Lulu Hypermarket

Lulu Retail Holdings

AI Operating System

DeployOne
Viewing as

Operating scope

Country head

Capability

All capabilities

Active handovers

0

Outcomes written back

0

Information density is explain.

PlacementOS · screen 01 of 07

Zone performance

Dwell, pick and conversion for every zone, read from the camera feed the store already runs. Anonymous counts only.

3 issues · 2 waiting on you

Issues in scope

3

12 instances across 11 places

Waiting on you

2

0 already decided in this session

Three largest

AED 1.4m–AED 5.1m

Modelled annual value, three largest only

Running without asking

0

0 armed and waiting on a threshold

Decision owner

City head

Returns to Country retail lead, Group

Scope

Oman

27 stores · all capabilities

Listen

Existing camera feed, anonymous countsTill lines matched to zoneTrading hours and day part

Process

Dwell against pick against basketFour weeks, not oneLike zones across like stores

Act

Test at the storeEscalate where it repeatsNever identify a person
Written backEvery outcome returns to the systems that produced the evidence.
KindOrder

Queue

3 issues across 12 places · 2 waiting on you
Choose

Produce holds the highest dwell in Muscat and close to the lowest pick rate

Muscat
What happened
Across the stores in Muscat, the produce zone records the longest dwell in the store and a pick rate in the bottom three zones. The pattern holds for four consecutive weeks and repeats across 4 of the stores measured.
Why it matters
High dwell with low pick means customers are considering and declining, which is the most expensive thing a zone can do. It occupies the customer's time and the store's best floor and returns less than a zone nobody stops in.
Already done
The read is separated from the verdict. Three explanations fit the same data and each one goes to a different desk, so the choice is put here rather than assumed.
Worth
AED 1.3m to AED 4.6m a yearModelledHigh dwell with low pick in produce. Value is the conversion gap against comparable zones, times the share recoverable once the cause is identified.Produce pick rate against dwell
Then what
Read recorded, test or referral raised on the chosen causeCountry retail leadReports back 30 Sept
City headPlacementOSDeployOneContextDeployOnePredict
Also open at
Approve

The loose produce scales at Sohar sit at the far end of the aisle from the produce

Sohar
What happened
Customers picking loose produce walk the length of the aisle to weigh, then return. The camera shows this as a repeated back and forth inside the zone, and it correlates with the abandoned picks.
Why it matters
This is the cheapest of the three explanations to test and the fastest to reverse. Two weeks of measurement on the same feed settles whether friction explains the produce gap before anyone spends money on price or on handling.
Already done
The test is designed, the measurement runs on the existing feed, and there is no cost beyond moving a scale unit.
Worth
AED 155k to AED 486k a yearModelledA layout friction test costs the move of a scale unit. Value is the conversion recovered if friction proves to be the cause.Abandoned picks in the produce zone
Then what
Test brief on the store list, measurement on the existing feedStore managerReports back 30 Sept
If approved
A two week scales test runs at Sohar, measured on the same feed
If declined
The produce question stays open and the same read repeats next month
Store managerPlacementOSDeployOneContextDeployOnePredict
Also open at
Declined

The system was asked for individual shopper paths and refused

Zakher Mall, Al Khuwair
What happened
The camera data would technically support following a single shopper through the store. The request came up in scoping. It was refused at design rather than case by case.
Why it matters
The moment a retail camera system follows individuals, it stops being an operations tool and becomes a privacy exposure with a regulator attached. Zone counts answer every question in this console without going anywhere near that.
Already done
Every camera-derived action here is a zone measure. No path, no face, no identity, no re-identification across visits.
Exposure
Not a revenue lineIndividual path tracking ends the conversation with a privacy officer in six jurisdictions, and it is not recoverable once it has been built.Camera reads at zone level only
Then what
Refusal held, zone counts onlyGroupStanding, no return date
Override
Nobody. Refused at design, not case by case
Cost of overriding
Individual path tracking is the line that ends the conversation with a privacy officer, in six jurisdictions at once
GroupPlacementOSDeployOneContextDeployOnePredict