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Analyzing and assessing Experiences' performance
Analyzing and assessing Experiences' performance

Learn how to use analytics to assess and optimize your Experiences' performance

Pulkit Agrawal avatar
Written by Pulkit Agrawal
Updated over a week ago

You made it! You have live Experiences, your users are engaging with them, and all that's left is to connect their impact to your product goals. 😊 With any Experience you create you can review key metrics over set periods of time, and layer these onto your product events to better understand their impact.

Chameleon collects some default data to help you analyze your Experiences. You can review the overall stats in your Chameleon Dashboard, export the full data as a CSV file, or send it automatically to your analytics platform (via one of our integrations, or API)

Availability & Usage

πŸ” Available for all plans

πŸ“ Analyze the impact of Tours, Tooltips, Microsurveys, Launchers

βš™οΈ Review or download from the Dashboard

Quick access

πŸ‘‰ We use Tours to exemplify the data you have available and how you can review key metrics. But for each Experience, the Dashboard will show a similar performance breakdown; and you can apply similar principles when analyzing other Experiences. The performance views do not include drafted Experiences.

Chameleon collects some data by default, from all the Experiences you have live. This includes events and properties, and all of these have a uid attached, so you can track and associate these with your users easily.

We track data that is directly associated with your in-product Experiences, so you can understand how they impact your product's adoption.

With each Experience, the data we collect will be slightly different based on the engagement options your users have. For example, the data collected for Tours include events such as:

Tour event


Started Tour

If an end-user sees the first step of a tour.

Completed Tour

If an end-user completes the last step of a tour (e.g. by clicking the button).

Exited Tour

When an end-user clicks the dismiss option in a Tour Step, this option is set to Exit the Tour.

Previewed Tour

When an admin user previews a tour.

Converted Tour

When a conversion event attached to a tour is triggered after the tour is started. See more about the conversion/goals below.

Step Seen

When a user views a step within a tour.

In addition, it also includes properties such as:

Tour Property



The name of the tour (as defined within the Editor).


The URL on which an event occurred (e.g. the URL of the first step of the tour for the Started Tour event).


The name of the step - sent for Exited Tour events.


The time in seconds between the Started Tour and Completed Tour / Exited Tour events (sent only for the latter events)

Browser, City, Country

and other browser-based properties

πŸ’‘ For full details of all data that Chameleon collects, view our schema Google Sheet:

We collect all this for each user so you can assess how users engage with your Experience, where they fall off, or where you can improve their journey.

Reviewing your Chameleon data, along with your product events enables you to understand how you can improve your efforts; and simply put, what's working and what isn't.

To make it easier to assess the performance of your Experiences, at a glance, you can view your overall Experience stats in your Chameleon Dashboard. Just head over to a specific Experience, and you'll see a performance breakdown, for how many Experiences you have live, how many users see them, and how they are performing overall.

πŸ’‘ Here, is where you can also download your data from the ellipsis menu to peruse outside Chameleon.

The performance graph is where you can understand how your Experiences perform over time, as well as understand how the changes you make impact their engagement and completion rate.

Here, you can see a breakdown of how many Tours were started and completed on a daily, weekly, or monthly basis, for a set time frame. On hover, you'll also see detailed stats for a particular period of time.

πŸ’‘ Use this to stay on top of how users engage with your Experiences and quickly spot spikes or different behaviors. You can connect a steady completion rate to a healthy trial activation, and so on.

You can use the table view below to understand how users engage with specific Experiences. Depending on the type you're reviewing, you'll also see some key metrics to help you understand better how they perform. With Tours, for example, you can:

  • Analyze the number of users who start and complete them

  • See the individual completion rate of each one

  • Review Tours that haven't been started recently (an indication that there might be something wrong)

Here are a few things you can review when assessing high/low performance:

  • if the Segment is as accurate as possible

  • are there any recent changes or updates made to the Experience?

  • when was it last updated/reviewed (any product changes your users are not aware of?)

πŸ‘‰ Learn more about reviewing Experience changes on the Activity feed and how you can use it for an efficient async flow with your team.

You can also open any Experience to review its individual performance, on the Analytics tab. In the first panel, you can review most of the table information with some useful additions, such as the page where the Experience is published, or its ID.

But below this, you can review a performance graph for the individual Experience; this can be a Funnel view, a breakdown of your Microsurvey responses, or your Launcher items completion.

Here, you can gain better insight into how users engage with your Experience. For example, the funnel reporting for individual Tours is powerful to identify drop-offs across Steps and help you improve your completion rate. This report lets you assess:

  • Total number of users that started and completed your Tour in the selected timeframe

  • Number and proportion of users (relative to users that started the Tour) that have seen and dropped off at each Step

With the performance review you conduct in the Dashboard, you can get a good picture of what's working or not and what you can try to improve.

But we encourage you to take your analysis one step further by exporting a spreadsheet -- either by downloading the CSV or by sending the data to your Google Drive. This enables you to analyze how your Experiences impact your product's adoption in the long run.

First, get familiar with the spreadsheet in front of you. Each row represents a unique action (event) a user has taken in your Tour, within the select time range. These events include:

  • Tour started, when a user sees the first Step of the Tour.

  • Tour exited, when a user dismisses any Step of the Tour (including the last Step).

  • Tour completed, when a user completes the last Step of the Tour.

  • Step seen, when a user sees a Step within the Tour.

  • And others that can be found in the "Events" tab of the Data Schema, such as Button clicked and Dismiss clicked.

Each row also contains user properties/attributes associated with the user that took this action. This includes default user properties collected by Chameleon and custom user properties that you're sending to Chameleon through our API, integrations (e.g. Mixpanel cohorts, HubSpot lists), or add via Chameleon Tags.

πŸ’‘ We highly recommend sending user properties to Chameleon to help target your Experiences. Learn more about how to send user data to Chameleon.

Next, review the Data glossary below πŸ‘‡ to gain a good overview of what each column represents.

Below are the definitions of the columns you will see in your exported data. All data is accurate at the time that the event took place, for the live/published Tour:

Data property



Unique and persistent ID for that Tour. Learn how to expose this.


Name of the Tour.


Total number of Steps in the Tour.


Unique and persistent ID for the Step (only for Step seen events).


The sequence number of the Step within the Tour (only for Step seen events).


Type of event (see above).


Time when the event took place.


Time since the beginning of the Tour (for Tour events).

Time the Step was showing (for Step events).

Divider indicating what the next set of columns correspond to.


Unique ID for the user that caused the event, as sent by your product. *


Width of the browser, in pixels.


Name of the browser.


Default browser language code.


The timezone for the browser, relative to GMT/UTC. **


Number of web sessions detected by Chameleon for that user. ***

Divider indicating what the next set of columns correspond to.


Any user data sent to Chameleon will be shown here

* This should match the ID you use to track users in your database or other analytics tools and sent as part of the Chameleon installation.

** Pacific Time would be -8.

*** Sessions are separated by 90 minutes of inactivity and the count begins after the Chameleon code snippet is installed.

Now that you know what you're looking at, here are a few things to keep in mind:

  • If a Step has a dismiss option, which is configured to show the Tour again later, it will not generate a Tour exited event.

  • This export does not contain detailed Step Seen event data (with information on all the Step configurations). However, this data can be sent to your connected integrations. To enable this for your account, please message us.

  • Content per cell is limited to 4096 characters (bytes)

  • Content that could be a function/formula in Excel are escaped with a leading single quote (i.e. '=cmdl' /C Notepad'!'A1')

Once you have your data at hand, you can use it to conduct a range of analyses, to answer questions such as:

  • Which Step are users exiting the Tour the most?

  • Which specific uses have seen a particular Step?

  • Which specific users have completed or dismissed the Tour?

  • Tour success by user property (such as language or a custom property).

  • How long it took a particular user to complete a Tour.

To do this, we recommend creating a Pivot table from all the data and then selecting the most relevant data to plot and compare.

Pivot tables allow you to easily group, filter, and chart a large table of data. In the pivot table, you can decide which columns from the original data to show on each axis and add further filters. You can create pivot tables in MS Excel or Google Sheets.

For example, here's how you can recreate the funnel chart we show in the Dashboard πŸ‘‡

Steps to create a Funnel Chart in Google Sheets

  1. Export data from Chameleon to Sheets

  2. Filter and remove any unwanted data rows

  3. Create a Pivot table

  4. Add the appropriate Pivot table settings

    • Rows - Event UID

      • Order by Descending

      • Sort by COUNTA of Event UID

      • Step seen*

    • Columns - Event

      • Order by Descending

      • Sort by Event

    • Values - Event UID

      • Summarize by COUNTA

      • Show as Default

    • Filters - Event

      • Status β€œStep seen”

      • * Go back to "Rows" and add the "Step seen" there

  5. Optional, copy and paste Step text to replace Step UIDs

  6. Create bar graph

It's important that users engage with Your Experiences, but to truly measure how your guidance impacts your adoptions is to look at whether users act on what they see in your Experiences.

With Tours, you can leverage your product events to understand how your Experiences drive your users to success. Goals can either be defined from within Chameleon (as a page load or click) or taken from any of the events you send to Chameleon (via our integrations or our API).

πŸ“© This feature is only available in the Growth or Enterprise Plan. To learn more or upgrade your plan, please contact us.

Once you understand how users are engaging with your Experiences, it's time you connect this data with your product events. We highly encourage you to use a specialist analytics provider to analyze your product data. Because your most important product events are unique to your brand and goals, you're the best to establish what success means to you.

We integrate with common providers which you can use to track your native product events alongside Chameleon events. This way, you can holistically evaluate the impact of your Experiences on other user actions, and understand how you can improve your process.

πŸ’‘ We recommend you consider using Segment or Freshpaint to streamline your analytics tracking and enjoy greater control of your data pipeline.

You can learn more about how Chameleon works with these tools, from our user guides:

You can also add the data that Chameleon automatically collects directly into your database and then query this data alongside all your other product data.Β 

To do this, simply use our open API to send Chameleon data to your database or other tools.

Find out more

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