Glossary

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Glossary / Evaluation and implementation guide

Data Aggregation

Data aggregation is the practice of combining many records into summaries: counts, sums, averages and grouped totals.

In a revenue stack, it turns individual contacts, activities and ad impressions into consolidated datasets that dashboards can report on consistently.

A practical example

Example: marketing aggregates form submissions by week and campaign, while sales aggregates opportunities by quarter. If the two use different date boundaries, the same pipeline appears as two different numbers in each team's report.

What to evaluate before investing

  • Ask how the platform defines aggregation windows: calendar weeks, rolling periods, or time zones, and whether they are configurable.
  • Check whether aggregated metrics can be traced back to the underlying records for audit and debugging.
  • Test whether the same aggregation logic can run against CRM, MAP and ad data without per-source manual adjustments.

Limitations and tradeoffs

Aggregation discards detail by design; once records are summarized, you cannot recover individual-level answers from the aggregated dataset alone.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.