Who gets this? Shops on all Postscript plans have access to this feature. Learn more about Postscript Plans.
Popup analytics gives brands an aggregate overview of popup performance broken down into several criterion including impressions, engagements, and conversations.
Available data updates every 15 minutes.
With Popup Analytics, you can:
View impressions, engagements, phone, and email conversations for each popup.
Understand activity attributed to each popup by day, week, or month.
Easily digest analytics in either interactive charts or aggregated tables.
Export data for personal analysis or to use with your data warehouse.
To navigate to message analytics, select Data & Insights in the side menu of your Postscript dashboard, then select Popups.
Popup Analytics
Under Popups, the data displayed in the graph will depend on the time period and filters you've selected.
Select Opted-in Subscriber View or Submission View from the View.
Select a date range from the Date drop-down menu or set a custom date range. Then set the Date Interval drop-down menu to set how data displays (by day, week, etc.).
Select which metrics appear via the KPI Selector drop-down menu, then select whether to analyze Unique Impressions, Impressions, Total Phone Conversations, Phone Conversations, Email Conversations, or Engagements.
Select the filter button to use optional additional filters to get more granular, filtering by Popup Name, Platform, or Enabled.
Hover over data points to view the associated exact date and metric value.
TIP! When using a custom date range to view analytics for a specific month in the Postscript app, be sure to add an extra day on the tail end of the date range. For example, to view analytics for the month of June, please input the custom range as 06/01 to 07/01.
Popup Trend Visualizations
Based on the selections above, brands will see a bar chart displaying how the KPI has performed during the selected time period.
Beneath that, merchants will see two more charts looking at conversion trends by channel.
Each chart displays bars for the total volume of popup impressions for each time period and is overlaid with a line indicating conversion rates for the channel.
Popups Analytics Data Tables
Scroll down to the bottom of the page to see popup data in table formats. Similar to the interactive graphs above, the data displayed in the data table will depend on the time period and filters selected. Clicking on a column header sorts it in ascending or descending order.
Is Enabled. Indicates whether the popup is turned on or off.
Trigger Type. Indicates when a popup is displayed, such as after a Delay or an Exit.
Last Updated At. The date of the popups last edit (or creation).
Unique Impressions. How many times the popup was seen over time period.
Phone Conversions. How many phone conversions each popup converted.
Email Conversions. How many email conversions each popup converted.
Engagement CVR. The percentage of popup impressions that resulted in a phone or email conversations.
Phone Conversion Rate. The percentage of popup impressions that resulted in a phone conversions.
Email Conversion Rate. The percentage of popup impressions that resulted in an email conversions.
Brands can also take a deeper dive into the analytics by viewing Popup Detail by Period to see how different popups performed during specific date ranges.
Popup Traffic Sources
Note: Traffic source data is available starting April 14, 2024. Date ranges before this will not return results.
The Popup Traffic Sources tab shows exactly which traffic sources — paid, organic, email, and more — are driving your popup subscribers, and follows those subscribers all the way through to purchases. This is especially useful for brands running paid media or multiple landing pages.
TIP! This tab relies on UTM parameters being passed to your popup links. If UTM tracking isn't set up, traffic will appear as "(not set)" in the report. Note that "(not set)" doesn't necessarily mean organic traffic — it simply means no UTM parameter was associated with that subscriber, which can happen for a variety of reasons. Make sure UTM parameters are configured on your links to get the most out of this report.
To use the Popup Traffic Sources tab:
Navigate to Data & Insights in the side menu of your Postscript dashboard, then select Popups, and click the Popup Traffic Sources tab.
Use the Opt-in Date dropdown to set your date range.
Use the Metric dropdown to choose which metric to display in the charts. Options include:
Subscribers — Total number of new phone subscribers.
Order CVR (D1) — Percentage of new subscribers who placed an order within 24 hours of opting in.
Revenue per Sub (D1) — Average revenue attributed per subscriber within the first 24 hours.
Attributed Revenue D1 — Total revenue attributed to new subscribers within the first 24 hours.
Use the UTM Parameter dropdown to choose which parameter to break down by: UTM Source, UTM Medium, UTM Campaign, UTM Content, UTM Term, or First Page Visited. Use First Page Visited to track performance by specific landing pages on your site.
Optionally, use the Popup Name dropdown to filter results to a specific popup.
The page displays two charts based on your selections:
[Metric] over Time by [UTM Parameter] — A line chart tracking your selected metric over time, broken down by the top 5 values of your selected UTM parameter. Click any value in the legend to show or hide it from the chart.
Aggregated [Metric] by [UTM Parameter] — A bar chart showing the total aggregated value of your selected metric per UTM value across the selected date range.
Below the charts, two data tables provide a deeper breakdown:
Performance by UTM Source
Performance by UTM Source shows metrics for each UTM value, with the following columns: UTM Source, Unique Impressions, Subscribers, Phone Opt-in Rate, Order CVR (D1), Revenue per Sub (D1), and Attributed Revenue D1. Higher-performing values are highlighted with darker color formatting, making it easy to spot which sources are driving the best results at a glance.
Performance by Popup
Performance by Popup shows the same metrics broken down by individual popup name. This is useful when multiple popups are running at the same time and you want to understand which specific popups are contributing to a given traffic source's performance.
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