I want to get continuous structured data on competitor trade promotion strategies, shelf placements, and in-store merchandising tactics from major European e-commerce grocery and retail websites.

Goal

I want to get continuous structured data on competitor trade promotion strategies, shelf placements, and in-store merchandising tactics from major European e-commerce grocery and retail websites.

Source coverage

• aldi.de
• lidl.de
• rewe.de
• euroshop.de
• dm.de
• rossmann.de
• kaufland.de
• metro.de
• toom.de
• real.de
• groceryshopping.de
• preisvergleich.de

Sample data

Illustrative sample data from the original configuration, not live or verified results.

Insights and analytics

• Total Competitor Promotions Monitored (metric)
• Top 5 Retailers by Trade Promotion Frequency (bar)
• Monthly Trends in Shelf Placement Changes (line)
• Promotion Type Distribution (donut)
• Top Merchandising Tactics by Retailer (horizontal_bar)
• Current Trade Promotions by Retailer (table)
• Cumulative Promotions Over Time (area)
• Average Discount Offered (metric)
• Shelf Placement Categories by Retailer (pie)
• In-Store Merchandising Tactics Trend (line)
• Key Observations on Competitor Strategies (insights)
• Detailed Promotions Analysis by Retailer (table)

Change notifications

• Price Change Detected — is now €2.50 (-€0.50) aldi.de
• New Listing Appears — now available rewe.de
• Product Unavailable — is out of stock dm.de
• Coverage Gap Found — missing from catalog kaufland.de
• Menu or Listing Updated — price updated to €15.99 rossmann.de

Integrations and delivery

• api
• google-sheets
• salesforce
• email

Make this your own

Start with this goal in Jsonify, then choose the sources and data you need.