// ADVANCED AI
Predictive Analytics:
Know What Your Customers Will Buy Tomorrow.
If you only look at past data, youre flying blind. With Xanevo's Predictive Analytics you use deep-learning models to compute valid future scenarios from your ERP and market data. For pinpoint inventory, reduced capital lock-up, and maximum delivery capability. Statistics on steroids, based on the quality of your golden records.
More than reactive reporting.
01
Demand planning
Precise forecasts for purchasing
02
Trend analysis
Early detection of market shifts
03
Inventory optimization
Reduce capital lock-up
What benefit does predictive analytics deliver in e-commerce?
Predictive analytics transforms historical transaction data into forward-looking actions. By combining internal ERP data with external market factors, sales forecasts emerge that reduce overstock by up to 20 percent while securing delivery capability for trending products. Forecast quality correlates directly with input data quality, so we check the consistency of your data through the Legacy-to-AI Bridge before any model training. No clairvoyance, statistically founded probabilities with clear confidence intervals.
// COMPARISON
Reactive reporting vs. predictive analytics
Aspect
Traditional reporting
Xanevo predictive analytics
Focus
Retrospective: what happened?
Prospective: what will happen?
Decision
Manual based on experience
Data-driven probabilities
Inventory
Safety stocks as buffer
Dynamic, demand-aligned levels
Trend response
Reactive (after out-of-stock)
Proactive (before trend peak)
Data base
Sales history only
History plus external signals plus seasonality
// PRODUCT MODULES
Three modules for forecasting, trend detection, and data integration
Module 1: Demand forecasting, Intelligently steer inventory
Analysis of historical sales cycles and seasonalities. Consideration of marketing campaigns and holidays in the forecast. Automated purchase suggestions for the buying team, with clear confidence interval. Out-of-stock situations are prevented while capital lock-up through overstock drops.
Module 2: Trend detection, Anticipate the market
Integration of external signals: social media, competition, weather, search volume. Early warning system for declining interest in core assortments. Strategic support for category management. Trends are detected before they become hype, and before the assortment sells out.
Module 3: Data readiness and integration
A precise forecast is only as good as its source. As part of our Advanced AI Services we first check the consistency of your data through the Legacy-to-AI Bridge to ensure your models run on valid golden records. Results flow through defined interfaces back into SAP, Dynamics, or your BI tool.
// FAQ
Three questions operations managers and CFOs ask
Typically 12 to 24 months of clean transaction data from your ERP suffice to detect first reliable seasonality patterns. For products with longer purchase cycles (capital goods, durable consumer goods) we need more history, we check this in the data readiness assessment.
While black-swan events are hard to calculate, predictive analytics massively shortens reaction time by detecting anomalies immediately. Instead of talking about declines after weeks, the alert comes within hours. That drastically shortens reaction time compared to classic monthly reporting.
Through our Legacy-to-AI Bridge with established connectors. We read transaction and master data from SAP, calculate the forecast outside, and write purchase suggestions back into SAP materials management. No interference with SAP logic, no risk to existing workflows.
// PREDICTIVE ANALYTICS
We analyze your forecast potential
Give us an excerpt of your transaction history. We compute a demand-forecasting model for one of your product categories and show concretely where you would reduce capital lock-up or lift delivery capability. Pseudonymized, in two weeks.