What integrations does Growth Suite have with Klaviyo for beauty brands?

A/B Testing Beauty Discount Campaigns

A/B testing is the only reliable way to move past discount intuition to actual evidence about what your specific audience responds to. Beauty customer behavior varies significantly by brand, product category, price point, and demographic - best practice for one brand may be wrong for yours. Systematic testing builds a proprietary knowledge advantage over competitors who rely on industry benchmarks alone.

Testing Priority Matrix

Statistical Validity Requirements

A valid A/B test requires: (1) Minimum 100 conversions per variant (not just exposures), (2) At least 2 weeks of runtime to account for day-of-week variation, (3) Statistical significance of 95%+ before declaring a winner, (4) A/B split by visitor (not by day or week) to control for temporal confounds.

Monitor secondary metrics beyond conversion rate: (1) Average order value per variant (a higher-converting offer might produce lower AOV), (2) Return rate (deep discounts may attract higher-return customers), (3) Repeat purchase rate within 90 days (discount-triggered customers may have different LTV).

Growth Suite A/B Testing

Growth Suite's A/B Testing Module within Trigger Campaigns enables split tests across all key variables - offer amount, timer duration, copy, and imagery - with automatic traffic splitting and built-in statistical significance reporting. Results are presented alongside revenue impact estimates, not just conversion rates, making the business case for each variant clear. Test one variable per campaign to maintain clean experimental conditions.