Uni: A/B Price Testing & CRO

Develop by The UniCorner

Free plan available

Optimize profits with UniAB's dynamic A/B price testing and analytics.

Profit optimization

Analytics insights

Dynamic price testing

Split testing products

Maximize conversion rates

Specific group targeting

About Uni: A/B Price Testing & CRO

Launched May 22, 2025

Built by The UniCorner

Unlock Deals 20% off

BON Loyalty Rewards Program

(1,475 Reviews)

Unlock Deals 20% off

Sponsored

Loyalty rewards program with points, POS, referrals &...

Description

Simply run unlimited AB price test to maximize your profit. Find the sweetspot price by a/b testing

Elevate your store's profit and conversion rate with UniAB. Split price testing in any products to find the sweetspot price. Gain insights of a/b testing campaign through Analytics to optimize performance. Convert ab testing to be your unique strategy to boost conversion rate and maximize profit!

A/B Price testing: Test with different price to maximize profit
Analytics: Monitor results with Visitors, Clicks, Orders, Revenue, AOV and more
AB Test for specific customer group: Country, Desktop, Mobile, UTM Source

Pros

Dynamic A/B testing for pricing allows for optimization of profits.
Comprehensive analytics for monitoring key performance indicators like Visitors, Clicks, Orders, Revenue, and AOV.
Ability to test different prices on specific customer groups such as by Country, Device, and UTM Source.
Helps in finding the optimal price point or 'sweet spot' for different products.
Contributes to boosting the store's conversion rate by informed decision-making.

Cons

The complexity of implementing and managing A/B tests may require a learning curve.
Potential for initial confusion or negative customer reactions due to varied pricing.
Heavy reliance on data analytics, which may require additional expertise or integration with existing systems.
May not accommodate all types of products or pricing strategies effectively.
Results can be influenced by external factors not accounted for in the A/B testing.