# 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: | Card | What It Shows | | ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **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: | Column | Description | | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Visitors** | The number of unique visitors assigned to this variation | | **Sessions** | Total browsing sessions for this variation | | **Revenue** | Total revenue from all orders, excluding taxes. For most experiment types, shipping fees are excluded. For **shipping experiments**, shipping fees are included in revenue since the shipping rate is what's being tested. | | **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). For shipping experiments, this includes shipping fees. | | **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. > **Shipping experiments note:** Revenue, Rev./Visitor, Rev./Session, and AOV all include shipping fees for shipping experiments. This is because the shipping rate is the variable being tested, so it must be included in revenue calculations to accurately measure the impact. For all other experiment types, shipping fees are excluded from revenue. 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: | Column | Description | | -------------------- | ------------------------------------------------------------ | | **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: | Column | Description | | --------------- | ------------------------------------------------------------- | | **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: | Segment | Options | | ------------------ | --------------------------------------------------------- | | **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. | Filter Category | Available Filters | | ---------------- | ----------------------------------------------------------- | | **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: 1. **Results tab** — Check the header cards for the current statistical status and projected revenue 2. **Probability to Win chart** — See which variation is leading and by how much 3. **Performance Over Time** — Confirm the trend is consistent, not just a spike 4. **Advanced Analytics → Visitors & Traffic** — Check if the result holds across different visitor segments 5. **Advanced Analytics → Statistical Confidence** — Once your experiment is nearing or has reached significance, review the confidence metrics to validate the result