The Mobile eCommerce Optimization Initiative is an ongoing study involving leading Magento System Integrators and an ever-growing number of merchants. If you join us, we’ll help you grow checkout revenue through standardized and continuous experience optimization and shared insights.


Experimentation Templates built on the basis of the best practices and framework that leads to a high probability of success and involves cross-merchant data sharing

Provided by System Integrators who are analyzing checkout metrics, selecting merchant specific experiments, interpreting results, and recommending next steps

Collaboration and Innovation of better methods through the ability to roll up anonymized data and to compare merchant specific results against industry-wide metrics


Optimization of the checkout funnel is a highly complex and technical task that requires the use of advanced data analytics and smart optimization algorithms.


Standardized Experiments

Magento platform-specific optimization templates were built on the foundation of recommended best practices, simplifying experiment setup and enabling cross-merchant data roll-ups.

Parallel Experiments

This initiative allows for many experiments running parallel to broaden the scope of the data and uncover the best ensembles, which are groups of treatments that play well together.

Adaptive Algorithms

Self-learning algorithms minimize the risk of experimentation through dynamic allocation of more traffic to winning treatments in real time.

Embedded Analytics

Optimization experiment-specific tracking of rich activity data is pre-embedded on the Magento platform, enabling analysis across a wide range of visitor attributes without the need for tagging.

Cross-Merchant Insights

The use of standardized experiment templates enables roll-out of data at both the micro and macro levels — from individual participant results to industry-wide metrics.


Anonymized Data

Participants in the community initiative will mutually share the anonymized data to learn from comparisons between their own results and industry averages.

Average Metrics

Multi-merchant averages are useful as a general trend but dangerous if considered as guarantee that an experiment will win or lose on a specific merchant site.

Results Distributions

Every merchant has unique attributes. In actioning shared insights, merchants should pay close attention to the spread of results achieved by other participants.