As a retailer, you face a combination of challenges. You must optimize operational efficiency in-store and across the supply chain while building strong, increasingly individualized relationships with customers.
Dashboards and reports are useful for tracking performance. But they fall short in helping you determine specific drivers of performance or to find opportunities to increase revenue. You need a data discovery tool that lets you analyze multiple dimensions in an intuitive way, and drill down into details when issues are found.
Heat Map Explorer helps you:
- Analyze your products within your full product hierarchy.
- See gaps and opportunities for new and emerging products.
- Identify operational issues across categories, sales associates, customer segments or stores.
- Find high-potential customer segments and track their behavior.
- Analyze store layouts to optimize product placements and promotions.
- Find rapidly growing niche products deep within your product hierarchy.
- Identify poorly performing products and product categories.
- Compare volume vs growth to focus on the products poorly performing in both.
The top heat map shows a typical bar chart of sales by product category. Color indicates change from the prior period: green for increased sales, red for decreased sales.
The bottom heat map shows the increased depth Heat Map Explorer provides. The sub-categories driving the revenue loss in Premium Cosmetics are easy to identify. In Hair Care and Bath & Shower, red sub-categories hidden on the basic bar chart indicate other revenue loss.
- Analyze performance and targets over time across multiple stores.
- Distinguish regional patterns from problems limited to particular locations.
- Apply filters to view performance by specific product categories or store types.
This heat map shows the performance of four stores over a 12-month period. The size of each bar shows total sales. Green bars exceeded the target sales, while yellow and red bars fell short.
The Haw Creek store at the top exhibited consistently degraded performance until it was closed in November. The Swannanoa store at the bottom has consistently done well, matching or exceeding target sales for 9 of the past 12 months.
- Visually analyze Big Data at a deep to gain critical insights.
- Analyze market baskets to identify promotion and placement opportunities.
- Integrate directly with your web Big Data analytics platform.
This heat map shows the output of a market basket analysis for a target product. Size indicates the number of transactions that included each category and sub-category and color indicates the likelihood that sub-category was purchased within the target product.
- Analyze how product placement affects performance within stores.
- Filter by customer type, product category or active promotions.
- Search to find specific products or hover over any element for full details.
This heat map shows the output of a market basket analysis, mapping correlations of one product to the locations of other products bought with that product. This allows you to understand how customers move through the store and how the location of related products drives sales.
- Visualize demographic and economic performance data by geography.
- Import your own geographic maps and link to your Excel & SQL data.
- Use interactive filters to analyze slices of your data.
- Easily switch from geographic and category views of a single dataset.
This heat map shows the price of milk relative to the national average. Green counties are less than the national average, yellow & red counties are greater. In Heat Map Explorer, you can hover over any county to see all the data for that county, or zoom in to get a closer look at the map.