Feature: Dynamic Metrics

Turn Raw Data into Actionable KPIs—Updated in Real Time

Calculate and display key metrics that automatically respond to filters, selections, and map interactions. Always current, always relevant.

Problem

Your stakeholders need KPIs—total sales, ride counts, error rates—but building dashboards that combine metrics with geographic context is a custom development project. When data lives in Snowflake and maps live somewhere else, keeping numbers in sync with what's on screen becomes a constant headache.

Solution

Honeycomb Maps calculates metrics on-the-fly by aggregating columns directly from your dataset. Apply a filter, draw a polygon, or adjust the timeline—your metrics update instantly to reflect exactly what's visible on the map. No custom code, no sync issues, no stale numbers.

Key Benefits

Real-time calculations

Metrics are computed on-the-fly, taking into account active dimension filters, polygon selections, and timeline settings. What you see on the map is what you measure.

Showcase important KPIs

Display total sales, count of deliveries, number of errors, average ride duration—any aggregation that matters to your business, right on the map.

Flexible formatting

Format metrics as currency, percentages, numbers with precision, or custom formats. Make your numbers readable and meaningful for any audience.

Always up-to-date

Because fresh data is pulled from Snowflake when maps load, your metrics reflect the latest information—no manual refreshes or stale caches.

How It Works

1
Choose your aggregationSelect which column to aggregate and the calculation type (sum, count, average, min, max, etc.).
2
Apply formattingConfigure how the metric displays—currency symbols, decimal places, percentages, or custom labels.
3
Watch it respondAs users filter, select areas, or adjust the timeline, the metric automatically recalculates to match.

Example Use Case

A logistics company tracks daily delivery volumes across their service regions. With dynamic metrics, dispatchers see the total deliveries, average delivery time, and success rate for whatever area they're viewing—whether that's a single neighborhood or an entire metropolitan region. When they filter to just today's deliveries or draw a polygon around a problem area, the numbers instantly update to reflect that specific slice of data.