Note
The Segments Dashboard is the most granular analytics tool available, allowing you to create custom segments of subscriptions to track their performance over time. Use it to understand how Skio features and subscription behaviors impact revenue, retention, and churn metrics.
Before you start
Check your dashboard version: This guide covers the latest version of the Segments Dashboard.
Permissions required: You need admin access or access to analytics to view the Segments Dashboard. Learn more about permissions.
Data refresh frequency: The dashboards update every four hours. Data for the current day may lag slightly compared to real-time Shopify reporting.
What you should know: By default, the dashboard displays metrics for all subscriptions in your selected date range. You can apply custom segments to filter the entire dashboard to only subscriptions matching your segment conditions. Dynamic segments sync nightly at 12am EST to automatically add new subscriptions that match and remove subscriptions that no longer apply.
Need help creating segments? See the Custom segments best practice guide.
What is the Segments Dashboard?
The Segments Dashboard provides granular insights into custom groups of subscriptions. It answers critical questions like:
How does Surprise & Delight impact subscription value and retention?
How do Cancel Flow saves impact subscription value and retention post-save?
What actions are taken by subscriptions and how do they impact KPIs and retention?
What are the KPIs of subscriptions created in a specific time period?
What's the Shipping Interval distribution for my subscriptions?
How many products were added to, removed from, or are currently active in subscriptions?
The dashboard includes an audit log table to track all actions taken on subscriptions and tie them to revenue metrics, plus retention analysis and product breakdowns.
Filters and KPI cards
At the top of the dashboard, you'll find controls for customizing your view:
Date Range: Used for tracking all actions and orders processed in the date range for subscriptions that were active at some point during that period
Segment Filter: Apply custom created segments to filter the dashboard. By default, displays data for all subscriptions
Create Segment: Button to create a new custom segment with specific conditions
Subscriptions: Count of all subscriptions that were active at some point in the date range
Cancelled Sub Count: Count of subscriptions that were active at one point but now have a cancelled status
Activations: Count of subscriptions in the segment created in the date range (all others were created prior and were active during the period)
Orders Processed: Count of all orders processed by subscriptions in the date range
Revenue Generated: Sum of the order total of all orders processed in the date range
% Cancelled: Percentage of subscriptions in the segment that were cancelled as of the last day of the date range
AOV: Average order value of all orders processed in the date range
ARG (Average Revenue Generated): Total average revenue generated per subscription in the date range
AOC (Average Order Count): Average number of orders processed per subscription in the date range
Audit Log Table
Tracks all actions taken on subscriptions and ties them directly to revenue metrics to assess their impact. For each action, you'll see:
Action: The name of the action performed on the subscription (displays all actions tracked in Skio's audit logs)
# subscriptions: Count of subscriptions that had this action performed in the date range
Action count: Total count of actions performed in the date range on subscriptions
AOV w/ Action: AOV of subscriptions that had the action performed
AOV w/o Action: AOV of subscriptions that did NOT have the action performed (control group)
LTV w/ Action: LTV (average revenue generated) of subscriptions with the action
LTV w/o Action: LTV of subscriptions without the action
AOC w/ Action: AOC of subscriptions with the action
AOC w/o Action: AOC of subscriptions without the action
Note
Values in this table are lifetime values as of today and do not adjust based on the date filter applied to the rest of the dashboard.
Common actions to track:
1-time add-ons
Quick Actions
Skips
Swaps
Surprise and Delight gift applied
Automations/Journeys
Bulk Operations
Reactivations
Pause
Update Payment Method
Discount Code applied
Logins
Products Breakdown Table
Provides a product breakdown of all active products in the segment.
Product: The product title; may appear as multiple rows if there are multiple variants or SKUs
Subscriptions: Number of active subscription lines associated with the product
Subscribers: Number of unique customers subscribed to the product
Quantity: Total quantity of the product currently active in subscriptions (as of the end of the date range)
Activated: Count of times the product was added to a subscription in the selected date range (includes new subscriptions or recurring product adds)
Cancelled: Count of times the product was removed from a subscription in the selected date range (includes cancelled subscriptions or removed products)
Note
This tab focuses on subscription activity only. For financial metrics like revenue and AOV, use the KPI tab (7) instead.
Shipping Interval Breakdown
A breakdown showing the distribution of subscriptions by their shipping frequency (e.g., 30 days vs 60 days). This table does not adjust based on the date filter but will adjust for product filters and segment filters applied.
Monthly Breakdown
Provides retention rate by month per subscription monthly cohort (the month the subscription was created) and retention by order count.
View Toggle: This toggle lets you switch between Retention, Revenue, LTV, AOC, Orders, and Retention (Orders) views. By default, you’re viewing Retention by Month, but clicking another tab allows you to see different KPIs for the same cohorts.
Cohort Date Selector: Indicates the month in which the subscriptions started. The retention data in each row tracks these subscriptions over time, month by month.
How to interpret the Monthly Breakdown chart
The example in (3) highlights a specific data point (e.g., "40%") in a cohort row. These highlights help draw attention to drops or patterns. In the example shown, July 2025 retention dropped sharply to 40% and remained there, suggesting churn issues within the first month.