Recipes

Realistic dashboard questions, each with a working query.

Each recipe is a complete query you can adapt. Recipes combine the operations from the previous pages, so they are the quickest way to see how the pieces fit together.

Choosing an operation

  • How many events? use count()
  • How many per period? use timeseries()
  • How many distinct? use unique()
  • What are the values? use aggregate()
  • Split by a field? use groupBy()
Build a query
Filters
Condition
Field
Operator
Value
Query code
Recipes
Signups per day
typescript
const signups = await vanta.timeseries({
  filters: filter('type', 'equals', 'user.signup'),
  interval: 'day',
  time: timeRange('2024-01-01T00:00:00Z', '2024-01-14T23:59:59Z'),
})
Returns one bucket per day with the signup count, aligned to UTC. Quiet days appear as gaps.
Unique active users this week
typescript
const activeUsers = await vanta.unique({
  field: 'userId',
  filters: filter('type', 'equals', 'user.active'),
  time: timeRange('2024-06-24T00:00:00Z', '2024-06-30T23:59:59Z'),
})
Distinct users who sent an active event in the week. A user active every day counts once.
Average order value
typescript
const averageOrderValue = await vanta.aggregate({
  filters: filter('type', 'equals', 'purchase'),
  aggregations: [{ name: 'aov', field: 'data.amount', operation: 'avg' }],
  time: timeRange('2024-01-01T00:00:00Z', '2024-12-31T23:59:59Z'),
})
Averages the amount stored on every purchase event. Swap the operation for sum to get total revenue instead.
Checkout completion by country
typescript
const byCountry = await vanta.groupBy({
  groupBy: ['context.country'],
  filters: filter('type', 'equals', 'checkout.completed'),
  time: timeRange('2024-01-01T00:00:00Z', '2024-12-31T23:59:59Z'),
})
Groups completed checkouts by country, with the count for each. Add a second field such as data.plan for a finer breakdown.
Top plans by usage
typescript
const byPlan = await vanta.groupBy({
  groupBy: ['data.plan'],
  filters: filter('type', 'equals', 'purchase'),
  time: timeRange('2024-01-01T00:00:00Z', '2024-12-31T23:59:59Z'),
})
One group per plan with the number of purchases. Add a filter for a specific period to track a plan's momentum month over month.
Page views over time
typescript
const pageViews = await vanta.timeseries({
  filters: filter('type', 'equals', '$page'),
  interval: 'hour',
  time: timeRange('2024-01-01T00:00:00Z', '2024-01-07T23:59:59Z'),
})
Page view counts per hour across a week. Use day or month for longer windows.