Reports Overview
Once your experiment is live and collecting data, Elevate gives you a full reporting suite to understand how each variation is performing. This page walks you through the different reports available and what you'll find in each one.
Experiment Report Structure
When you open a running or completed experiment, you'll see a top navigation with the following tabs:
Overview — Your experiment setup and configuration
Results — The main performance report
Raw Data — Individual order and event-level records
Advanced Analytics — Deeper breakdowns across multiple dimensions
Each of these is covered below.
Overview
The Overview tab shows your experiment configuration — the variations you set up, traffic allocation, and the pages or products being tested. Think of this as a reference for what you're testing. No performance data lives here; it's purely about the setup.
Results
This is the primary report you'll check while your experiment is running. It's designed to answer the big question: is this change working?
Header Cards
At the top of the Results page, you'll see a row of summary cards:
Total Visitors
The number of unique visitors across all variations
Experiment Goal
The metric your experiment is optimizing for (e.g., Conversion Rate, Revenue Per Visitor)
Statistical Significance
The current status of your experiment's results — see Statistical Significance for details
Experiment Duration
How long the experiment has been running
Projected Revenue
An estimate of the revenue impact over the next 30 days, based on current performance and visitor velocity. This card only appears when there's a measurable difference between variations.
Results Table
Below the header cards, you'll find a table comparing each variation side by side. The columns include:
Visitors
The number of unique visitors assigned to this variation
Sessions
Total browsing sessions for this variation
Revenue
Total revenue from all orders, excluding shipping fees and taxes
Product Revenue
Revenue from the specific product being tested (visible for product-level experiments)
Rev./Visitor
Average revenue per unique visitor (Total Revenue ÷ Unique Visitors)
Rev./Session
Average revenue per browsing session (Total Revenue ÷ Total Sessions)
Conv. Rate
Percentage of unique visitors who completed a purchase (Conversions ÷ Unique Visitors × 100)
Session Conv. Rate
Percentage of sessions that resulted in a conversion (Conversions ÷ Sessions × 100)
Conv.
Total number of unique visitors who completed a purchase in this variation
Orders
Total number of orders placed by both new and returning visitors
Profit
Net earnings after deducting product costs (requires cost data)
Profit/Visitor
Average profit per unique visitor (requires cost data)
Ship. Rev.
Total revenue collected from shipping fees across all orders
AOV
Average Order Value — the average amount spent per order (Total Revenue ÷ Total Orders)
Some columns are conditional. Profit columns only appear if you've enabled product costs. Product Revenue is only shown for product-level experiments. Session-based columns require sufficient session tracking data.
The variation that's currently leading is highlighted, and each metric includes a lift indicator showing the percentage difference compared to the control.
Charts
Below the table, several charts give you a visual understanding of how the experiment is performing:
Conversion Rates — A bar chart comparing conversion funnel stages (Add to Cart → Checkout → Purchase) across variations
Probability to Win — A chart showing each variation's probability of being the best performer, based on the Bayesian model. This is the primary statistical output of your experiment.
Session Duration — Average time visitors spend on the page per variation
Where Users Go Next — Shows where visitors navigate after viewing your test page, including bounce rate. Useful for understanding whether a variation keeps people engaged or pushes them away.
Performance Over Time — A time-series chart tracking your key metrics day by day, so you can see trends and patterns as the experiment progresses
Raw Data
The Raw Data tab gives you access to individual records attributed to your experiment — useful for auditing, debugging, or investigating specific orders and events.
Orders Table
A searchable, sortable table of every order attributed to your experiment. Each row represents a single order and includes:
Order ID
Links directly to the order in your Shopify admin
Created Date
When the order was placed
Order Number
The Shopify order number
Total
Order total (revenue)
Quantity
Number of items in the order
Total Discounts
Any discount amount applied
Shipping
Shipping cost for the order
Profit
Net profit after product costs (if cost data is enabled)
Financial Status
Payment status of the order
Visitor ID
The unique visitor who placed the order
Source Name
Where the order originated (e.g., web, draft order)
Total Products
Number of distinct products in the order
Products
Links to each product in the order within your Shopify admin
Subscription
Whether the order contains a subscription item
Orders flagged as outliers are labeled. You can also remove individual orders from the experiment if they were incorrectly attributed.
You can export the full orders dataset as a CSV for further analysis.
Events Table
A log of individual visitor events tracked by the experiment. You can filter by event type and device:
Event types: Page views, Add to cart, Checkout create
Device types: Desktop, Tablet, Mobile
Each event record includes:
Time
When the event occurred
Event Type
The type of action (page view, add to cart, checkout started)
Variation
Which variation the visitor was assigned to
Referrer
The URL that referred the visitor
Device Type
The visitor's device
Country
Visitor's country
City
Visitor's city
Visitor ID
The unique visitor identifier (hidden by default)
You can export the full events dataset as a CSV.
Experiment History
A timeline of all actions taken on the experiment — when it was created, launched, paused, resumed, updated, or marked as complete. Each entry includes a timestamp and, where applicable, details of what was changed. This is useful for understanding the context of your results (e.g., if a variation was edited mid-experiment).
Advanced Analytics
The Advanced Analytics tab provides deeper, segmented analysis of your experiment data. It's organized into sub-tabs, each focused on a different aspect of performance.
Summary
A high-level view of your experiment's key metrics plotted over time. Each metric is shown as a time-series chart comparing all variations:
Conversion Rate
Add-to-Cart Rate
Avg Session Duration
Revenue Per Visitor
Average Order Value
Profit Per Visitor (requires cost data)
This tab is useful for spotting trends, seeing when a variation started pulling ahead, or identifying if performance has been consistent over time.
Visitors & Traffic
Focused on understanding who your visitors are and how they behave:
Conversion Rate and Avg Session Duration by variation
Bounce Rate — The percentage of visitors who left after viewing only one page
New vs. Returning Visitors — Revenue Per Visitor broken down by visitor type, so you can see if your variation performs differently for new visitors compared to returning ones
Top Traffic Sources — Performance breakdown by the sources sending traffic to your experiment
Orders & Checkout
A detailed look at the ordering and checkout process:
Orders Per Visitor — How many orders each visitor generates on average
Checkout Completion Rate — The percentage of visitors who started checkout and completed a purchase
Average Order Value — Revenue per completed order
Items Per Order — Average number of items in each order
Checkout Duration — How long visitors spend in the checkout flow
Discount Usage — What percentage of orders used a discount code
Cart Abandonment Rate — The percentage of checkout starts that didn't result in a purchase
Products Breakdown
For experiments involving specific products, this tab shows per-product performance data — revenue, conversions, and traffic for each product in the test. This is especially useful for price experiments and product group tests where you need to see which products are driving the overall result.
Subscriptions
For stores with subscription products, this tab breaks down subscription-specific metrics:
Subscription Orders Per Visitor
Subscription Revenue Per Visitor
Subscription Profit Per Visitor (requires cost data)
Subscription as a % of Total Orders
Avg Subscription Units Per Order
This helps you understand whether your variation is impacting subscription behavior specifically, beyond just one-time purchases.
Statistical Confidence
A detailed view of the statistical analysis behind your experiment. This includes:
Metric Summary Cards — Probability to win for each goal metric (Conversion Rate, Revenue Per Visitor, Add to Cart Rate, etc.), not just your primary goal
Advanced Details Table — A breakdown of statistical power, minimum detectable effect, credible intervals, expected loss/gain, and other technical metrics
For a full explanation of how statistical significance works, see Statistical Significance.
Segmentation
Most tabs in Advanced Analytics support segmentation, allowing you to filter and break down results by:
Device
Mobile, Desktop
Visitor Type
New Visitors, Returning Visitors
Traffic Source
Paid, Organic
Source Channel
Your top traffic sources (e.g., Google, Facebook, Direct)
Segmentation is useful for discovering that a variation might work well for one audience but not another — for example, a layout change that converts better on mobile but worse on desktop.
Filtering
Across all reports, you can apply filters to narrow down the data you're looking at. Filters apply globally to whichever tab you're viewing.
Date Range
Select a custom date window to focus on a specific period within your experiment. Useful for comparing performance week over week or isolating results around a specific event (e.g., a sale or product launch).
Product Filter
Focus your report on specific products within the experiment. This is especially useful for Advanced Price Experiments where multiple products are being tested — you can drill into individual product performance rather than looking at the aggregate.
Advanced Filters
Click the filter icon to open the advanced filtering panel. Each filter supports match criteria — you can set it to is, is not, or contains depending on the filter type.
Source
Traffic source, Referrer URL
Location
Country, Region, City
Page
Page URL, Entry page, Entry path
Device
Browser, Operating system, Screen size
UTM Tags
UTM medium, UTM source, UTM campaign, UTM content, UTM term
Currency
Order currency
Visitor Type
New visitors, Returning visitors
These filters let you answer very specific questions — for example, "How does this variation perform for mobile visitors from Instagram in the US?" or "What's the conversion rate for visitors who entered through my homepage?"
Additional Options
Exclude Discounts — Toggle to exclude orders that used a discount code, so you can see performance without promotional influence
Show All Products — For Advanced Price Experiments, toggle to include products outside the test scope in your results
Enable Product Cost — Link to set up cost data for profit-based metrics (Profit Per Visitor). Once enabled, profit columns appear in your results.
What to Look At First
If you're not sure where to start, here's a practical order:
Results tab — Check the header cards for the current statistical status and projected revenue
Probability to Win chart — See which variation is leading and by how much
Performance Over Time — Confirm the trend is consistent, not just a spike
Advanced Analytics → Visitors & Traffic — Check if the result holds across different visitor segments
Advanced Analytics → Statistical Confidence — Once your experiment is nearing or has reached significance, review the confidence metrics to validate the result
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