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Why Non-Aggregatable Metrics Cannot be Summed
Why Non-Aggregatable Metrics Cannot be Summed

Walkthrough example of why non-aggregatable metrics cannot be summed. Also includes links to other related knowledge base articles.

Written by Kelsey Maynard
Updated over a week ago

# Definition

Non-aggregatable ("non-agg") metrics are those that are unique to their segmentation. In other words, if non-aggregatable metrics are summed, the sum will be inaccurate.

# Overview

Please note that the following examples use User Level data to help understand why non aggregatable metrics cannot be summed. You will not find this type of data within Funnel!

The following is a typical advertising account structure. Consider this example - each ad below, from each campaign, reached Kelsey.

# Reach

Reach refers to the total number of people who have seen the ad or content. If 100 total people have seen the ad, that means the ad’s reach is 100.

Even though all 9 ads have reached Kelsey, reach should reflect 1. At the campaign level, reach should be reflected as 1, not 3. Aggregating reach will lead to inaccurate totals.

 Level Accurate Reach Account 1 Campaign 1 Ad 1

## Reach as an Aggregatable Metric

If reach is aggregatable, the summed totals reflected would be inflated and inaccurate.

Because of aggregation, reach is reflected as 9 when it should be 1. Since reach is currently an aggregatable metric, you are able to remove dimensions from the Data Explorer view when looking at reach. This will also lead to inaccurate results.

## Reach as an Non-Aggregatable Metric

Having reach as a non aggregatable metric makes sure that the metric doesn't display a total count. Also, the metric will not display if all dimensions, including date, are not included in the Data Explorer view. This is to avoid inaccurate totals.

# Example

Consider the following clicks, both unique and total, for November 2022.

Non aggregatable metrics can be challenging to work with because aggregation is not possible. For fields like clicks, which are possible to aggregate, you can rely on aggregating smaller windows of data to understand larger windows.

## Total Count: Clicks

The sum of daily total clicks is equal to total monthly clicks.

## Unique Count: Clicks

The sum of daily unique clicks is not equal to unique monthly clicks. Allowing unique clicks to aggregate would lead to inaccurate totals.

According to Data Explorer, the month of November had 23 unique clicks. Taking a look at the calendar above, it's clear that the unique clicks for November should reflect 3 (Kelsey, Walter, and Nick).