Glossary
Retail Intelligence: Key Terms Defined
The language of physical retail intelligence — from visitor segmentation to store governance. All terms as defined and used by Storalytic.
Visitor Segmentation
Clear Lingerer
A store visitor who remains in a defined zone for long enough, and with sufficient behavioural consistency, 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 using kernel density estimation (KDE) and Gaussian mixture model (GMM) algorithms 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.
Short Lingerer
A store visitor who pauses in a zone briefly — longer than a walk-by, but not for long enough or with enough behavioural consistency 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.
Core Concepts
Governance Framework
ATTRACT / SERVE / FLOW
Storalytic's three-gauge operational governance framework for physical retail stores. ATTRACT measures the effectiveness of zones and displays at drawing visitors in — specifically the rate at which visitors transition from Walk-By or Short Lingerer to Clear Lingerer. SERVE measures the quality and speed of service delivery at points of assistance, consultation, or checkout — primarily through queue depth, wait time, and service cycle duration. FLOW measures the capacity and efficiency of movement through the store — identifying congestion, bottlenecks, and dead zones. Together, the three gauges give store managers and area managers a single operational dashboard that tells them what their store needs on any given day.
ATTRACT
The first of Storalytic's three operational gauges. 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 is the metric that governs the front end of the physical conversion funnel.
SERVE
The second of Storalytic's three operational gauges. 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. A low SERVE score indicates that engaged visitors are being lost or frustrated at the point of service — turning potential conversions into abandoned transactions.
FLOW
The third of Storalytic's three operational gauges. FLOW measures the capacity and efficiency of visitor movement through the store as a whole. It identifies congestion zones, underutilised pathways, and temporal patterns in store occupancy. A low FLOW score indicates structural inefficiency in the store layout or in how visitor distribution is managed across peak periods.
Technology
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 locally — on-premises, inside the store. Video is processed entirely on the EdgAlytic device and never transmitted to any external server. Only anonymised, aggregated behavioural metrics leave the store. The EdgAlytic architecture is the foundation of Storalytic's privacy-by-design approach and is the hardware equivalent of the Offline Cookie concept.
Allen
Storalytic's AI assistant layer. Allen translates zone-level analytics data into plain-language operational recommendations — surfacing missed-value opportunities, flagging anomalies, and delivering daily and weekly performance summaries to store managers without requiring data analysis skills. Allen is the interface between the Storalytic intelligence layer and the store teams 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 human presence, assign anonymous movement identifiers, classify engagement behaviour, and compute dwell time — all in real time, on-premises. The output is not video or images but structured numerical data: counts, durations, and classification rates.
Analytics
Missed Value
The estimated revenue opportunity lost in a zone where Clear Lingerers — visitors who have demonstrated active purchase intent — did not proceed to a transaction. Missed Value is calculated by multiplying the number of non-converting Clear Lingerers by the average transaction value associated with that zone's product category. It is the primary commercial urgency metric in Storalytic's dashboard: it quantifies what the store left on the table, not just in aggregate but zone by zone and time period by time period.
Engaged Value
The total estimated revenue potential represented by all Clear Lingerers in a zone during a given period. Engaged Value = number of Clear Lingerers × average zone transaction value. It represents the commercial opportunity that entered the zone, regardless of whether it converted. Engaged Value and Missed Value together define the conversion efficiency of a zone: Missed Value / Engaged Value = the gap rate.
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 value was lost.
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.
Privacy & Compliance
GDPR Compliance (in-store AI)
The regulatory framework governing the use of AI computer vision in physical retail environments under the European General Data Protection Regulation. Storalytic's architecture is designed for GDPR compliance by default: video is processed locally on EdgAlytic edge devices (never transmitted), only anonymised aggregated data is stored and transmitted, no facial recognition is used, no biometric data is collected, and no individual can be identified from the data Storalytic produces. Processing is justified under Article 6(1)(f) — legitimate interest for operational improvement — where individual identification is not possible.
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