Analyzing Inline (Web) Personalization Campaigns

Once you launch a Web Personalization 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 Web Personalization. You can click on the (hyperlinked) Campaign’s Name to analyze a 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](analysing-segments #section-4-campaigns) section. You can click on the (hyperlinked) Campaign Name to analyze the Web Personalization campaign in further detail.

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

Understanding Top Panel

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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.

  • (Campaign) Type: Given the highly targeted nature of Web Persnalization, all campaigns created through the channel are considered to be Triggered campaigns by default.

  • (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.

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  • 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 Web Personalization Campaigns

A step-by-step guide on how you can modify Web Personalization 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:

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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 analyze.

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

Step 3: Specify Level of Data Granularity

You can create up to 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 analyze 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 4: 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!

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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 team members.

Here's how you can go about it:

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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.

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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

Step 5: Select Level of Data Granularity

At WebEngage, you can create up to 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 analyze 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.

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Step 6: 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 7: 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 Web Personalization 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.

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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.

  • 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.

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  • 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, 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, 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 a Web Personalization 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 Web Personalization 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:

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 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.

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Let's go over each card:

Unique Impressions

Indicates the total number of users that have seen the Web Personalization Banner at least once within the selected time frame.

Total Impressions

Indicates the total number of times users viewed the Web Personalization Banner on the web browser 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 Web Personalization Banner within the selected time frame.

  • The card also indicates the number of users that clicked on the Web Personalization Banner 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 Web Personalization Banner, 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 Web Personalization 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 banner (4,353) and those who made the purchase (8,109).

  • 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 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 Web Personalization Campaign's Conversion Rate against Control Group

For example, in the above visual, we have analyzed the conversion rate of a Web Personalization campaign nudging users to search for summer clothing under the clothing section.

The campaigns Performance Overview reveals that:

  • Unique Conversion Rate of the campaign: 2.38%

  • Unique Conversion Rate of CG: 2.26%

  • Conversion Uplift: 5.30% (negative uplift is always indicated in red)

Clearly, the Web Personalization campaign performed well but did not contribute majorly against the organic conversions.

Thus, it's always advisable to test your campaigns 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:

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

2. Variation Comparison

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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 Web Personalization 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 Web Personalization 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 different variations in the message on the banner and thus, created three versions of the campaign.

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

End Goal: Identify which message style leads to higher conversions

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Key takeaways:

  • Variation C emerges as the winner as it resulted in maximum Unique Conversions - 6.08%, contributing $ 295,435 in Revenue! While Variation A achieved a Unique Conversion rate of 5.4%, contributing $1,7,896 in Revenue and Variation B achieved a Unique Conversion rate of 4.84%, contributing $166,476 in Revenue.

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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.

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For example, in the above visual, we can see that Variation C (6.08%) achieved a higher Unique Conversion rate and was determined the winner.

This is because Clicks was selected as the Win Criteria of the test while setting it up, and Variation C (3.28%) achieved a higher Unique Click Rate than Variation A (2.47%). and Variation B (2.72%). 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 its true impact on driving conversions. This can be done by enabling Control Group at Step 4: Conversion Tracking while creating the campaign.

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 1 Variation of a Web Personalization campaign and a Control Group against Unique Impressions, Unique Clicks, Unique Conversions and Revenue.

  • 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 Variation 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 2.08%, contributing $324,114 in Revenue.

  • Variation A influenced the maximum number of users to convert, achieving a Conversion Uplift of 2.25% and contributing a whopping $345,689 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).

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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

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By adding values to the query bar highlighted above, you can choose to analyze Variations split by the Browser, Device Type, and OS or vice-versa, against all the performance indicators tracked for Web Personalization 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)

  • Browser (Chrome, Edge, Opera, Firefox, Safari, and so on)

  • Device Type (Mobile, Desktop)

Step 1: Select Performance Indicators

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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)

(Detailed read on what each performance indicator denotes)

Step 3: Preview Variation's Message & Layout

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As shown above, using the View icon placed next to each Variation's header, you can preview the Web Personalization Banner for both, Desktop and Mobile users. This is a great way to understand how varied copies and layouts impact user-campaign interactions.

Step 4: Select a Data Format

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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

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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 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.

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Use-case: Analyzing Engagement Trends for a Cart Recovery Campaign

In the visual below, we have analyzed the engagement trends of a Journey Web Personalization campaign for the last 7 days (Nov 28 - Dec 21) as a Funnel View.

About the campaign:

  • The campaign aims at driving purchases for an e-commerce app by offering free shipping to all users who have searched for a product but have not purchased it even after 30 minutes. It's triggered for all users who perform the custom event - Product-Searched, after a Wait Time of 30 minutes if the user has not performed the custom event - Checkout-Complete.

  • The Conversion Event is also set as Checkout-Complete with a Conversion Deadline of 2 Days.

  • The campaign was launched on November 28.

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On analyzing engagement trends, we learn that:

  • The highest number of Unique Impressions, 43,597 and Unique Conversions, 5,518 occurred on Nov 30.

  • Interestingly, the engagement trends suggest that most of the users who performed the campaign's Conversion Event - Checkout Complete, did not actually click on the notification. They simply viewed it and converted.

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Now, let's widen the scope of analysis to a month (Oct 13 - Nov 13) to gain a better perspective on the campaign's engagement trends.

It reveals that:

  • The highest Unique Impressions occurred on Nov 2, 600, followed by Oct 20, 556.

  • The Unique Conversion and Unique Click trends throughout the month suggest that there is no correlation between the clicks and conversions contrary to popular assumption. Even though a low number of users clicked on the campaign, the conversion numbers consistently remain high.

  • Further, the highest Unique Conversions also occurred on Nov 2, 326.suggesting that users targeted by the campaign on this day had a higher intent to convert compared to other users.

We hope this has equipped you with a robust understanding of how you can leverage Engagement Trends to gain valuable insights into user behavior and the campaign's overall performance.

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

Step 1: Select a Variation

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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

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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).

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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.

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Use-case: Analyzing a Web Personalization Campaign Nudging Users to Search for University Enterance Exam Practice Material After University Search

Let's take the example of an international Edtech website. They recently launched university entrance exam study material as a new feature, and in a bid to drive adoption, they decided to contextually nudge users to try it out.

  • Marketers of the website created a campaign that nudges all users who have searched for universities to search for a university entrance exam material.

  • The end goal was to drive adoption and not necessarily purchase (as an outcome of great product adoption). Hence, the campaign's Conversion Event was set as the custom event, University-Search.

Now, let's analyze the campaign to understand it's users and their behavior better.

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Analysis 1 (in continuation of the use-case)

Identifying the top countries and type of users who searched for universities entrance exam material after searching for universities, over the last 30 days. For this, we'll analyze Total Impressions over Countries, split by User Type.*

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As shown above, here's how they went about their analysis:

Step 1: Since the campaign was launched in past, we'll select Last 30 days as the time frame of analysis.

Step 2: Select Country under the field - Over.

Step 3: Select User Type under the field - Split By and click enter!

It reveals that:

  • The notification was viewed 91,896 times within the selected time frame.

  • The maximum number of users engaged through the Web Personalization Banner are located in India, out of which The highest number of Impressions were recorded for *Known Users, 79,913.

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Analysis 2 (in continuation of analysis 1 of the use-case)

Now, let's analyze users who performed the conversion event of the campaign (Total Conversions), against the same variables, User Type and Country. This will help us draw a fair comparison between the users who viewed the notification and those who converted.

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As shown above, we'll select Total Conversions under the field - Show and click enter.

It reveals that:

  • Users engaged through the notification performed the campaign's Conversion Event - Hotel-search a total of 6,048 times within the selected time frame.

  • Keeping up with the Total Impression trends, the maximum number of converted users are located in India and are Known.

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Analysis 3 (in continuation of analysis 2 of the use-case)

Now that we have a fair idea of the campaign's impression and conversion trends, let's dig into the time of the day and country where the users interact with the website. For this, we'll analyze Total Conversions over Hours of the Day, split by Country.

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As shown above, here's how they went about their analysis:

Step 1: Select Hours of the Day under the field - Over.

Step 2: Select Country under the field - Split By and click enter!

It reveals that:

  • Maximum users engaged by the Web Personalization are from India India.

  • The highest Conversions occurred between 11 pm - 12 am (as per the account's timezone), followed by a spike in Conversions between 12 am pm - 1 am. This indicates that most users prefer to engage with the app during late-night as they unwind from a tiring day.

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

Step 1: Select a Variation/ Control Group

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If you have created multiple Variations for a Web Personalization 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, 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

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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:

(Detailed read on what each performance indicator denotes)

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

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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 Browser preferences

  • The trend of occurrence of selected campaign event against Hours of the Day, Days of 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 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 User Type

As discussed under Users, at WebEngage, users can be two types, Known (identified users) or Unknown (anonymous users).

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As shown above, using the first dropdown placed on the top left, you can select a user type to analyze campaign engagement as per your needs.

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The following options can be selected here:

Step 2: Select a Parameter

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As shown above, using the second dropdown placed on the top left, you can customize the List of Users by selecting a parameter. For example, in the above visual, we have customized the list of Known Users by Impressions.

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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 Web Personalization Banner.

  • 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 Web Personalization.

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

4. Impressions: Helps you analyze all the users that have seen the Web Personalization campaign against the following columns:

  • Total Impressions

  • Latest Impression Date**

3. Clicks: Helps you analyze all the users who 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

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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

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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 User ID.

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Why is the same User ID shown in multiple rows?

As visible in the above visual, multiple rows get populated with the same User ID on searching for a user. 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 Web Personalization campaign twice as a result. Thus, if a triggered campaign is sent to a user multiple times, you will be able to analyze their interaction with each run of the campaign, as shown above.

Access User Profiles

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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!

Updated 6 months ago

Analyzing Inline (Web) Personalization Campaigns


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