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Audience Insights provide visibility into how an audience’s membership changes over time, an audience’s potential reach, how enrichment changes reach, the distribution of attributes in an audience, and how much an audience overlaps with other audiences in your account. These insights can help improve the users you’re targeting to ensure your audience meets your business goals.
You can open Audience Insights from either the Audiences landing page or Audience Builder:
At the top of Audience Insights, you can find an overview of when the insights were last updated, the sample size used to calculate the different metrics, and how much historical data is available.
Insights last update (UTC): The timestamp of the most recent analysis run. Insights refresh on a schedule rather than in real time:
Analysis results: The precision of the metrics shown.
Historical data accumulates from the last time you edited the audience definition: each change to the membership criteria in the audience definition resets the historical data. For example, if you activate an audience and leave it unchanged for 30 days, Historic data shows 30 days and the insights display a 30-day historical trend. If you edit the criteria on day 31, metrics are calculated from that point forward. Inactive audiences don’t accumulate historical data, but you can still view insights based on the current definition.
The Audience Health section allows you to examine how your audience membership changes over time: how large the audience is, how fast it’s growing or shrinking, and where it’s likely headed next.
You can refer to this section to answer questions such as:
The Audience Size chart plots your audience membership across the selected date range. Use the 3 controls above the chart to change what it displays:
Today, 7 days, 15 days, 4 weeks, 8 weeks, 12 weeks, or a custom date range.
The 3 cards above the chart summarize the audience at a glance. Each card shows a headline value plus the change compared to the previous period of the same length (for example, vs last 15 days), with an up or down arrow indicating the direction of change. Each card includes a help icon with an inline definition.

The Trend view is the default view for the Audience Health section, and shows an area chart that plots total audience size at each point across the selected window. The vertical axis is audience size and the horizontal axis is time, with a tick for each interval in the selected date range. Use the trend view to read the audience’s overall trajectory: whether it’s growing, holding steady, or declining.

The Flux view is a grouped bar chart that shows movement in and out of the audience for each interval, rather than the running total. Each interval displays paired bars, labeled Entries and Exits, representing the users added to and removed from the audience during that period. Use the flux view to spot turnover and volatility that a stable total size can hide, such as an audience whose size looks flat but is actually cycling many users in and out each week.

Turn on Show Forecast to project the audience’s expected size into the near future. mParticle draws the forecast as a continuation of the trend line, labeled Forecasted size, accompanied by a shaded 95% confidence range that widens the further out it projects. The historical portion of the line is labeled Actual.

The Overlaps section shows how much the current audience overlaps with other audiences you’ve already created. Use it to avoid targeting the same users across multiple campaigns, identify redundant audiences, and find closely related segments.

A legend at the top of the section distinguishes the parts of each comparison: This audience, Other audiences, and the Overlap between them.
Use the 2 controls above the table to choose and order the comparisons:
Each row in the table compares the current audience against another audience:
| Column | Description |
|---|---|
| Name | The name of the other audience being compared. |
| Overlap | A visual indicator of how much the audiences intersect. |
| Shared Users | The number of users who belong to both audiences. |
| Trends | The change in the overlap, with an up or down arrow. |
| Overlap (%) | The overlap expressed as a percentage in both directions: the share of this audience that’s also in the other audience, and the share of the other audience that’s also in this one. The 2 values use the legend colors. |
| Date Created | When the other audience was created. |
The Reach section helps you assess the potential reach of your campaign across different user identifiers.
Each identifier count reflects unique identifiers, not unique users. A user with both an email address and a mobile phone number contributes to the count for each identifier type.
Use the tabs above the chart to choose what to compare:
Select Today to review current reach. In Overview, a horizontal bar chart shows the current estimated count for each identifier type. Bar length represents the number of unique identifiers along the Estimate size axis.

In Enrichment Breakdown, select Today to see current reach for identifier types that Match Boost or Household Reach can enrich. Each horizontal bar represents one identifier type and has 2 segments:
Select By Percentage to show each source as a percentage of the total identifier count for that identifier type, or By Count to show absolute identifier counts. Hover over a segment to see its count and percentage.
For example, if an email bar contains 10,000 identifiers and 2,000 came from enrichment, the Boosted segment represents 20% of those email identifiers. This doesn’t mean enrichment made 20% more audience members reachable. The Email Reach and Mobile Reach cards measure the percentage of audience members with an identifier available for each channel.
mParticle ID appears in the enrichment breakdown when Household Reach is enabled. Its Boosted segment reflects household expansion only, because Match Boost doesn’t add mParticle IDs.

Select a time range other than Today to see which identifier counts are increasing or decreasing. Use a shorter range to examine a recent change, or a longer range to follow a trend.
In Overview, the chart switches to a line chart, with one line per identifier type. Hover over a data point to see its estimated count and date. Select Daily (Average) to view daily changes, or Weekly (Average) or Monthly (Average) to compare averages over longer intervals.

In Enrichment Breakdown, select an identifier above the chart to examine how its first-party and boosted counts change. For example, if email identifier counts decline, the chart shows whether the decline comes from first-party data, enrichment, or both.
With Daily selected, stacked bars show first-party and boosted reach for each period, with a line showing total reach. Dashed vertical lines mark when Match Boost was enabled or disabled.

Choose Weekly (Average) to compare weekly averages in a stacked area chart, or Monthly (Average) to group data by month.

The historical Enrichment Breakdown chart displays at most 15 data points. With Last 4 weeks and Daily selected, days are grouped to fit this limit, so not every day appears individually. With Weekly (Average), the same range shows up to 4 weekly averages.
If data is unavailable for a period, this chart shows a gap or grayed-out bar. This doesn’t indicate audience loss.
You can also compare Match Boost snapshots using the By benchmarks view.
The Benchmarking section shows your audience’s email and mobile phone reach and how many identifiers Match Boost added. Use it to compare reach before enrichment, when Match Boost was switched on or off, and today.
You can access Benchmarking below the Reach chart in the Insights tab in Audience Builder. It also appears when you review an audience in the Update Audience flow. The summary cards, benchmark chart view, and Identities table are available only for audiences where Match Boost has been enabled.
The 2 summary cards show how much of your audience you can reach through each channel:
Each card shows the current percentage and, when available, the change since Match Boost, with a help icon explaining the metric. These percentages describe identifier availability, not confirmed matches in downstream platforms.

The Identities table compares estimated counts for each identifier type before enrichment, when Match Boost was enabled or disabled, and today. Benchmarking includes only identifier types that Match Boost can enrich, such as email addresses and phone numbers.
| Column | Description |
|---|---|
| Original (date) | The identifier count at the audience’s first snapshot, before Match Boost ran. |
| Boost on (date) | The total identifier count when Match Boost was enabled, plus how much of that total was added by Match Boost. |
| Boost off (date) | The total identifier count when Match Boost was disabled, after identifiers added by Match Boost were removed. This column appears only when Match Boost has been disabled. |
| Current size (Today) | The latest total identifier count, plus how much of that total was added by Match Boost. |
Audience membership and first-party identifier counts can change between snapshots. To identify Match Boost’s contribution, use the added by Boost count rather than the difference between total counts. For example, if Original contains 6,000 email identifiers and Current size (Today) contains 10,000, including 2,000 added by Match Boost, the count attributed to Match Boost is 2,000 even though the total grew by 4,000.
The count added by Match Boost can continue to grow between the Boost on and Current size (Today) snapshots as Match Boost finds new matches.
In the Reach chart’s Enrichment Breakdown tab, select By benchmarks. Use the identifier selector to switch between the identifier types available for your audience.
Each stacked bar separates First-party identifiers from identifiers added by Match Boost at a benchmark: Original, Boost switched on, Boost switched off when applicable, and Current. The chart and Identities table use the same snapshots. The chart shows 1 identifier at a time, while the table shows all supported identifiers together.

Updating an audience’s definition clears its previous benchmarking history. The next snapshot becomes the new comparison baseline and is labeled Updated definition instead of Original.
If you enable and disable Match Boost multiple times, the benchmark chart and Identities table show a snapshot for each change. Periods when Match Boost was off show no Match Boost contribution. Match Boost data resumes after it’s enabled again.
The Composition section shows the distribution of different values of an attribute across your audience to understand your audience demographics and characteristics. Hover your cursor over each section of the pie chart to:

To view user distribution according to a different attribute, use the dropdown menu to select the attribute. The composition view only includes single-value, non-numeric, non-calculated user attributes. Calculated attributes, list-type (multi-value) attributes, and attributes whose values are numeric are not available for selection.
Additionally, the composition view does not support selecting attributes with high cardinality: attributes that have a high number of unrepeated values. This includes attributes such as:
For example, a pie chart displaying the many unique values of “First name” would not be very useful in comparison to a chart displaying a breakdown of your audience by “favorite genre”.
If you select a timeframe other than Today, the pie chart is replaced with a line chart to represent your data over time.
For the Reach and Composition metrics, you can add additional filters to understand how these metrics change over time.
For Reach, see Audience Performance. The timeframe and averaging interval controls described below apply to Composition. If no historical data is available to calculate audience metrics over time, these filters are disabled. Audience metrics over time are not available for overlaps.
Use the first dropdown above each chart to select how far back you want to view data for. Options include:
This determines the time window displayed in the chart.
If no data is available for a given time period within your selection, the line chart will display a dotted line to indicate the gap:

Data may be unavailable for one of the following reasons:
If you select a timeframe other than Today, a second dropdown appears allowing you to change the averaging interval. Options include:
This setting smooths out fluctuations and makes it easier to identify broader audience trends.
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