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Snapshot Metrics vs Event Analytics

Snapshot metrics capture the current state of your product, while event tracking records what users do.

Simon Herd avatar
Written by Simon Herd
Updated over 2 weeks ago

Overview

When building analytics into your product using Accoil, it’s essential to understand the difference between event tracking and snapshot metrics. These two types of data serve different purposes—and complement each other when used correctly.

In this guide, we’ll use Loom —a well-known video messaging tool— as an example to demonstrate how to think about user behavior events versus point-in-time system metrics, and how both play critical roles in product analytics, customer segmentation, and growth strategies.


What Are Snapshot Metrics?

Snapshot metrics represent the current state of key objects or entities in your product. They’re typically:

  • Calculated nightly or on a regular cadence

  • Sent to Accoil via group() calls as traits (usually at the account level)

  • Designed to give you reliable, up-to-date counts that aren’t impacted by gaps or inconsistencies in event tracking

Examples from Loom

If you were building analytics for Loom, your snapshot metrics might include:

  • Total number of videos an account has created

  • Number of shared videos across all users in an account

  • Total video views accumulated by an account

  • Number of users in the workspace, broken down by role (e.g. admins, members, viewers)

  • Number of integrations (e.g. connected to Google Workspace, Slack, Salesforce)

  • Current plan type (Free, Business, Enterprise)

These metrics help answer important questions like:

  • Who are our power users?

  • Which accounts are ready to upgrade?

  • Are large teams using key integrations?

  • Are users actively sharing content externally?

🛠️ Best practice: Compute these snapshot metrics nightly and send them as traits in your group() calls. This ensures that segmentation in Accoil is based on reliable and current data.


What Is Event Tracking?

Event tracking captures what users do inside your product. These are emitted in real-time and typically sent using track() calls.

Examples from Loom

For Loom, common event tracking might include:

  • video_created — when a user records a new video

  • video_shared — when a video is shared externally

  • video_viewed — when someone watches a video

  • video_deleted — when a video is removed

  • user_invited — when an admin invites someone to the team

  • integration_added — when Loom is connected to another platform

These events help you understand:

  • How users are engaging with your product

  • Which features are being adopted

  • What behaviors lead to upgrades or retention

🧠 Tip: Event data is great for mapping journeys and identifying usage patterns, but it should not be used to calculate long-term or aggregate metrics like “total number of videos.” If an event is dropped or missed, your counts become inaccurate.


When to Use Snapshot Metrics vs Event Tracking

Again using Loom as an example.

Use Case

Snapshot Metric

Event Tracking

Current number of videos in an account

✅ Yes

🚫 No (event loss risk)

How many admins are in the workspace

✅ Yes

🚫 No

Who recorded a video today

🚫 No

✅ Yes

How often users share videos

🚫 No

✅ Yes

Total views on all videos per account

✅ Yes

🚫 No

Which features are most commonly used

🚫 No

✅ Yes


Segmenting Effectively in Accoil

To power segmentation and targeting in Accoil:

  • Use snapshot metrics to define account health, tier usage, or upgrade eligibility.

    • E.g., Accounts with 500+ videos on the Free plan → target for Sales outreach

  • Use event tracking to build behavioral cohorts and funnel reports.

    • E.g., Users who recorded and shared a video in their first 3 days

You can combine both in Accoil Recipes for rich segmentation logic. For instance:

Example Recipe:

  • Filter: Total videos > 300 (snapshot trait)

  • Filter: Used screen share in last 7 days (event)

  • Segment: “Power users actively using advanced features”


Key Recommendations

  • Don’t try to infer counts from events. Snapshot metrics should be the source of truth for totals.

  • Send snapshot data via group() traits nightly or periodically.

  • Track user actions via track() calls to understand feature engagement and user behavior.

  • Use Accoil Plays to combine both data types for effective segmentation and targeting.


Summary

In analytics, knowing what users did is not the same as knowing what exists. Event tracking helps you understand how users engage, but snapshot metrics show you what they’ve built and how much they’ve used.

By combining the two in Accoil, you get a complete view of product engagement, enabling smarter decisions across Sales, Customer Success, Product, and Marketing.

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