Advanced Retail Analytics
The analytical layer across every Cybex solution — merchandising, assortment, allocation, sales audit, CRM, online, POS, and omnichannel. AI insights and BI analytics, unified on a single conformed data platform.
BI plus AI, on one data foundation
Most retailers run two parallel analytical stacks: a BI stack producing last week's dashboards, and an AI stack producing forward-looking models that rarely make it into anyone's working routine. The analytical tax is paid twice — once on integration, once on interpretation — and the answers rarely agree.
Cybex Advanced Retail Analytics collapses that stack. Every solution module — merchandising, assortment, allocation, sales audit, CRM, online, POS, and omnichannel — draws from the same conformed data platform and feeds both the historical BI view and the predictive AI view. One source, two lenses, aligned by construction.
The two analytical lenses
Every module delivers analytical value in two complementary forms: BI analytics for the operating rhythm, and AI insights for forward-looking decisions.
BI Analytics
Retrospective · Diagnostic
Dashboards, KPI scorecards, ad-hoc queries, and scheduled reports. Answers the question: what happened, and why? The operating cadence every retailer already runs — only unified, governed, and real-time on the Cybex data platform.
AI Insights
Predictive · Prescriptive
ML-driven forecasts, anomaly detection, recommendations, and natural-language narratives. Answers the question: what is about to happen, and what should we do? Wired into the same screens and workflows the BI layer already uses.
Analytics across every solution module
Each Cybex solution exposes purpose-built BI analytics and AI insights tailored to the decisions that function actually makes. Together they form a unified analytical surface over the retail operating model.
Merchandising & Replenishment
BI: PVM decomposition, LY/TY comp reporting, sell-through scorecards, vendor performance.
AI Insights: Demand sensing, price elasticity, promotional lift attribution, new-item forecasting, margin-at-risk alerts.
Assortment Planning
BI: Range depth/breadth reports, cluster performance, seasonal carry-forward, open-to-buy visibility.
AI Insights: Style-level demand forecasting, attribute affinity modelling, cluster-level optimisation, white-space detection.
Allocation & WMS
BI: Weeks-of-supply monitoring, allocation exception reports, DC throughput dashboards, transfer logs.
AI Insights: Demand-weighted store tiering, size-curve optimisation, transfer recommendation engine, DC workflow orchestration.
Sales Audit
BI: Transaction exception reports, tender reconciliation, discount compliance, void/return tracking.
AI Insights: Transaction anomaly detection (z-score, isolation forest), shrinkage forecasting, associate risk scoring, fraud pattern recognition.
CRM & Loyalty
BI: RFM dashboards, cohort retention curves, campaign attribution, program-health reports.
AI Insights: Churn prediction, customer lifetime value modelling, next-best-offer recommendations, segment migration alerts.
Online & eCommerce
BI: Shopify/Magento performance dashboards, funnel conversion, cart abandonment, channel mix reporting.
AI Insights: Digital demand forecasting, session-level propensity scoring, product recommendation engine, search intent analysis.
POS & MPOS
BI: Hourly sales tracking, associate scorecards, basket analysis, real-time store performance.
AI Insights: Clienteling recommendations at checkout, upsell/cross-sell prediction, associate coaching signals, basket-level loyalty propensity.
Omnichannel
BI: Unified customer view, cross-channel attribution, inventory position across stores and web, BOPIS/ship-from-store reporting.
AI Insights: Channel preference modelling, cross-channel journey prediction, optimal fulfilment routing, unified-inventory optimisation.
Workflow Automation
BI: Task cycle-time reports, workflow exception tracking, SLA monitoring, throughput dashboards.
AI Insights: Predictive task sequencing, workload forecasting, adaptive routing, bottleneck detection.
Store Operations
BI: Traffic vs. labour dashboards, conversion by day-part, employee performance scorecards, store-cluster benchmarks.
AI Insights: Hourly traffic forecasting, labour-to-demand alignment, conversion driver analysis, weather-adjusted planning.
Pricing & Promotion
BI: Price history, competitive indexing, markdown cadence, promotion ROI reports.
AI Insights: Elasticity modelling, markdown timing optimisation, competitive price response, promotional lift forecasting.
Inventory & Working Capital
BI: Turn velocity, cash-conversion cycle, aged-stock reports, service-level monitoring.
AI Insights: Inventory productivity modelling, stockout risk forecasting, working-capital simulation, service-level trade-off analysis.
The AI Insights workflow
Every AI insight on the platform follows a consistent, auditable workflow. Reusable, governed, and available to every solution module.
Build a governed dataset on the conformed data model for the insight subject — with quality checks, lineage, and SLAs.
Define the analytical brief — what to compute, what models to apply, what format to return. Encodes domain knowledge explicitly.
Dataset plus instruction submitted to the AI engine — statistical models, ML, time-series, and narrative generation run in a single pass.
Analyst reviews results. Refine the instruction for additional depth, different cuts, or alternative framings — iterate until the insight is production-ready.
Persist the query, wire it into BI dashboards, schedule refreshes, and publish to the Cybex BI Module for every stakeholder.
Refined instructions saved as reusable templates — sharable across teams, applicable to new datasets, consistent methodology maintained.
For the complete workflow and workflow examples, see Retail AI Insights.
Advanced analytical capabilities
Every insight generated on the platform benefits from built-in statistical, ML, and forecasting capabilities — available uniformly to every module.
ML anomaly detection
Isolation forests, z-score analysis, DBSCAN clustering. Surfaces outliers in sales, inventory, and customer behaviour without manual threshold tuning.
Time-series forecasting
ARIMA, exponential smoothing, Prophet, and neural network models for demand, traffic, and sales forecasting with confidence intervals.
Statistical analysis
Regression, correlation, variance decomposition, hypothesis testing — built into every insight, no separate tooling required.
Retail-specific KPIs
Sell-through, weeks-of-supply, GMROI, comp sales, UPT, ATV, conversion — 50+ specialty retail metrics engineered into the model.
Natural-language narratives
AI-generated executive summaries explaining what happened, why, and what to do next — in plain language ready for leadership review.
Causal attribution
Decompose observed variance into underlying drivers — mix, price, traffic, conversion, channel — with defensible methodology.
Where analytics are delivered
Analytics meet users where they already work — no separate tool, no separate login, no separate learning curve.
Cybex BI Module
Matrix and ad-hoc query tools built into the platform. Role-based dashboards for store, district, and corporate users. Live refreshes and drill-down across every module.
Embedded in solutions
Analytics rendered inside the working screens of each solution — allocation, merchandising, CRM — so insights shape the decision at the moment it is made.
Dashboards
Role-based dashboards for store, district, corporate, and executive users. KPI scorecards, trend views, and exception lists — refreshed continuously, with drill-down and filter across every dimension.
Real-time alerts
Threshold- and ML-based alerting into the channels your teams already use. Anomalies flagged in minutes, not tomorrow morning's report.
Feature APIs
Governed REST/GraphQL APIs expose curated features and insights to your internal systems — allocation engines, pricing tools, third-party apps.
Executive app
Purpose-built dashboards for CEO, CFO, CMO, and CIO. The numbers that matter, refreshed continuously, with drill-down and AI-generated commentary.
Measurable outcomes
What retailers realise when analytics graduates from reporting artefact to operating layer.
Forecast accuracy
Hourly traffic and daily demand forecast accuracy after 90 days of model training on your data.
Labour cost reduction
Delivered through demand-aligned staffing — service levels held or improved.
Gross margin lift
From integrated pricing, markdown, and assortment insights deployed into merchant workflows.
Reporting-cycle compression
Weekly and monthly reporting cycles compressed as analysts shift from data preparation to analysis.
Deployment & integration
We partner with your team to deploy Advanced Retail Analytics against your unique solution footprint, source systems, and operating cadence. A typical engagement follows four phases.
Integration
2–3 Weeks
Connect source systems — POS, ERP, Shopify/Magento, WMS, CRM, labour, traffic counters. Map native schemas to the Cybex conformed data model.
Model training
2–3 Weeks
Train forecasting, anomaly, and classification models on your historical data. Calibrate thresholds and business rules to your policies.
Dashboards & insights
2–4 Weeks
Deploy role-based dashboards, scheduled reports, real-time alerts, and module-embedded insights across the solution footprint.
Training & adoption
1–2 Weeks
Train store, district, corporate, and executive users on the new analytical surface. Establish the operating rhythm that turns analytics into decisions.
Related essays from The Cybex Quarterly
The published thinking behind the analytical practice — reading the essay is the closest thing to sitting through the first three days of fieldwork.
Essay 08 · Retail Analytics
What belongs in a unified analytics environment — and what most retailers still keep stranded in spreadsheets.
Essay 09 · Data Science & AI
A practical taxonomy — which problems earn classical ML, which earn deep learning, and which earn neither.
Essay 07 · Forecasting Demand
Multi-horizon forecasts that respect seasonality, promotional lift, and the noise of new-product launches.
Essay 11 · Customer Traffic
Weighted historical averages with seasonal correction — translating forecast to staffing schedule.
Essay 05 · Predictive Store Ops
Traffic forecasting, task prioritisation, and staffing models that hold service levels while lowering labour cost.
Retail AI Insights
The complete AI Insights workflow — curate dataset, author instructions, review, refine, promote, reuse.