CASE Study

AI Predictive Segmentation drives a 29% uplift in CVR for a Global Beauty Leader

+29%
CVR Uplift
+27%
Sales Velocity Uplift
+35%
Engagement Uplift
+29%
CVR Uplift
+27%
Sales Velocity Uplift
+35%
Engagement Uplift
+29%
CVR Uplift
+27%
Sales Velocity Uplift
+35%
Engagement Uplift
+29%
CVR Uplift
+27%
Sales Velocity Uplift
+35%
Engagement Uplift
+29%
CVR Uplift
+27%
Sales Velocity Uplift
+35%
Engagement Uplift

The Challenge

The Challenge

A global premium skincare enterprise brand sought a solution to address all of their visitors (including the anonymous, and not only those who have signed-in), while pushing them into the proper optimization funnel relative to their level of intent: low intent will be redirected to brand awareness and high intent to conversion optimization.

They had only been able to identify and address 2.4% of their web visitors, lacking an effective method of engaging with the 97.6% of website visitors who remained anonymous. Additionally, their reliance on cookie based solutions, standard segmentation and signed-in users failed to provide the desired results. A viable solution that addresses each website visitor within their first session was needed, without compromising privacy, and without the need to replatform, or replace the existing solutions that are in use.

Kahoona’s Innovative Solution

Kahoona’s AI-powered predictive segmentation enabled the prediction of each visitor's probability of purchasing (PoP) in real time. By leveraging Kahoona’s unique data modality and advanced behavioral analysis, they could dynamically tailor the user experience based on individual visitor intent levels — without the need for extensive historical data or invasive tracking. This immediate understanding of user behavior allowed for the delivery of hyper-personalized experiences that resonated with both high and low intent visitors.

Activation Strategy

Refine the Proposition per each Target Customer Persona

Curate a deep analysis of opportunities to improve customer experience per customer persona, leveraging the deep & comprehensive customer profile formed by Kahoona for each website visitor (including intent level, AOV, Pricing Group, Category Intent, Attitudinal Behavior, and much more).

1

Dynamic Funnel Personalization

  • High PoP Users: For visitors with a high likelihood of purchasing, they implemented personalized calls to action, exclusive offers, expedited checkout processes and more. These activations successfully expedited their journey through the conversion funnel, encouraging immediate purchases.

  • Low PoP Users: To engage visitors with a lower probability of purchase, the emphasis focused on building brand affinity. They showcased compelling content such as skincare tips, product benefits, and stories that aligned with their values, to nurture long-term interest towards eventual conversion.

2

Performance Validation per Customer Persona

To validate the effectiveness of Kahoona's predictive segmentation, rigorous A/B testing was conducted. One group experienced the optimized journey tailored by PoP segmentation, while the control group continued with the standard site experience. It then ran per customer persona (low-intent, and high-intent) separately.

3

bottom line

The Results

Kahoona demonstrated the power of AI predictive segmentation in enhancing the customer experience, covering both high and low levels of intent:

+29% CVR Uplift for High-Intent

High PoP users experienced a 29% uplift in conversion rates compared to the control group, demonstrating the effectiveness of Kahoona's predictive segmentation targeted conversion prompt.

+27% Accelerated Sales Velocity

The average time to purchase for high PoP users was reduced by 27%, underscoring the effectiveness of targeted funnel optimizations in accelerating the decision-making process.

+35% Enhanced Engagement

 Low PoP visitors demonstrated a 35% boost in engagement metrics such as CTR, Page Views, Session Duration and BLS score, suggesting that awareness-focused content successfully fostered interest and deeper brand connections.

Conclusion

By partnering with Kahoona, there was a significant improvement in their ability to cater to both high and low intent visitors.

The case demonstrates how a strategic focus on real-time, predictive intent segmentation can drive better business outcomes and significantly increase LTV—enhancing conversions among ready-to-buy visitors and building awareness among those still in the exploration phase.

This approach not only empowered the ability to maximize the value of each visitor interaction but also set a new standard in hyper-personalized, intent-based customer experiences in the beauty industry.

Ready to embrace this cutting-edge technology?

Book a meeting with one of Kahoona’s experts!

Schedule a meeting