Retail Intelligence: Key Terms Defined

The Loop (SEE → ACT → PROVE)

Storalytic's operating principle, and the structure of the product. SEE: behaviour on the shop floor is measured continuously at zone level: who passed, who engaged, who was served. ACT: that measurement is turned into one concrete, named move for a specific zone, ranked ahead of every other move available this week. PROVE: once the move is made, the platform measures it on equal windows before and after, reports the verdict, and remembers the result. A store that only sees has a report. A store that runs the loop has a method. Most retail analytics stops at SEE; the loop is what makes the next decision better than the last one.

PROVE (the guidance loop)

The closing step of the loop, and the part other tools leave out. When a store makes a change, such as moving a display, restaffing an hour or re-signing a zone, the change is logged with its date. A store cannot split its visitors in two the way a website can. So a logged change is measured against the same floor before it: the same number of days either side, at least four weeks, one rule for every change. The verdict reads improved, declined, mixed or no change. Season, promotions and a second change on the same zone move the numbers too, so the store decides whether it was the change. The euro outcome is reported honestly as measured, modelled, or still building. Results that came from a tracked action with sales entered are reported as proved €; everything else remains estimated €. Proved outcomes are retained, so the store accumulates a record of what actually works on its own floor. Storalytic measures realised impact; it does not promise a return.

The Four Gears

How Storalytic frames a benchmark. Rather than comparing a store to an abstract ideal, performance is measured against four gears: (1) the store's own best weeks, (2) its best comparable zone, (3) the peer cohort, which follows once enough stores are on the platform, and (4) best-in-class, held as the horizon rather than a target. The active benchmark is always the next gear up, never the furthest one, which keeps the goal credible and reachable. The gap to that next gear is what the platform expresses as € within reach.

€ Within Reach

The monetary size of the jump from a zone's current performance to the next gear: the realistic growth available if a specific, achievable improvement is made. It is a forward-looking growth figure, not a loss figure: it describes demand already present on the floor that is not yet being converted. € within reach is always a modelled estimate, derived from measured behaviour combined with the store's own conversion and basket assumptions. Behaviour is measured; money is modelled, and Storalytic labels the difference everywhere it shows a number.

Clear Lingerer

A store visitor who remains in a defined zone for long enough to be classified as actively engaged with the product or display. A Clear Lingerer has demonstrated purchase intent through their dwell behaviour: examining, comparing, or considering. The classification is made by cut-offs set from each zone's own visit durations, applied to movement data. Clear Lingerers are the primary commercial signal in Storalytic's analytics layer: their count, their rate relative to total zone visitors, and their conversion or non-conversion define the core opportunity metrics. Sometimes called the physical click: the in-store equivalent of a product page view online.

Short Lingerer

A store visitor who pauses in a zone briefly: longer than a walk-by, but not for long enough to be classified as a Clear Lingerer. Short Lingerers typically notice a display or product but do not enter sustained engagement. They represent a mid-tier signal: not passive, but not yet activated. In the engagement funnel, Short Lingerers sit between Walk-Bys and Clear Lingerers.

Walk-By

A store visitor who passes through or near a zone without stopping or engaging. Walk-Bys are detected and counted but represent low or no commercial engagement with that zone's products or displays. A high Walk-By rate combined with a low Clear Lingerer rate typically indicates a display problem, a layout problem, or a product–placement mismatch: the zone is receiving traffic but not capturing attention.

ATTRACT / SERVE / DEPLOY

Storalytic's three operational gauges, each answering a different commercial question: grow, protect, save. ATTRACT (grow) measures the effectiveness of zones and displays at drawing visitors in (the rate at which visitors transition from Walk-By or Short Lingerer to Clear Lingerer), and expresses the gap as € within reach. SERVE (protect) measures the quality and speed of service at points of assistance, consultation, or checkout, through queue depth, wait time, and service cycle duration. DEPLOY (save) measures staffing efficiency: idle or over-staffed capacity that could be redeployed to where demand actually is. Together the three give store and area managers one reading of what their store needs on any given day, and what it is worth acting on first.

ATTRACT

The grow gauge, the first of Storalytic's three. ATTRACT measures commercial engagement at the zone level: what proportion of zone visitors become Clear Lingerers. A low ATTRACT score indicates that traffic is reaching a zone but not converting to engagement, pointing to display, signage, product mix, or layout issues. ATTRACT measures the front end of the physical conversion funnel, and expresses the distance to the next gear as € within reach.

SERVE

The protect gauge, the second of Storalytic's three. SERVE measures service quality at zones where staff interaction or transaction processing occurs: consultation points, service counters, and checkouts. It captures queue depth, average wait time, and service cycle duration. SERVE leads with minutes against target. Where a euro is shown, it is sales at risk (est.), a modelled range that is never summed.

DEPLOY

The save gauge, the third of Storalytic's three. DEPLOY measures staffing efficiency: how well staffed hours line up with the demand actually present on the floor. It shows checkout staff hours you could move: lanes staffed while nobody is waiting, priced as a saving. DEPLOY is deliberately not a measure of movement, congestion, or bottlenecks: queue and waiting time belong to SERVE, and counting them twice would overstate the opportunity.

Pattern Classification

The colour-coded chip Storalytic assigns to every zone, describing what is happening in that zone's funnel. It is a diagnostic label: it points to the lever with the most headroom, so the first action is obvious. There are six patterns.

Strategic Positioning

A merchandising view that plots each product zone on two axes: its share of store visitors, and the euro it earns per visitor. Where Pattern Classification says what is wrong inside a zone's funnel, Strategic Positioning says what role the zone plays in the store as a whole. It sorts zones into four roles.

EdgAlytic

Storalytic's proprietary edge computing device deployed inside retail stores. The EdgAlytic device connects to existing CCTV or IP cameras and runs AI computer vision models on the device, inside the store.

Allen

The companion who carries the loop. Allen is a role, not a technology: it translates zone-level behavioural data into plain-language operational recommendations: naming what is within reach, flagging anomalies, answering questions about the store in everyday language, and delivering daily and weekly summaries without requiring analytical skill from the store team. Allen also carries the PROVE step back to the floor, reporting whether the last change actually worked. It is the interface between what the platform measures and the people who act on it.

Computer Vision (retail)

The application of AI image analysis models to video feeds from retail store cameras to extract behavioural data about visitor movement, dwell, and engagement. In retail, computer vision replaces manual observation with continuous, objective, zone-level measurement. Storalytic's computer vision models detect presence, assign tracking numbers and classify behaviour on the device in the store, with zone metrics aggregated each trading day. The output is structured numerical data: counts, durations, and classification rates.

Zone Analytics

The practice of measuring and analysing visitor behaviour within discrete, defined areas of a physical store, rather than treating the store as a single undifferentiated space. In Storalytic, zones are defined during deployment (product areas, displays, service counters, checkout, entrance) and each zone becomes an independently measurable unit. Zone analytics enables funnel analysis at the product-area level: how many visitors entered, how many engaged, how many converted, and where growth is within reach.

Dwell Time

The duration for which a visitor remains within a defined zone. Dwell time is measured per zone visit and aggregated to produce average dwell times, dwell time distributions, and dwell-by-segment breakdowns (Walk-By, Short Lingerer, Clear Lingerer). Dwell time is a core input into engagement classification: longer, more consistent dwell is a precondition for Clear Lingerer status. It is also used to diagnose specific friction points: unusually short dwell at a high-margin zone indicates a display or product communication failure.

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