Analyzing In-app Campaigns

Once you launch an In-app campaign through the channel or a journey, its impact on user engagement and revenue can be analyzed in detail through Campaign Overview.

How to Access

Let's quickly show you how you can access campaign analysis through the various sections of your dashboard:

Access Campaign Overview through List of Campaigns

A list of all the campaigns created through the channel can be found under the List of Campaigns section or the central hub of In-app. As shown below, you can click on the (hyperlinked) Campaign’s Name to analyze a campaign in further detail.

Access Campaign Overview Through Journey Overview

A list of all the campaigns attached to a journey can be found under Campaigns in the journey's Overview. As shown below, you can click on the (hyperlinked) Campaign Name to analyze the In-app campaign in further detail.

Access Campaign Overview through Segment Overview

A list of all the campaigns sent to a segment of users can be found under Campaigns in the segment's overview section. You can click on the (hyperlinked) Campaign Name to analyze the In-app campaign in further detail.

Before we dive into campaign analysis, let's get you acquainted with the top panel.

Understanding Top Panel

As highlighted above, the top panel provides a quick snapshot of the campaign with key details like:

• Campaign Name: As defined at Step 1: Audience, while creating the campaign.

• (Target) Audience: Indicates the segment targeted by the campaign, as defined at Step 1: Audience, while creating the campaign.

  • You can click the (hyperlinked) segment's name to analyze its users and rules of segmentation, as shown below.

• (Campaign) Type: Given the highly targeted nature of In-app Notifications, all campaigns created through the channel are considered to be Triggered campaigns by default. Thus, depending on where the campaign has been created, it could be of the following types:
  • Triggered
  • Journey: As shown below, all in-app journey campaigns can be traced back to the journey they're attached to by clicking on the (hyperlinked) campaign type, Journey. Doing so will direct you to the journey's Live View.

• (Campaign) Status: Indicates the current status of the campaign.

  • If you save a campaign without launching it, then it will be saved as a draft. The same is reflected by the status, Draft.

Now, let's get you acquainted with its features:

Modify Campaign

As shown below, using the icons placed next to the Campaign's Name, you can choose to Edit, Delete, Duplicate, Pause/Resume and Tag the campaign, as per your marketing needs.

• All modification icons are hidden for journey campaigns since they can be modified only through the journey they have been created through.
• Once you Pause a Running campaign, you can choose to Resume it's delivery to the target audience by clicking the Resume icon, as highlighted above.

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Related Read: Modifying In-app Campaigns

A step-by-step guide on how you can modify In-app campaigns.

Download a Report

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Please Note

Reports can be downloaded only by Admins who have access to Account Management. If you are unable to do so, then please get in touch with the account owner.

You can easily download a copy of campaign stats for offline analysis, upload it to another platform, and so on. Here's how you can go about it:

Step 1: Click the Download icon

As shown above, in doing so, you will be prompted to specify the kind of data you want to analyse.

Step 2: Specify the time frame for which the stats should be shown (Data to Include)

As shown above, you can specify the time frame as:

• Campaign's Start Date till Present Date
• Custom Dates

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Detailed Read

• How Data to Include works

• Understanding Report Stats

Step 3: Select Data Breakdown

In this dropdown you can choose from 4 options i.e. _Day-wise, Week-wise, Month-wise, and 30 days rolling window. _Each of these have been explained below.

• Day-wise: When you choose the day-wise option the report that will be sent to you will have an aggregate of each day i.e. each row will consist of each campaign or variations day wise statistics.
  For example, if you want to download a report for the last 7 days, by choosing the day wise data breakdown option, you will receive a report with 7 rows each containing data for each of the days.
• Week-wise: When you choose this option the report will consist of the aggregate of each week, i.e. Every row will contain the week-wise statistics for each campaign or variation, with each week defined from Monday to Sunday.
  For instance, if you download a report for the past 1 month on the 30 Nov ’23 , and set the data breakdown option to week-wise, then you will receive a report that consists of 5 rows of aggregated data for each week starting from Monday to Sunday. Whereas, if a month starts during the middle of the week, for example the 1st of the month is on a Thursday, then the row for the first week will be from Thursday to Sunday.
• Month-wise: On choosing this option your statistics will be aggregated for each month i.e. each row will consist of month wise statistics. (calendar month will be considered)
  If you wish to download a report spanning from January 1st to November 30th and select the month-wise data breakdown option, you will receive 11 rows. Each row will contain aggregated data for each respective month, providing a comprehensive breakdown of information (based on calendar month).
• 30 day (Rolling window): On choosing this option, your statistics will be aggregated based on every 30 days irrespective of the calendar month, i.e. Every row will include the rolling window statistics for each campaign or variation for up to 30 days.
  For example, if you choose a date range from 15th June to 14th August, two rows will be generated i.e. 15th June to 14th July and 15th July to 14th August.

Click here to know more about the use cases of each.

Step 4: Specify Level of Data Granularity

You can create upto 5 versions of a campaign and test each one to determine the copy that resonates with your audience. Thus, while downloading a report, you can choose to analyse consolidated campaign stats OR a variation-wise breakdown.

As shown above:

• Select Campaign Level Granularity to view the average performance of all campaign variations.

• Select Variation Level Granularity to view the individual performance of each variation and identify the top performing version.

Step 5: Click Download!

Schedule a Report

In our quest to make campaign reporting a seamless experience, we built Scheduled Reports - customizable and automated reports delivered straight to your inbox!

As highlighted above, using the Reporting icon, you can set up a periodic report to have all the stats shown under Overview, emailed to multiple the team members.

Here's how you can go about it:

Step 1: Click on the Reporting icon

• As shown above, in doing so you will be prompted with a pop-up allowing you to customize the report's settings.
• The report's name will be the same as the campaign's name. This will be included in:
  • The emailed report's subject line
  • under the Scheduled Reports section of your dashboard

Step 2: Define the Frequency of report delivery

You can choose to have a report delivered on a Daily, Weekly or Monthly basis, as per your needs.

• As shown above, we have selected Weekly as the Frequency for our report.

Step 3: Specify the time of delivery (When)

As shown above, you can choose to have the report delivered at a specific time of the day. The same can be defined in an AM/PM format against the field, When.

Step 4: Specify the time frame for which the stats should be shown (Data to Include)

Too many data points always lead to chaotic insights. This is why we have made it possible for you to specify the time frame (number of days) for which you'd like to receive campaign stats.

As shown above, you can select a time frame between Last 1 Day to Last 30 Days _against _Data to Include.

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Detailed Read

• How Data to Include works

• How a combination of Data to Include & Frequency determine the date of stats included in the report

• Understanding Report Stats

Step 5: Select option for Data Breakdown

In this dropdown you can choose from 4 options i.e. Day-wise, Week-wise, Month-wise, and 30 days rolling window. Each of these have been explained below.

• Day-wise: When you choose the day-wise option the report that will be sent to you will have an aggregate of each day i.e. each row will consist of each campaign or variations day wise statistics.
• Week-wise: When you choose this option the report will consist of the aggregate of each week, i.e. Every row will contain the week-wise statistics for each campaign or variation, with each week defined from Monday to Sunday.
• Month-wise: On choosing this option your statistics will be aggregated for each month i.e. each row will consist of month wise statistics. (calendar month will be considered).
• 30 day (Rolling window): On choosing this option, your statistics will be aggregated based on every 30 days irrespective of the calendar month, i.e. Every row will include the rolling window statistics for each campaign or variation for up to 30 days. For example, if you choose a date range from 15th June to 14th August, two rows will be generated i.e. 15th June to 14th July and 15th July to 14th August.

Step 6: Select Level of Data Granularity

At WebEngage, you can create upto 5 versions of a campaign and test each one with a small test segment to determine the copy that resonates with your audience. Thus, while scheduling a report, you can choose to analyse consolidated campaign stats OR a variation-wise breakdown.

As shown below:

• Select Campaign Level Granularity to view the average performance of all campaign variations.

• Select Variation Level Granularity to view the individual performance of each variation and identify the top performing version.

Step 7: Add team members as Subscribers

As shown above, you can choose from a list of all the team members who have access to your WebEngage dashboard. Doing so will ensure that all the added users receive the campaign performance report, as per its settings.

• However, if a team member is not a part of your WebEngage account, then you will not be able to add them as a Subscriber.

Step 8: Click the Schedule button

• A notification will pop-up on the bottom right corner of the page, confirming that the report has been scheduled. (Understanding Report Stats)

• You can modify or delete the report anytime you like through the Scheduled Reports section, nested under Settings in your account.

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Please Note

• Reports can be configured by only those Admins that have access to Account Management. Please get in touch with the account owner if you're unable to do so.

• You can schedule additional reports for campaigns sent through In-app and all the channels combined through Settings > Scheduled Reports in your dashboard.

See Campaign Details

As demonstrated below, clicking Show Details reveals a thorough recap of all the rules and settings specified while creating the campaign. This section can be minimized by clicking Hide Details.

Here's a list of all the details shown here:

• Campaign ID: A unique campaign ID is generated by us each time you create a campaign.

• Target Devices: As selected at Step 1: Audience, while creating the campaign, this can be any of the following options:

  • Both Android and iOS
  • Only Android
  • Only iOS

• Start Date: Indicates the date-time on which the campaign was launched or will be launched (if the campaign is still scheduled), as specified at Step 2: When, while creating it.

• End Date: Indicates the date-time on which the campaign will end or ceased getting delivered. An End Date can be specified at Step 2: When while creating it.

• Tags: Tags is a handy feature that helps you categorize your campaigns as per their purpose, target audience, frequency or any other parameter that makes them easier to search for.

  • If a campaign is tagged: All the tags added to the campaign will be shown here. You can click on a hyperlinked tag to add more tags to the campaign or remove existing ones.
  • If no tags have been added: As shown below, you can click on Add Tags to create new tags for the campaign and add existing ones to it.

• Audit Logs: Click View to access a history of all the interactions your account admins have had with the campaign. Each action, including campaign creation, message edits and changes made to its settings is recorded here. (Detailed Read)

• Conversion Event: Indicates the action users are expected to perform on your app after receiving the campaign, as specified at Step 4: Conversion Tracking, while creating it.

  • If you have not set up Conversion Tracking for the campaign or the journey it's attached to, then the same will be indicated by the status Disabled, here.

• Conversion Deadline: Indicates the duration till which the campaigns' Conversion Event will be tracked after it has been delivered. The same can be specified at Step 4: Conversion Tracking while creating the campaign.

  • If you have not set up Conversion Tracking for the campaign or the journey it's attached to, then the same will be indicated by the status Disabled, here.

• Control Group: Indicates whether or not a Control Group was set up to measure the campaign's effectiveness against organic user behavior at Step 4: Conversion Tracking, while creating it. The same is indicated by:

  • Enabled
  • Disabled

• Send Winner: Indicates whether or not automated Variation testing was configured for the campaign while creating it, by setting up Send Winning Variation Automatically at Step 4: Conversion Tracking. The same is indicated by:

  • Enabled
  • Disabled
  • If Send Winner is enabled, then the following details will help you out with a quick recap of the rules of testing:
    • Size: Indicates the size of test audience with which all the _Variations _of the campaign will be tested with to determine a winning variant.
    • Time to Test: Indicates the duration for which all the Variations of the campaign will be tested for.
    • Win Criteria: Indicates the parameter (Impressions, Clicks, Conversions) based on which a winning Variation will be determined.

• Created By: Indicates the name of the user who created the campaign.

• Created On: Indicates the date-time on which the user started creating the campaign.

• Last Edited By: Indicates the name of the user who has made the most recent edit to the campaign.

• Last Edited On: Indicates the date-time on which the most recent edit was made to the campaign.

Now, let's show you how you can analyze an In-app Campaign to gain valuable insights into its impact on user engagement, conversions, and revenue.

How to Analyze

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Must Read

Please refer to Campaign and Channel Performance Indicators for a complete list of all the user-channel interactions tracked for In-app campaigns.

As shown above, using the navigation bar, you can toggle between the following sections to slice-and-dice data and analyze multiple aspects of the campaign:

• Overview
• Analyze
• List of Users

Select a Time Frame of Analysis

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Please Note: You Cannot Analyse 'List of Users' for a Specific Duration

List of Users includes campaign engagement details for all the users that have been a part of the campaign's target audience throughout its lifetime.

By default, all stats under Overview and Analyze are shown from the campaign's Start Date till present day (if the campaign is running) or till upto 45 Days from the campaign's End Date (if the campaign has ended).

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Using the date range filter, you can analyze the campaign's performance for the following durations:

• Today

• Yesterday

• Last 30 Days

• Last 60 Days

• Last 90 Days

• Custom Dates (as selected by you)

Now, let's dig into each section, starting with Overview.

Overview

Here you can analyze the campaign's performance from its Start Date till the present day (if the campaign is running) or till 45 days from the campaign's End Date (if the campaign has ended), against key performance indicators like Impressions Clicks, Conversions, Revenue for each Variation. You can alter this by selecting a time frame.

1. Performance Overview

This subsection presents a summary of the campaign against key performance indicators like Unique Impressions, Unique Closes, Unique Click, Unique Conversions, and Revenue.

Let's go over each card:

Unique Impressions

Indicates the total number of users that have seen the In-app Notification at least once within the selected time frame.

Unique Closes

• Unique Close Rate: Calculated against the number of Impressions, it indicates the share of users who dismissed or closed the In-app message within the selected time frame.

• The card also indicates the total number of users who dismissed or closed the In-app Notification within the selected time frame.

Unique Clicks

• Unique Click Rate: Calculated against the number of Impressions it indicates the share of users that clicked on the In-app Notification within the selected time frame.

• The card also indicates the number of users that clicked on the In-app Notification, helping you gauge the campaign's true impact on user engagement.

Unique Conversions

• Unique Conversion Rate: Calculated against the total number of messages Delivered, it indicates the share of users that performed the campaign's Conversion Event at least once within the selected time frame.

• The card also indicates the number of users converted through the In-app Notification, helping you draw a fair comparison between the number of users who clicked on the campaigns, users who converted, and the total Revenue.

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Comparing the number of Clicks - Conversions and Total Revenue of an In-app Campaign

For example, a quick look at the campaign's Performance Overview above reveals that contrary to the popular assumption, there is no correlation between the number of users who clicked on the notification (41) and those who booked a hotel stay (71).

• This is an extremely valuable insight as it could mean that most of these users had a high intent to purchase and would have booked the hotel stay irrespective of the offer.

• The hypothesis can easily be tested by adding a Control Group to the campaign's target audience and comparing the conversion rate of the two groups (since control group users will not receive the campaign).

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Please Note

Conversions will not be tracked for your campaign/journey if you have not specified a Conversion Event at Step 4: Conversion Tracking, while creating it.

Detailed Read on how Conversion Tracking works.

• Compare Unique Conversions with Control Group: If you have enabled Control Group while creating the campaign, then as highlighted below, you will be able to draw a scientific comparison between the campaign's conversion rate and the organic conversion rate - helping you understand its true impact.

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Analyzing In-app Campaign's Conversion Rate against Control Group

For example, in the above visual we have analyzed the conversion rate of an In-app campaign nudging users to search for hotels at destinations, related to their recent flight search history.

The campaigns Performance Overview reveals that:

• Unique Conversion Rate of campaign: 54.37%

• Unique Conversion Rate of CG: 73.91%

• Conversion Uplift: - 26.43% (negative uplift is always indicated in red)

Clearly, the In-app Notification deterred users from performing their organic behavior, causing lower hotel searches. For the same reason, the campaign has been Paused.

Thus, it's always advisable to test your campaigns (and journeys) with a Control Group before sending it to the entire target audience to ensure that it helps amplify the desired user behavior, and not hinder it. Here's how you can automate Variation testing with a Control Group.

Now, let's walk you through the metrics shown here:

• Unique CG Conversions: Calculated against the total number of users included in the Control Group (CG), it indicates the share of users that performed the campaign's Conversion Event at least once within the selected time frame, even though they didn't receive the campaign.

• Conversion Uplift: Indicates the percentage increase or decrease in the Unique Conversion rate achieved by the campaign, calculated against the Unique Conversion rate of the Control Group.

  • It's shown beside the campaign's Unique Conversion rate, in Green for positive uplift, in Red for negative uplift, and in Grey for no uplift.

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Fact Check

Conversion Uplift equals [(Unique Conversion Rate of Campaign/ Unique Conversion Rate of CG) x 100] - 100

Revenue

Indicates the amount of Revenue tracked for the Total Conversions that have occurred within the selected time frame.

• Revenue numbers are always shown in the currency selected by you while setting up Revenue Mapping

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Please Note

Revenue will not be tracked for your campaign if:

• You have not set up Revenue Mapping for your account

• You have not specified a Conversion Event while creating the campaign (or its journey)

• You have not mapped the specified Conversion Event as a Revenue Event in your account

Detailed Read on how Revenue tracking works and how Revenue is attributed to a campaign.

2. Variation Comparison

The most insightful section of Campaign Overview, Variation Comparison helps you analyze the impact of each message Variation against key metrics like their Layout (each Variation can have a different template), Dismisses, Clicks, Conversions, Revenue and so on, for the chosen time frame.

However, depending on the settings specified while creating the campaign, the stats shown here may vary. Let's get you acquainted with the impact of each:

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Skip to: How to customize & analyze this section as per your strategic needs.

2.1. When Variation Distribution is Set Manually

If you have manually specified the audience size for all the Variations at Step 4: Conversion Tracking, then using this section, you will be able to identify a winning Variation by analyzing the performance of each. The following aspects of the test will be highlighted here:

• Percentage of the audience targeted by each Variation (calculated against the total target audience)
• The performance of each Variation against all the performance indicators tracked for In-app campaigns

Let's demonstrate a short use-case to show you how it works:

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Analyzing Manual Variation Distribution Test Results

Let's take the example of an e-commerce app. In the visual below, we have analyzed the performance of a journey In-app campaign offering free shipping to all users who have added products to their cart but have not completed checkout yet.

Marketers of the app wanted to compare the effectiveness of a footer notification and a header notification and thus, created two versions of the campaign.

• Variation A was a Footer style notification

• Variation B was a Header style notification

Both variations consisted of the same message and were equally divided amongst the target audience.

End Goal: Identify which layout style leads to higher conversions - Footer or Banner?

Here's what their analysis looked like...

Key takeaways:

• Variation A emerges as the winner as it resulted in maximum Unique Conversions - 56.12%, contributing $800K in Revenue! While Variation B achieved a Unique Conversion rate of 53.27%, contributing $720K in Revenue.

• The lower Unique Close rate (21%) and higher conversion rate of Variation A clearly indicate that users preferred to interact with a Footer style In-app Notification.

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Skip to: How to customize and analyze this section as per your strategic needs.

2.2. When Send Winning Variation is Enabled

If you have enabled Send Winning Variation Automatically at Step 4: Conversion Tracking while creating the campaign, then you will be able to analyze the test results through this section. As shown below, the following aspects of the test will be highlighted here:

• The winning Variation (which was automatically sent as the only campaign to the entire target audience)
• The performance of each Variation that was tested with the test audience

For example, in the above visual, we can see that even though Variation A (3.4%) achieved a higher Unique Conversion rate that Variation B (3.1%), the latter was determined the winner.

This is because Clicks was selected as the Win Criteria of the test while setting it up, and Variation B (13%) achieved a higher Unique Click Rate _than _Variation A (12.45%). Similarly, you too can select a custom Win Criteria for testing the Variations, as per your business goals.

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Skip to: How to customize and analyze this section as per your strategic needs.

2.3. When Control Group is Enabled

You can compare each Variation's conversion rate with the Control Group's organic conversion rate to determine it's true impact on driving conversions. This can be done by enabling Control Group at Step 4: Conversion Tracking while creating the campaign or the journey (the campaign is attached to).

As shown below, the extent to which a Variation influences users to perform the Conversion Event can be measured through its Conversion Uplift, indicated alongside Total Conversions and Unique Conversions, in Green, for positive uplift, in Red, for negative uplift and in Grey for no uplift.

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Analyzing Variations Against Control Group through Conversion Uplift

In the above visual, we have analyzed 2 Variations of an In-app Notification and a Control Group _against _Unique Impressions, Unique Closes, Unique Clicks, Unique Conversions and Revenue.

• Both Variations and the Control Group were equally divided amongst the campaign's Test Audience.

• Since Control Group was enabled for the campaign, Unique Conversion rate was the sole Win Criteria used to identify a winner version of the message.

On comparing the Variations against the Control Group we learn that:

• Users who did not receive the campaign as a part of the Control Group converted at a rate of 4.3%, contributing $4,570 in Revenue.

• Variation A influenced the maximum number of users to convert, achieving a Conversion Uplift of 6.97% and contributing a whopping $5,800 in Revenue!

  • As a result, Variation A was identified as the winner and was sent to the entire target audience of the campaign (indicated by the test results highlighted above).

• Variation B achieved a Unique Conversion Rate of 3.8%, indicating a decrease of 11.62% in conversion when compared to the Control Group's conversion rate, 4%.

  • This indicates that the notification had a negative impact as it deterred users from performing the desired behavior.

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Related Reads

1. Why you should (almost) always use a Control Group to measure the effectiveness of your campaign and how it works.

2. How you can test Variations with a smaller test audience and automatically send the winner to the entire target audience of the campaign!

Now, let's show you how you can slice-and-dice this section to gain relevant insights:

Step 1: Customize Table

By adding values to the query bar highlighted above, you can choose to analyze Variations split by the Device, OS or vice-versa, against all the performance indicators tracked for In-app campaigns.

In doing so, you will be shown a secondary view of each Variation, split by the selected option, helping you analyze user-campaign interactions in further detail, as shown below.

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The following options can be selected under both the fields:

Variations: Helps you compare the performance of all the Variations for the selected time frame.

Technology

• OS (iOS, Android)

Step 2: Select Performance Indicators

As shown above, using the filter icon placed on the top right, you can select/deselect metrics to customize the table as per your analytical needs.

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The following metrics can be selected here:

Totals (Total Impressions, Total Closes, Total Clicks, Total Conversions, Total Click-through Conversions)

Uniques: (Unique Impressions, Unique Closes, Unique Clicks, Unique Conversions, Unique Click-through Conversions)

• Revenue (Total Revenue, Click-through Revenue)

(Detailed read on what each performance indicator denotes)

Step 3: Preview Variation's Message & Layout

As shown above, using the View icon _placed next to each _Variation's header, you can preview the In-app Notification for both, iOS and Android users. This is a great way to understand how varied copies and layouts impact user-campaign interactions.

Step 4: Select a Data Format

While the default view shows you percentage values (%) for all the campaign performance indicators, using the overflow menu highlighted above, you can choose to analyze these stats as numbers (by selecting #).

• Percentage value of all the performance indicators like Closes, Clicks, Conversions and Click-through Conversions is calculated against the total number of Impressions.*

3. Engagement Trends

This section helps you analyze day-wise user engagement trends for each Variation against the following performance indicators, as per the chosen time frame.:

• Unique Impressions
• Unique Closes
• Unique Clicks
• Unique Conversions

Let's analyze a use-case to get you acquainted with the workings of this section:

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Skip to: How you can customize the stats shown here as per your analytical needs.

Now, let's show you how you can customize this section as per your analytical needs:

Step 1: Select a Variation

By default, engagement trends are shown only for Variation A (the first version of the campaign). Using the dropdown placed on the top left, you can choose to analyze trends for each Variation against - Unique Impressions, Unique Closes, Unique Clicks and Unique Conversions.

• If you have enabled Control Group for the campaign, then you can choose to analyze its Unique Conversion trends by selecting 'Control Group' from the dropdown highlighted above.

Step 2: Select a Format of Visualization

While the default format of visualization is a Line Graph, as shown above, using the overflow menu placed on the top right, you can change this to a Bar Graph or a Table, as per your analytical needs.

Analyze

While Overview presents a comprehensive view of the campaign's performance, this section helps you slice-and-dice data in multiple ways to gain maximum insights into user-campaign interactions.

First Impression

The default view of this section shows you a Day-wise trend for Total Impressions recorded for all the Variations from the campaign's Start Date till the present date or till up to 45 days from its End Date (whichever occurs first).

Using the query bar highlighted above, you can choose to analyze the campaign's performance against a specific performance indicator, split by 2 parameters for a custom time frame.

Let's Analyze a Use-case to Show You How it Works

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Skip to: How you can customize the stats shown here as per your analytical needs.

We hope this has equipped you with a broad understanding of how you can gain in-depth insights into your campaign, it's users and their preferences through Analyze. Now, let's walk you through all the steps of analysis:

Step 1: Select a Variation/ Control Group

If you have created multiple Variations for an In-app campaign, or have enabled Control Group for it, then using the dropdown highlighted above, you can choose to selectively analyze the performance of each.

However, if your campaign consists of just one Variation, then this dropdown gets hidden.

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Any one of the following options can be selected here:

• Overall: Helps you analyze the combined performance of all the Variations against each metric for the selected time frame.

  • For example, if you choose to analyze Revenue, Overall, then we will sum up the Revenue tracked for each Variation to help you analyze their collective impact.

• Variation A/B/C/D/E: Helps you analyze the performance of a Variation, against a selected performance indicator, as per the chosen time frame.

• Control Group: If you have enabled Control Group at Step 4: Conversion Tracking while creating the campaign or its journey, then selecting this option will help you its Unique Conversions/ Total Conversions.

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Related Read

Please refer to Campaign Variations and Testing for a quick read on how you can test multiple Variations of a campaign with a smaller audience and automatically send the winner to the entire target audience!

Step 2: Select a Performance Indicator

You can choose to analyze the overall performance of the campaign or each Variation against a performance indicator or campaign event (like Impressions, Clicks, Conversions, Revenue) by selecting an option under the field - Show.

• As highlighted above, the total value of the selected performance indicator is also indicated under the query bar.

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Any one of the following campaign events can be selected here:

• Totals (Total Impressions, Total Closes, Total Clicks, Total Conversions, Total Click-through Conversions)

• Uniques: (Unique Impressions, Unique Closes, Unique Clicks, Unique Conversions, Unique Click-through Conversions)

• Revenue (Total Revenue, Click-through Revenue)

(Detailed read on what each performance indicator denotes)

Step 3: Select the Dimension(s) for Analysis (Over & Split By)

As demonstrated for the use-case discussed above, by selecting an option under the fields - Over and Split By, you can choose to analyze the selected performance indicator (campaign event) against two dimensions (system attributes). This is a great way to dig into multiple aspects of the campaign like:

• The top Locations and Devices used to perform the selected campaign event

• The Types of Users who performed the campaign event and their OS preferences

• The trend of occurrence of selected campaign event against Hours of the Day, Days or the Week or Months of the Year and so on.

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The following options can be selected under both the fields:

• Time (Days, Weeks, Months)

• Time Block: Trends against time, Hours of Day, Days of Week, Months of Year, are always shown in your project's timezone, as set by you while setting up your WebEngage account.

• User Type (What it means)

• Location (Country, City)

• Technology (Device Type, OS Name, Device Manufacturer, Device Model, App Version, App ID, Platform)

List of Users

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Must Read

Please ensure that you have a good understanding of the various types of Users and related concepts before proceeding. Doing so will help you understand the workings of this section, better.

This section has been specially designed to help you track down campaign engagement details for each user that targeted by the campaign, over its entire lifetime.

First Impression

By default, List of Users shown you a Summary of user-campaign interactions for All Users who have been included in the campaign's target audience, from its Start Date till the present date or up to 45 days from its End Date (whichever occurs first).

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Please Note

All the stats and engagement details are gleaned over the entire lifetime of the campaign. For the same reason, List of Users cannot be analyzed for a particular time frame

Now, let's get you acquainted with its features:

Customize List

Here's how you can customize the List of Users as per your analytical needs:

Step 1: Select a Parameter

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The following options can be selected here:

1. Summary: Shows you an overall summary of all the users included within the target audience, against the following columns:

• Latest Message Status: Indicates the status of the message sent to the user with a date-time stamp as any one of the following:

  • Impression on (date-time)
  • Closed on (date-time)
  • Clicked on (date-time)
  • Converted on (date-time)
  • Added to Control Group on (date-time): Shown for all users who were not sent the campaign as they were added to the Control Group, as specified by you while creating the campaign.

• Total Impressions: Indicates the total number of times the user viewed the In-app Notification.

• Latest Impression Date:** Indicates the date-time on which the latest view occurred.

• Total Clicks: Indicates the total number of times the user has clicked on the In-app Notification.

• Latest Click Date: Indicates the date-time on which the latest click occurred.

2. Impressions: Helps you analyze all the users that have seen the in-app notification against the following columns:

• Total Impressions

• Latest Impression Date**

3. Clicks: Helps you analyze all the users have clicked on the campaign over its entire lifetime, against the following columns:

• Total Clicks

• Latest Click Date

4. Conversions: Helps you analyze all the users that have performed the campaign's Conversion Event, over its entire lifetime, against the following columns:

• Total Conversions: Indicates the total number of times the user performed the Conversion Event within the specified deadline.

• Latest Conversion Date: Indicates the date-time on which the latest conversion occurred.

• Latest Conversion Type: Indicates the campaign event Views, Clicks to which the conversion was attributed to as Click-through Conversion Impression-through Conversion or Send-through Conversion.

• Revenue: Indicates the total amount of Revenue contributed by the user (calculated against Total Conversions).

(Detailed read on what each performance indicator denotes)

Download List

As shown above, using the Download icon placed on the top right of the table, you can choose to download a user-wise engagement report for all the users targeted by the campaign, over its entire lifetime. Here's how you can go about it:

Step 1: Click the Download icon.

• In doing so, you will be prompted with a pop-up to re-confirm your decision.

Step 2: Click the Download button on the pop-up window to proceed.

• An email containing a link to the downloadable file will be sent to your registered email address shortly.

Search for a User

As shown above, using the search box placed on the top right, you can dig into the engagement status of a particular user by searching for their Email, User ID, and Phone.

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Why is the same User ID shown in multiple rows?

As visible in the above visual, on searching for a user, multiple rows get populated with the same User ID. Each row contains a different message status with a varying date-time of Impression and Conversion.

This is because the user chose to perform the trigger event twice and was sent the triggered In-app campaign twice as a result. Thus, if a triggered or journey campaign is sent to a user multiple times, then you will be able to analyze their interaction with each run of the campaign, as shown above.

Access User Profiles

As shown above, you can access the profile of a user targeted by the campaign by clicking their (hyperlinked) User ID. Doing so will help you analyze the user's channel preferences, personal details device preferences, latest interactions with your campaigns, app, website, the technical aspects of each interaction much more!

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Must Read

Please refer to Analyzing User Profiles for a robust understanding of how you can dig into the preferences and behavior of individual users.

We hope this has equipped you with a robust understanding of how you can mine valuable insights into a campaign to understand its real impact on user engagement and revenue. Please feel free to drop in a few lines at [email protected] if you have further queries. We're always just an email away!