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Using A/B Tests to measure efficacy
Using A/B Tests to measure efficacy

Use Control Group or Multivariate A/B testing for Tours to experiment and measure impact

Chameleon Team avatar
Written by Chameleon Team
Updated over a week ago

A/B Tests are a great way to accurately measure the impact of your adoption efforts with Chameleon. You can create and compare different versions of the same Experience and decide which is more impactful for your goals.

From the Dashboard, you can run a Control Group (Chameleon vs. nothing) or A/B Test (different variations of the same Tours). But you can also test the other Experiences, manually. We recommend starting with a Control Group test and iterating until your Experience is effective before testing Experience variations.Β 

Explore an interactive demo for A/B Testing πŸ§ͺ

Availability & Usage

πŸ” A/B Testing available for Growth & Enterprise

πŸ“ Ready to power your Tours (Tooltips, Microsurveys, Launchers)

πŸ“© Contact to discuss your plan needs

πŸ“ Available for Announcement & Banner Tours.

When creating your Tour you can choose to run a Control Test for your selected audience and exclude a percentage of users who should not see your Tour. This will enable you to assess the effectiveness of your Tour and understand how it impacts your users' goals.

Build your Tour as usual and go to the Testing panel in your Dashboard, to turn on Control Group testing. Next, set the proportion of users that should be part of the control group and decide when your experiment ends.

β„Ή With custom events, you can also pick the Auto finish option and allow Chameleon to end your experiment once it's successful. Learn more about sending data to Chameleon.

πŸ‘‰ For Tours with multiple variants, you can also pick the variant that should be displayed to your users, from the same Testing panel.

Every user identified by Chameleon is automatically assigned a random number (Testing ID property) with a value between 0 and 100. This value is persistent for each user and can be leveraged for targeting and experimentation.

To select a control group, Chameleon randomly chooses a number between 0-100 as the start of the range for the group. The size of the group will determine the end range for the group (including going back to 0 after 100.) The corresponding users within this range will form the group.

E.g. if you choose a 20% control group for a Tour, the Testing IDs for the group could be 87.3 to 7.3. If you do this for another Tour, the group may be 12.9-32.9.

β„Ή If you later increase the size of the control group, then the range is simply increased, from the same starting value.

See in your Dashboard the results of all Experiments on any of the Tours you test. You can change your Tour Goal after you start an Experiment, and Chameleon will simply start a different Experiment for you to keep the results clear.

β„Ή Users who start a Test Group might not always meet the goal of your Tour. In your Experiment results you can see different numbers between users who 'Started' a Tour and the 'Goal completed' stat, as users can start Tours but not perform the events you set as Goals.

An event will be logged whenever a user is first identified to be within the Target Audience and is liable to see this Tour. This event* -- "Chameleon Experiment entered" -- will be available within all your connected analytics integrations.

Within Mixpanel, the event name is "Experiment Started" to better match Mixpanel's experimentation analysis framework. πŸ‘‰ See our integration guide to how to identify different Tour Variants in Mixpanel.

*This event does not take into account URL Rules or other conditions for the Experience, only when a user first matches the user Segment's conditions.

For this event, the following properties will also be logged:

  • GroupΒ 

  • Testing ID

  • Tour name

  • Page URL

The "Group" property values are either:

  • Control (Out) -- user is part of the control group and will not see the Tour

  • Test (In) -- user is part of the test group and can see the Tour

Other events (e.g. "Tour started") will also be logged as normal once a user starts interacting with your Tour. You will see all these within your analytics platform (e.g. Amplitude, Heap, Mixpanel, Google Analytics) and can use this to further analyze the conversion or relative impact of your Chameleon experiment.Β 

πŸ” Available for Growth & Enterprise plans

πŸ“ Ready to use with Announcement & Banner Tours.

You can also perform multi-variate testing on your Tours and show different versions to users to determine which version performs better.

Build your Tour as usual, and from the Dashboard's Build Steps panel, click the 'Create variant' button. Chameleon will duplicate your existing Tour and you'll be able to adjust each variant further.

With each variant, you'll be able to edit the Steps and all configurations as usual, including reordering, or deleting Steps in the Dashboard. In the Builder, you'll be able to switch between each variant from the top bar to make adjustments or preview how each displays.

β„Ή Chameleon labels your variants with A, B, C, D, etc., and adds individual colors to each variant so you can easily distinguish them. If you create a variant (B) delete it and then create another variant, it will be labeled (C).

You can also rename your Variants from the Dashboard by clicking the pencil button next to each name. This change will be reflected everywhere in the Dashboard, so you can track experiments easily.

β„Ή If you rename your Variants, the Chameleon label will pick up the first letter of the first word you use to help you identify them and track Variants easily. For now, on the Analytics page, in the Experiments dropdown, the same Variant name will be kept for different Experiments, but you will see the updated Variant names.

You can create variants with a different number of Steps and configurations. Once you have your content and style set for each variant, go to the Test panel in the Dashboard, to define your A/B test. You can:

  • set a percentage of users that should see each variant

  • pick how the experiment should end -- if auto (Chameleon stops the experiment) or manually finish (you stop the experiment)

Publish your Tour live next and in the Analytics tab, you'll see a section dedicated to your experiments where you can review how each variant is performing.

Here too, you can switch between different Experiments to review the results.

Review your results in the Dashboard and send them to any connected analytics integrations to better understand which is more successful and manages to drive users toward achieving their goals.

πŸ’‘ You can also use the Experience name to segregate the data, as each Chameleon event contains additional attributes, such as Experience name, User ID, URL, etc.

With each Experiment you start Chameleon will analyze how each variant is performing and will rate it with a 'Confidence score'. This takes into account how many users engaged with your Tour during your Experiment.

The 'Confidence score' is a good way to understand what you need to work on to improve either the quality of your experiment (e.g. audience size) or the configurations of your Tours (e.g. if not enough users complete the Tour or meet your goal)

You can also manually test different Experience variations. You'll have to define your Test Segments and assign them to the appropriate Experience version when creating your variations. Here's how to do it πŸ‘‡

To create a Test Group, simply add an extra "sampling filter" to your Segment that will select a random sample of users of the desired size.Β You can still target users based on other conditions, such as user properties, events, data sources, etc.Β 

To add the sampling filter:

  1. Select Default properties as the type of filter

  2. Select Testing ID in the next dropdown

  3. Use more than or less than to define the range of users

  4. Set the boundary number for this Testing ID value.

In the above example, users that have a Testing ID value between 50 and 100 would be targeted. This would constitute 50% of the users within the group defined by the other segment filters.Β 

To target 10% of users, you could use either:

  • Testing ID more than 90

  • Testing ID less than 10

You could also use multiple filters to target another 10% group (e.g. Testing ID more than 10, and Testing ID less than 20).

You can use the same filter configuration in another Segment (by re-creating the filter) to target the same user group. This enables you to run multiple A/B tests on the same user group.Β 

To test two variations of the same Experience:

  1. Create the control version of the Experience, including a Segment, using the sampling filter above.

  2. Duplicate the control Experience, update the Experience name (using the variant name/label), and then re-create the Segment. This time use the opposite sampling filter so that you're targeting the alternative user group.

  3. Set both Experiences live.

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