Adding the functionality of A/B testing capabilities for scheduled campaigns within Merchandising Cloud, Would allow merchants to create two versions of a merchandising strategy, such as different product pinning rules, merchandising rules, promo cards, or product recommendations and deliver them to separate audience segments or split website traffic (e.g. 50/50).
Performance could then be measured based on key metrics such as click-through rate, engagement, conversions, or revenue to identify the most effective experience.
The same functionality would also provide significant value for Product Recommendations.
Currently, merchants need to manually change recommendation types, wait for enough data to be collected, and compare analytics before deciding which strategy performs best.
Having a Built-in A/B testing would automate this process, making it much easier to identify the highest-performing recommendation engine and optimise the customer experience with confidence.
This enhancement would enable data-driven merchandising decisions, reduce manual effort, and help merchants continually improve conversion rates through experimentation.
