Breakdown 1st party vs third party (marketplace) product exposure for key queries

[emirbelkahia]

Context

Understanding how much visibility is given to first-party (1P) versus third-party (3P) products is increasingly important for strategic retailers, especially those with marketplaces and house brands.

This question is becoming more frequent from the field and even surfaces in executive-level reporting. CSMs and clients need a simple way to break down exposure by product source across popular queries to evaluate balance, fairness, and potential business bias.

Opportunity

MCP can deliver strategic value by:

1. Analyzing the top queries and identifying how results are split between 1P and 3P products.
2. Calculating ratios and counts per segment (e.g. % of impressions or top N results that are 1P).
3. Visualizing the result in a clear breakdown or chart-ready structure.
4. Flagging over- or under-exposure patterns that might require ranking adjustment or business escalation.

As most e-commerce players launching marketplaces are still exploring how to best rank 1P vs 3P products, there’s no universal best practice yet. In the absence of a clear conviction, the ability to measure and surface structured insights becomes essential. MCP can help clients observe exposure patterns, experiment safely, and inform future ranking decisions.

Proposed behavior

The MCP node should:

• Retrieve analytics data and match it against product date (e.g. "productFamily", or "isMarketplace" attribute).
• For the top N queries (e.g. top 10 by volume):
  • Count 1P and 3P results in the top search positions (e.g. top 10).
  • Return % breakdown per query.
  • Format the data for easy charting or reporting (e.g. Recharts-compatible format).
• Optionally highlight cases where the split is extreme (e.g. 100% 3P) and could require review.

Example prompt

Can you analyze my top 10 queries and show me the breakdown of 1P vs 3P product visibility in search results?

Expected output

{
  "queryBreakdown": [
    {
      "query": "garden table",
      "1P_percentage": 35,
      "3P_percentage": 65
    },
    {
      "query": "plancha",
      "1P_percentage": 70,
      "3P_percentage": 30
    }
  ],
  "recommendations": [
    "⚠️ 'garden table' heavily favors 3P. Consider boosting selected 1P SKUs if aligned with business goals.",
    "✅ 'plancha' has a healthy 1P/3P balance."
  ],
  "chartReadyFormat": {
    "labels": ["garden table", "plancha"],
    "datasets": [
      { "label": "1P", "data": [35, 70] },
      { "label": "3P", "data": [65, 30] }
    ]
  }
}

Value

• Provides clients with visibility on how different sources are represented in search.
• Helps identify alignment (or misalignment) with commercial priorities.
• Supports CSMs in strategic conversations with marketplace stakeholders.
• Makes it easier to track exposure shifts over time or across campaigns.

Notes

• Assumes presence of a reliable productFamily or similar attribute.
• Could evolve into a recurring audit capability (e.g. monthly report generation).
• Future version could let users simulate the effect of boosting one segment.