Why should you care?

Product and growth teams ask questions find() cannot answer. A reusable pipeline becomes the source of truth for a metric.

See it live — copy this example

Open mongosh or MongoDB Compass, select database nosqlverse, then run the example. Change one field and run again.

db.orders.aggregate([
  { $match: { status: "paid", placedAt: { $gte: ISODate("2026-07-01") } } },
  { $group: {
      _id: { $dateToString: { format: "%Y-%m-%d", date: "$placedAt" } },
      revenue: { $sum: "$total" },
      orders: { $sum: 1 }
  }},
  { $sort: { _id: 1 } },
  { $project: { date: "$_id", revenue: 1, orders: 1, aov: { $divide: ["$revenue", "$orders"] }, _id: 0 } }
])

Run Example »

Edit the code below and click Run to see the result in Toolliyo’s live editor.

What happened?

• Filter paid July+ orders.
• Group by calendar day string.
• Sort chronologically.
• Project AOV as revenue/orders.

Practice next

1. Seed orders across several days.
2. Run the pipeline.
3. Add tenantId to $match for SaaS.
4. Group by week using %G-W%V style formats.
5. Add $facet for revenue + top SKUs together.

Remember

Analytics = match → group → sort → project. Compute KPIs like AOV in-pipeline. Prefer secondaries for heavy jobs.

Daily GMV chart

Finance plots revenue by day for the festival week.

Outcome: The chart’s API is this aggregation.