Описова аналітика

Descriptive analytics is the process of collecting and analyzing historical and real-time business data to answer the question "what is happening right now?" In retail, it covers sales performance, price dynamics, product turnover, supplier operations, assortment behavior, and customer activity — all structured into a clear, accessible picture for decision-making.

Datawiz BI collects data from a retail chain's systems and organizes it into more than 30 ready-made interactive reports across four main categories: sales, assortment, loyalty program customers, and promotions and marketing. Reports update continuously and can be filtered by store, category, brand, time period, and other dimensions without requiring manual data preparation.

Datawiz BI provides 130 standard indicators covering profit, revenue, average receipt, product turnover, price dynamics, order quantity, loyalty program data, and the number of days a product was not sold. All metrics can be broken down by store, region, category, brand, or individual SKU, and monitored across any time period — including intraday analysis.

Beyond the 130 standard metrics, Datawiz BI allows users to build custom indicators using the Formula Builder. This means teams can define metrics that reflect their specific business logic — for example, chain-specific margin calculations or composite KPIs — without relying on IT or development resources.

Descriptive analytics answers "what happened and what is happening now" — it structures historical and real-time data into reports and dashboards. AI analytics in Datawiz BI goes a step further, answering "why it happened" and "what will happen next" through machine learning models that detect hidden patterns, forecast demand, and generate automated recommendations. Both layers are available within the same platform.

Datawiz BI provides constant access to up-to-date data, with reports reflecting changes throughout the day. This allows retail teams to monitor key indicators at multiple points during business hours and respond quickly to deviations in sales, stock, or pricing without waiting for end-of-day summaries.

Descriptive analytics in Datawiz BI is used across multiple roles: category managers track assortment performance and promotion effectiveness, store managers monitor store-level KPIs, top managers review chain-wide revenue and profit dynamics, marketers analyze customer behavior and loyalty program results, and analysts build custom reports and dashboards for deeper investigation.

Retail chains using Datawiz BI report measurable improvements across key metrics: a 13% reduction in lost sales, a 15.5% decrease in excess inventory, an 11.2% increase in average check, and a 28% improvement in financial results per SKU. These outcomes result from faster detection of underperforming products, timely stock adjustments, and data-driven decisions on assortment and promotions.

Datawiz BI offers a free trial and an interactive demo environment where users can explore the full report library, test filtering and drill-down functionality, and evaluate how the platform works with sample retail data — no credit card required.