{
    "action": "tool_call",
    "reasoning": "The question asks for natural segmentation approaches. I have basic country-level stats showing 15 countries with India (code 1) dominating at 8,652 restaurants. To identify meaningful segments, I should examine the key dimensions: cuisines (1,851 distinct), cities (147), price ranges (4), rating tiers, and service features (online delivery, table booking). Let me start by looking at the distribution across price ranges and rating categories, which are likely to reveal natural customer/market segments.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT \"Price range\", \"Rating text\", COUNT(*) as restaurant_count, ROUND(AVG(\"Aggregate rating\"), 2) as avg_rating, ROUND(AVG(\"Average Cost for two\"), 0) as avg_cost, ROUND(AVG(\"Votes\"), 0) as avg_votes FROM raw.\"Zomato Restaurant Dataset\" GROUP BY \"Price range\", \"Rating text\" ORDER BY \"Price range\", avg_rating DESC",
        "purpose": "Examine the natural segmentation by price range and rating quality to identify market tiers",
        "source": "raw"
    }
}