The price dashboard indicates the difference between the planned price and the price collected at the Point of Sale. Thus creating a gap in the price analysis that is used to identify which products are being sold above or below the planned price. In addition, the page is designed to provide a comprehensive view of how product prices in the market compare to the prices you observe during your routine visits to the store. By analyzing these components, you can gain insights into how in-store prices align with target prices and identify any significant discrepancies.

Components

Map View (Bottom Half): This section shows a map that identifies the location and address of stores. It provides geographic context, allowing you to see where each price data point originates.

Price chart (bottom half):

Green Line: Represents the average price of the product across all stores. The median gives a central value, filtering out extreme highs or lows.

Blue Line: Indicates the average price, providing a general idea of ​​the overall price trend.

Salmon Bars: Shows price variation, highlighting the range between the highest and lowest prices observed. The horizontal axis lists the product names, while the vertical axis displays a price scale, such as 0, 50, 100, 150.

Information Cards (Top): These cards show percentages related to price variations:

Median Variance: Percentage difference between the target price and the observed median price. Average Variance: Percentage difference between the target price and the average observed price. Maximum Variance: The largest percentage difference observed from the target price.

Minimum Variance: The smallest percentage difference observed from the target price.

Filter

At the top of the Price Analysis page, there is a section dedicated to filters. This feature allows you to refine the data displayed based on specific criteria, ensuring that the analysis is tailored to your exact needs. Here are the available filters:

1. Date Range: Select a specific time period to display price data for a specific period.

2. Customer Territory: Filter data based on customers’ geographic or regional territories.

3. Customer Category: Refine results by different customer categories, allowing for more segmented analysis.

4. Customer Name: Display pricing data for a specific customer by selecting their name from the list.

5. Product Category: Focus on a particular product category to understand its pricing trends. ]

6. Product Brand: Narrow your analysis to a specific brand and see how your products are priced across all stores.

7. Product Name: Dig deeper into the pricing details of a specific product.

8. Group by: Organize the displayed data by different criteria, such as brand, product category, or customer territory, to obtain a structured view. By using these filters, you can customize the view to highlight the most relevant information, making your analysis more accurate and actionable.