-row red → white → green:weak %medianpeak %
Hour-of-day distribution — per venue (% of venue orders)
Each row sums to ~100%. Hours 4–8 omitted (≤0.05% of orders). Peak hour outlined green.
peakmid≤50% of peak
Per-row red → white → green
Advertising priorities
Ranked by FTU gap × volume × discovery weakness
#
Venue
Tier
Rationale
Campaign timing
Recommended daypart / DOW boosts
Scope
Boost window
Why
Data confidence audit
Per-metric confidence rating with rationale and anchor documentation.
Metric
Source
Confidence
Rationale
Anchor docs / explores
Studio Bakery — unpublished
Studio Bakery (VENUE_UNPUBLISHED, classified as bakery not sushi/asian) recorded 0 delivered/refunded orders in the last 90 days. Excluded from competitive analysis. Do not allocate paid media until republished.
How tiers are assigned
High: FTU rate > 3pp below median (17.4%) AND high-volume — acquisition priority.
Medium: Near-median FTU OR mid-volume with daypart/DOW gap — growth budget or timing fix.
Low: FTU at or above brand average AND already top-5 in city — retain efficiency, sustain spend.
Hours below 50% of venue peak → daypart targeting. Weakest DOW vs strongest → day-specific promos.