Functionality

The tool analyzes product prices and user behavior to send highly relevant discount alerts. This allows you to build campaigns that target users with products they have already considered, increasing the likelihood of conversion.

• Identifies Significant Price Drops: Scans for products that have had a significant price decrease within the last 24 hours.
• Checks Product Availability: Filters recommendations to only include items that are currently in stock and available for purchase.
• Targets Interested Shoppers: Finds users who have viewed these specific products but have not yet made a purchase.
• Prioritizes Top Products: Recommends products based on the highest percentage price drop and overall popularity to maximize engagement.

How it Works

1. Identify Recent Product Viewers: The system begins by identifying users who have viewed products within the timeframe defined by the `Activity Window` (e.g., the last 30 days).
2. Calculate Price Change: It then compares the current inventory data with a snapshot from one day ago to calculate the exact percentage decrease in price for each product.
3. Apply Change Filters: The tool first filters this list to only include products with a price decrease greater than the configured `Minimum Price Drop %` threshold. A second check is performed to ensure these products are currently available and meet the `Minimum Stock Level`.
4. Exclude Converted Users: To ensure recommendations are relevant, the system filters out users who have already purchased the discounted product within the `Activity Window`.
5. Rank and Recommend: Finally, for each eligible user, the system ranks the matching products by the magnitude of the price change and its popularity score. It then delivers the top N products based on the `Number of Recommendations` setting.

Visualizing the Process

Configurable Parameters & Terminology

Understanding these parameters can help you fine-tune your campaigns to better align with your business goals:

• Minimum Price Drop %: The minimum percentage decrease in price required to trigger a recommendation.
• Activity Window: The number of past days considered when evaluating a user's product views and purchase history.
• Number of Recommendations: The maximum number of products to recommend to a single user.
• Minimum Stock Level: The stock threshold an item must meet to be considered available for recommendation.

Outputs & Data Points

The system generates these key outputs to populate your campaigns:

• userid: The identifier for the user who viewed the product.
• product_id: The unique identification code for the product.
• sku_id: The SKU identifier for the product.
• variant_id: The variant identifier for the product.
• item_name: The name of the recommended product.
• product_description: A description of the product.
• product_url: The URL linking to the product page.
• product_image: The URL for the product's image.
• release_date: The release date of the product.
• previous_price: The product's price before the drop.
• current_price: The new, lower price of the product.
• price_change_percentage: The calculated percentage of the price drop.
• popularity_score: The popularity score of the product.
• rating: The rating score of the product.

Data Integration Requirements

For seamless operation, the tool integrates with the following data sources:

• PRODUCT VIEW events (Mandatory): Used to identify which products a user has shown interest in. Key fields include userid, url, and product_id.
• Online Order events (Mandatory): Used to exclude users who have already purchased the product. Key fields include userid and product_id.
• Inventory (Mandatory): Contains product metadata, pricing, and stock levels. Key fields include price, stock, product_id, sku_id, variant_id, isavailable, release_date, product_image, product_description, and product_url.