Analytics

Analytics provides visibility into your notification system. Track notification lifecycle signals, understand user engagement patterns, and optimize your workflows based on near real-time data. Navigate to the Analytics tab to get started.

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Available data points

Analytics provides visibility into notification performance across multiple dimensions. You can analyze data by:

• Channel performance - Identify underperforming channels by comparing delivery and engagement metrics or look for any dips in delivery, open or click rates over time.
• Notification volume - Detect over-messaging patterns by tracking notifications per user across channels and categories.
• Unsubscription trends - Reduce churn by understanding which channels and categories drive opt-outs.
• Workflow Level Breakdown - Optimize notifications by comparing engagement across workflows, templates, channels and vendors.
• Errors - Proactively fix issues by surfacing API, workflow, and delivery errors before users notice.

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Performance Overview

Performance Overview provides a high-level view of your notifications performance.

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Channel performance

Compare delivery and engagement across channels to see where users are most responsive. You see overall delivery, open and click rates by channel and their timeseries trend. You can drilldown graph by template-in addition to the global filters (workflow, tenant, date range). The chart above shows these metrics by channel. You might see a warning icon next to a channel when the tracking is not properly configured for the channel. Click on the icon to see the details and fix the tracking issue. Metrics tracked across channels: Not all channels track all metrics. Here’s what’s tracked at the channel level: Interpreting your metrics: For export options, see Exporting data.

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Notification volume

Monitor average notifications sent per user per day. Over-messaging is one of the reasons users unsubscribe. Use this view to spot over-messaging before opt-outs spike. The following breakdown explains what you’re looking at. What you’ll see:

• Average notifications per user - Average number of notifications each user receives per day. You can notification bucket vs %of users in each bucket. Anything in the red zone is considered over-messaging and you should try to keep the notification volume in the blue zone.
• Volume trends over time - How notification volume changes over time
• Volume by category - Which preference categories contribute most to total volume
• Volume by channel - Which channels are sending the most notifications

Reducing volume:

• Use throttling to limit how often workflows trigger per user
• Use batch to consolidate multiple updates into single notifications
• Use smart channel routing to stop delivery on further channels when a user engages with the notification on any one channel.
• If you’re sending broadcast or promotional notifications, reduce the frequency of sending them.
• Use preference categories to let users manage preferences per category-prevents complete channel opt-outs and highlights where to reduce volume.

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Unsubscription trends

Monitor opt-outs by channel, category, and time period to understand what is driving your users to opt out. What you’ll see:

• Total opt-outs - Number and percentage of users who unsubscribed
• Day-wise trends - Opt-out patterns over time (use available time breakdowns to spot spikes)
• Category breakdown - Which categories drive the most opt-outs
• Channel breakdown - Which channels contribute most to opt-outs

Investigate the opt-outs:

1. Check notification volume first - Over-messaging is the most common cause. Check if volume trends correlate with opt-out spikes.
2. Filter by category or channel - Identify which categories or channels have the highest opt-out rates and then optimize the volume or content of the notifications.
3. Analyze day-wise trends - Check if opt-outs spiked after a specific campaign or change.

Use filters (category/channel/workflow) to isolate drivers. Export raw user data for deeper analysis.

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Workflow Level Breakdown

The Workflow Level Breakdown helps you compare notification performance at the most actionable level - individual workflows, templates, channels, and vendors. Each row shows notification performance indicators for a specific workflow, template, channel, vendor and category. Metrics shown:
Filters:
Other than the global filters (workflow, tenant, date range), you can also filter by all table columns locally - channel, vendor, category and template.
Sorting:
Click any column header to sort. Sort by lowest seen/click rate to find underperformers, highest to find top performers, or trigger count for high-volume workflows.
What to look for:

1. Identify top performers
   • Sort by % Seen / Delivered or % Clicked / Delivered (descending)
   • Look for patterns in channel, timing, or template design
   • Reuse successful patterns across similar workflows
2. Identify underperformers
   • Sort by % Seen / Delivered or % Clicked / Delivered (ascending)
   • Compare against similar workflows in the same category
   • Check whether the issue is content, channel choice, timing or frequency of sending
3. Identify issues with delivery
   • Low % Delivered indicates delivery or vendor issues
   • Click through to the Errors tab to investigate notification delivery failures and fix them.
4. Compare channels for the same workflow
   If you are sending on multiple channels for the same workflow,
   • Compare engagement rates side by side
   • Decide whether certain channels should be deprioritized or removed
   • Consider using smart delivery to automatically choose the best channel

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Errors

The Errors tab helps you identify and resolve issues that prevent notifications from being triggered, executed, or delivered. Unlike Logs (which show every event), Errors aggregates failures so you can quickly spot issues and prioritize fixes. You’ll see errors grouped into three sections:

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API Request Failures

Errors where API or SDK requests were not successfully processed, and no workflow execution was started. If this error table is empty and you’re actively sending requests, your integration is working as expected. What you’ll see:

• Total occurrences - How often the error occurred in the selected time range
• Last seen - When the error last happened (to see if it’s ongoing)
• Context - API type or request context involved
• Error description - The exact error message reported

Common causes:

• Invalid or expired API key
• Authentication failure
• Missing required fields (for example user_id)
• Invalid request payload format

Filters: API type, error description. Sortable.

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Workflow / Broadcast Execution Failures

Errors that occur after a request is accepted, but while executing a workflow or broadcast. These usually indicate issues with workflow configuration or template data. Each row represents a workflow (or broadcast) and the node where execution failed. What you’ll see:

• Total occurrences - How often the error occurred in the selected time range
• Last seen - When the error last happened (to see if it’s ongoing)
• Workflow - The workflow where the failure occurred
• Node Name - The specific node in the workflow where execution failed
• Error description - The exact error message reported

Most common errors:

• Template rendering failures due to missing variables
• Dynamic fields in workflow couldn’t be evaluated due to missing data or invalid data types

If the same error appears multiple times with a high occurrence count, it indicates a systemic issue affecting many notifications. Filters: Workflow and Tenant (Global filter), Node name, error description. Sortable.

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Notification Delivery Failures

Errors reported by vendors after SuprSend successfully sent the request, but the vendor could not deliver the notification. What you’ll see:

• Total occurrences - How often the error occurred in the selected time range
• Last seen - When the error last happened (to see if it’s ongoing)
• Template - The template slug for the failed notification
• Channel - The channel where delivery failed (email, SMS, push, etc.)
• Vendor - The vendor that reported the delivery failure
• Error description - The exact error message reported

Common delivery errors:

• User channel identities are invalid, blocked or missing
• Vendor-side rate limiting
• Credit limit exceeded
• Temporary vendor outages

Some delivery failures (like invalid addresses) require fixing user data. Others (like temporary outages) may resolve automatically. Filters: Workflow and Tenant (Global filter), Template slug, channel, vendor, error description. Sortable. If errors persist or you’re unsure how to resolve a specific failure, see the Error Guide or contact support.

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Exporting data

Export CSVs for analysis outside SuprSend (Sheets/Excel/Data warehouse). How to export:

1. Navigate to the data point you want to export
2. Click the 📥 icon in the top right of that section
3. Select your date range (relative or absolute)
4. Choose your export type (aggregate or raw user data)
5. Apply any filters you want to include
6. Download the CSV file(s)

Export types: Aggregate user data - Summary statistics grouped by date and time (matches what you see in charts). Includes: Date/time buckets, total counts, percentage rates, grouped by workflow/channel/category/vendor/template. Use cases: Custom dashboards, trend analysis, high-level reporting. Raw user data - Individual user-level records with timestamps for available events. Includes: User records, timestamps for each event, workflow/template/channel/vendor/category, user properties and metadata. Use cases: Check each log, detailed user behavior analysis, and drilldown into trends to identify patterns.

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Navigating Analytics

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Refresh

Analytics data updates automatically every 5 minutes. You can manually refresh the data by clicking the refresh button to get the latest metrics.

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Filters

You have global filters to drill down analytics data by workflow, tenant, and date range. Other than this, local filters are available for against respective data point to filter by channel, vendor, category, node, error description and template.

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Date Range and Retention

Analytics default to “Last 7 days” when first opened. Choose from relative ranges (Last 1 day, 7 days, 30 days, and additional presets) or select absolute date ranges with timezone-aware selection. Data retention period is based on your pricing plan. For extended retention options, contact our sales team.

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Frequently Asked Questions

Need help? Contact our support team.