E-Tailing

As more consumers switch to online retailing as their primary channel, data analytics can help you be more nimble and gain a larger market share. Behavioral targeting and personalization requirements are driving up the need for larger data sets and more atomic-level data analysis. You can now segment the long tail of customers and products at a more atomic level to provide the right product to the right customer at the right time.

Aster Data provides the analytic horsepower required on a massive scale for e-tailing applications such as:

• Recommendation engines – increase average order size by recommending complementary products based on predictive analysis for cross-selling.
• Cross-channel analytics – sales attribution, average order value, lifetime value (e.g., How many in-store purchases resulted from a particular recommendation, advertisement, or promotion).
• Event analytics – what series of steps (golden path) led to a desired outcome (e.g., purchase, registration, etc.).
• Segmentation – loyalty campaigns and offers to distinct segments and individuals.

Web analytics – path analysis, attribution, user engagement, and more. This is critical in making relevant e-tail site design decisions to deliver the right content and advertisements to the most relevant user segments, improving their shopping experience.

Common issues impacting e-tailing data warehouses: