Boost Analysis in Unified Performance Reporting

Updated 

5 days ago

Overview

Boost Analytics in Unified Performance Analytics (UPA) helps you measure the impact of boosting social posts with confidence. It aligns posts by their boost start date and organizes performance into three clear phases: Pre-Boost, In-Boost, and Post-Boost.

This approach consolidates organic, paid, and total performance metrics into a single, consistent framework. As a result, you can easily measure uplift, identify trends, and evaluate ROI across posts and campaigns - without relying on manual spreadsheets or guesswork.

In this article, you’ll learn:

  • How Boost Analytics in UPA helps you analyze boosted posts

  • Key Dimensions used in Boost Analytics

  • How Boost Analytics works

  • How to plot and visualize Boost Analytics in Ads Reporting dashboards

Why Boost Analytics?

Advertisers boost thousands of posts every month, but comparing performance before and after boosting requires pulling data from multiple native tools, exports, and spreadsheets.

Boost Analytics changes that, the platform aligns posts by their Boost Trend Day, making it easy to compare performance trajectories across posts through -

  • Clear visuals that highlight exactly when uplift occurs.

  • Automated data synchronization, edge cases, and calculation logic.

Boost Analytics is more than a reporting upgrade. It gives you clarity and confidence in every paid media conversation and enables clear justification of the ROI of boosting.

Key Dimensions in Boost Analytics

A Boost Episode represents a continuous period during which a post is actively boosted through one or more ad entities, with no gaps in ad delivery.

If multiple ad entities (across one or more ad accounts) boost the same post during overlapping periods, they belong to the same Boost Episode. A new Boost Episode begins only when all ad entities from the previous episode end and a new boost starts later.

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Boost Trend Day is a normalized timeline dimension that aligns all posts based on the day their paid boost begins.

  • Day 0: Ad start date of the first ad entity (the source of truth for boost start)

  • Day < 0: Days before the boost starts (Pre-Boost period)

  • Day 0 to Day N: Days during the boost (In-Boost period)

  • Day > N: Days after the boost ends (Post-Boost period)

Boost Trend Day is defined at the Boost Episode level and allows you to compare posts boosted on different calendar dates.

Example: If a post was boosted from November 1 to November 5:

  • October 31 = Day -1

  • November 1 = Day 0

  • November 2 = Day 1

  • November 6 = Day 5 (Post-Boost)

Where:

  • Day 0 marks the first ad impression

  • Days < 0 show organic-only performance

  • Days 0 to N show organic + paid performance

  • Days > N show organic-only performance after boosting ends

The Boost State dimension defines the lifecycle phase of a post within a Boost Episode. It enables clear segmentation across Pre-Boost, In-Boost, and Post-Boost periods.

Possible values include:

  • PRE: Before boosting starts

  • IN: During the boost

  • POST: After the boost ends

The system derives this value for each activity date based on the ad delivery window. Boost State powers segmentation, uplift calculations, and visual styling across dashboards.

Boost Duration shows the total number of days a post remains actively boosted during a Boost Episode.

The system calculates it automatically using ad delivery data:

  • Boost Duration = Ad end date of the last ad entity − Ad start date of the first ad entity

You cannot edit this value manually.

How Does Boost Analytics Work?

Boost Analytics follows a structured Boost Episode Lifecycle (refer to image below) that tracks a post from publish to post-boost analysis. The system aligns data automatically so you can clearly understand performance before, during, and after boosting.

  1. Post Is Published: A post is published organically on the social platform. At this stage, the post only generates organic activity and has not entered Boost Analytics.

  2. Ad Entity Becomes Active: When an ad entity associated with the post starts delivering impressions:

    • The system detects the ad start date which is marked as Boost Trend Day (Day 0).

    • A Boost episode is created to track the continuos boost period

    This step establishes the single source of truth for when boosting actually begins.

  3. Boost Episode Ongoing (In-Boost Period): While the ad entity remains active:

    • The system classifies all activity as In-Boost (Day 0 to Day N).

    • It synchronizes and calculates Paid, Organic, and Total metrics by activity date.

    • Each day is mapped to a Boost Trend Day so performance aligns across posts, regardless of calendar date.

  4. Ad Entity Ends: When all ad entities associated with the post stop delivering:

    • The system marks the Boost End Date (Day N).

    • The Boost Episode concludes.

    • Boost Duration is finalized based on actual ad delivery data.

  5. Post-Boost Period Begins: After boosting ends:

    • The system continues tracking organic-only performance.

    • Activity is classified as Post-Boost (Day > N).

    • This makes it easy to assess sustained impact after paid promotion stops.

  6. Dashboard Rendering and Visualization: Finally, UPA renders dashboards using the aligned Boost data:

    • Dashboards apply Boost Trend Day to all metrics.

    • Visualizations clearly show Pre-Boost, In-Boost, and Post-Boost performance.

Plot and Visualize Boost Data in Ads Reporting Dashboards

Follow these steps to visualize Boost Analytics in Ads Reporting dashboards:

  1. Create a widget in your reporting dashboard and select Unified Performance Analytics as the Data Source.

  2. Choose the visualization type for your widget.

  3. Select Boost Trend Day as a dimension to view aligned post performance across calendar dates.

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  4. Scroll to the Define Advanced Options section.

  5. Apply the Boost Episode Number filter and select the required Episode.

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  6. Add the required Total, Paid, and Organic metrics to analyze pre-boost and post-boost performance.

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  7. Apply additional filters, such as Post Status ID or Campaign custom fields, if needed.

  8. Click Add to Dashboard to save and publish the widget.

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