Overview
MoEngage Analytics is powered by a query engine that runs directly on your event data stored in a data warehouse. Every analysis you run, whether it's a Funnel, Behavior analysis, Retention report, RFM, or a Custom Dashboard, translates into one or more queries that read your data.
To ensure that every customer on the platform gets consistently fast, reliable analytics, we enforce a Fair Usage Policy (FUP) on query data scans. This policy is based on your Monthly Tracked Users (MTUs) and ensures that the shared infrastructure remains healthy for everyone.
This article explains how MoEngage’s scan-based model works, what happens when you approach your FUP limit, and what you can do to keep your queries fast and well within limits.
How MoEngage Analytics Queries Work
MoEngage charges based on the volume of data scanned per query, not the number of queries you run. This means:
- A broad query that touches many events and attributes scans more data.
- A narrow, well-scoped query scans significantly less data and returns results faster.
- The structure and format of your underlying data have a direct impact on how much is scanned.
MoEngage manages all infrastructure and the cost of running queries on your behalf. However, each workspace has a monthly scan allowance based on your MTUs. Queries that consistently scan large volumes of data can exhaust this allowance earlier in the month, which may affect your ability to run additional analyses.
Fair Usage Policy (FUP) on Analytics Queries
| info |
Note MoEngage Analytics’ data-scan FUP limits are generous for all-around usage. 99.9% of MoEngage customers never reach them. |
To ensure fair access to analytics resources for all MoEngage customers, a monthly data scan limit applies to each workspace. This limit is tied to your MTU count.
| info |
Note Your monthly query scan allowance is calculated based on your MTUs and your plan. To check your current usage or request an increase, contact your Customer Success Manager (CSM). |
When your workspace approaches or exceeds the monthly scan limit:
- A warning notification appears on the Analytics dashboard.
- Queries might be throttled or restricted until the next billing cycle.
- You can contact your CSM to increase your limit based on your usage needs.
Query Optimization Tips
The following best practices help you get faster query results and make the most efficient use of your scan allowance. Implementing these tips benefits every analysis you run — Funnels, Behavior, Retention, RFM, and Custom Dashboards.
1. Narrow Your Date Range
Date range is the single most impactful parameter in any query. The wider the range, the more data MoEngage has to scan.
- Use the shortest date range that answers your question.
- Avoid defaulting to 12-month windows unless you specifically need them.
- For recurring dashboards, use rolling windows (Last 7 days, Last 30 days) instead of fixed long ranges.
| lightbulb |
Tip A 7-day funnel analysis scans roughly four times less data than a 30-day analysis of the same events. Use shorter windows for exploratory work, and only expand when validating a trend. |
2. Filter by Specific Events to Avoid Broad Event Selection
Each additional event you add to an analysis increases the volume of data scanned. Be intentional about which events you include.
- Select only the events that are directly relevant to your analysis.
- Avoid adding events "just in case" — you can always run a follow-up query.
- In Funnel and Behavior analyses, each step adds to the total scan volume.
3. Apply User Filters (Segments) Upfront
Filtering by a segment or user attribute early in your query reduces the user population Athena needs to evaluate, which reduces the data scanned.
- Apply segment filters at the start of your analysis rather than relying on post-query filtering.
- Use specific user attributes (for example, country, platform, or user type) to scope your analysis to a relevant subset.
4. Limit the Number of Event Attributes You Analyze
When you break down an analysis by event attributes (for example, splitting a purchase event by product category, payment method, and region simultaneously), each additional dimension increases the data scanned.
- Use one or two breakdowns per analysis rather than stacking multiple unnecessary attribute splits.
- Run separate analyses for separate questions, rather than one very wide analysis that tries to answer everything at once.
5. Avoid Stacking Multiple Custom Dashboard Widgets Simultaneously
Custom Dashboards allow you to visualize multiple metrics on one screen. Each widget executes its own query. If your dashboard has many widgets with broad date ranges and event coverage, opening it triggers a large number of simultaneous scans.
- Group related widgets into focused dashboards rather than one all-encompassing dashboard.
- Use narrower date ranges for dashboard widgets — they refresh faster and scan less.
- Remove widgets you no longer actively use.
Quick Reference: Optimization Checklist
| Optimization | What to Do | Impact |
|---|---|---|
| Narrow date range | Use the shortest range that answers your question | High |
| Fewer events per analysis | Select only relevant events; avoid adding extra steps | High |
| Apply segment filters early | Scope to a specific user cohort upfront | High |
| Limit attribute breakdowns | Use 1–2 attribute splits per analysis | Medium |
| Use saved segments | Avoid rebuilding the same audience filter repeatedly | Medium |
| Optimise dashboard widgets | Fewer widgets, narrower ranges, remove unused widgets | Medium |
Need a Higher Query Limit?
If your team's analytics needs regularly exceed your current FUP allowance, you can request an increase. Contact your Customer Success Manager (CSM) to discuss your usage patterns and get your limits adjusted.
In addition to raising limits, your CSM can advise on query patterns specific to your integration and suggest workspace-level optimizations based on your event schema.