More testing, less dev time: AMA scales experimentation with Kameleoon
Industry
Services
key features
Web Experimentation

30+
users from multiple teams rely on Kameleoon
+10%
conversion rate from a single test
1 platform
to run all web and mobile tests
Experimentation that delivers results
- More testing, minimal dev effort: AMA can experiment across web and mobile with less reliance on developers.
- Accurate, trusted data: With multiple statistical models and integrations with their analytics stack, AMA spends time discussing results instead of debating methodology.
- Refining designs through data: Experimentation revealed key design flaws while driving a 10% increase in conversion rate, helping AMA optimize with confidence.
Representing more than one million members, the Alberta Motor Association (AMA) is a trusted provider of roadside assistance, travel services, driver education, insurance, and many other services for the Canadian province of Alberta.
As they focused on growing membership and improving retention, they needed a way to scale experimentation without overburdening their developers.
AMA wanted a solution that could support testing across multiple touchpoints, allowing different teams to launch experiments independently and integrate with their existing tools to simplify workflows. Here’s how Kameleoon helped AMA achieve these goals.
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Scaling experimentation across web and mobile
One platform, built for all teams
Before Kameleoon, AMA’s experimentation efforts were limited to their website. When they started searching for a new testing tool in 2023, they knew they wanted a single solution that could support both web and mobile app testing without adding complexity.
With Kameleoon, they can now run all tests in a unified platform. The marketing team easily builds web tests using Kameleoon’s no-code graphic editor, while developers focus on feature experiments for their mobile app. With each team working independently, AMA has scaled its program while keeping developer workloads manageable.

More control over data analysis
Flexible statistical models
For AMA, making data-driven decisions means both running experiments and ensuring they’re analyzed correctly. They needed a platform that allowed flexibility in choosing the right statistical model for each test. With Kameleoon’s multi-stat engine, AMA can choose from CUPED, Sequential, Frequentist, and Bayesian methodologies, ensuring they get the most accurate and actionable insights.
Kameleoon integrated with the team’s existing tools
AMA tracks their full digital experience across various analytics platforms but they struggled to find a testing platform that integrated with their existing stack. Kameleoon’s integration capabilities have eliminated manual work and enabled real-time analysis, helping AMA evaluate test results efficiently.
Testing that impacts business outcomes
Higher conversions and better decisions
AMA set out to increase new memberships by optimizing the design of their membership comparison page. Using Kameleoon’s graphic editor, they launched a split test that led to a 10% improvement in conversion rate and validated the impact of their design changes.
In another test, AMA experimented with a new call-to-action (CTA) button to drive conversions. Surprisingly, the original CTA performed better. By testing first, they avoided rolling out an ineffective change, proving that experimentation is both about big wins and preventing costly missteps.
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Kameleoon and AMA: Experimentation that drives real impact
By giving AMA the right tools and the flexibility to use them effectively, Kameleoon has helped them build a testing program that delivers measurable results.
Key Kameleoon features used by AMA

AI Predictive Targeting

Prompt-Based Experimentation
Enhance all-team experimentation with Kameleoon’s new results page
"With Kameleoon, we’ve been able to run more tests without constant developer support. The graphic editor has been a game-changer for our marketing team, making it easy for us to launch new tests with confidence."




+10%
conversion rate from a single test
1
Experiment prevented an ineffective change
30+
Unique users across multiple teams
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