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Barilliance

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"AI-driven eCommerce personalization platform."

Case Study
Frequently Asked Questions
This company uses AI to tailor shopping experiences, recommend products, and send targeted emails. It helps online retailers turn visitors into buyers by personalizing their interactions and offers, reducing cart abandonment, and boosting customer loyalty.
Barilliance Stated Claims
These are public claims Blurbs AI believes to have been made by Barilliance.
AI driven personalization
Barilliance claims that they create personalized shopping experiences across the purchase journey using AI-powered, real-time personalization.
Omnichannel experience
Barilliance claims that they provide engaging, omnichannel experiences tailored for each shopper, personalizing shopping across the funnel.
Seamless integration
Barilliance claims that they offer a 5-minute setup integration with popular eCommerce platforms and seamless integration with email providers.
ECOMMERCE PERSONALIZATION
CART ABANDONMENT EMAILS
PERSONALIZED PRODUCT RECOMMENDATIONS
ONSITE PERSONALIZATION
LIVE NOTIFICATIONS
WORKS WITH SHOPIFY
SALESFORCE INTEGRATION
MARKETING AUTOMATION
CUSTOMER ENGAGEMENT TOOLS
BEHAVIORAL TARGETING
BlurbSTAR Case Study
Billabong & Barilliance
AI-driven recommendations improve Billabong's conversion rate and profits.
533%
Conversion Rate Lift from Product Recommendations
15.2%
Ecommerce Conversion Rates on Product Recommendations
This profile remains unclaimed. Blurbs can only offer a partial, unverified case study.
1.
Situation
Billabong's Personalization Challenge
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Global presence necessitated streamlined merchandising.
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Partnered with Barilliance for AI-driven personalization.
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Initial success led to broader implementation.
Billabong, an iconic swimwear brand with global reach, faced the challenge of effectively managing and optimizing its merchandising strategy across multiple assets and brands. With an extensive portfolio that includes DC Shoes, Roxy, and Quicksilver, it needed a robust personalization partner to handle this complexity. Billabong's objective was to enhance customer engagement, conversions, and revenues through a more targeted and personalized customer experience. In pursuit of this goal, they partnered with Barilliance, a technology provider specializing in AI-driven product recommendations. The initial implementation occurred across their US assets, where they began witnessing measurable improvements that motivated a wider rollout across other geographic and brand lines.
2.
Task
Optimization via AI Knowledge
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Implement AI-driven dynamic recommendations.
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Optimize logic based on customer journey context.
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Targeted offers for new and returning users.
Billabong sought to optimize the conversion rates across its online channels by utilizing Barilliance's AI capabilities. The task was to implement a recommendation logic that dynamically fits real-time customer interactions based on their journey stage and context. For example, Barilliance's system identifies if a customer is a new prospective buyer or a returning one, adjusting the recommendations accordingly. On the homepage, new visitors see top-selling products, while returning customers are presented with recommendations based on their previous interactions, such as past purchases or recently viewed items. This system adapts to customers' needs and browsing behavior, whether they're on the homepage, product pages, or cart pages, to maximize engagement and conversion rates.
3.
Action
Adapting and Leveraging Personalization
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Two recommendation widgets on product pages.
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Collaborative filtering in shopping cart.
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Personalization increases AOV and LTV.
Barilliance enabled Billabong to adapt their recommendations through strategic personalization features on various parts of the customer journey. On product pages, they implemented two personalized recommendation widgets. One suggests top-selling items within the same category, and another dynamically updates based on recently viewed products. In the shopping cart, collaborative filtering suggests complementary products based on current cart contents, aimed at increasing average order value, profits, and customer lifetime value. By allowing the recommendation engine to use in-session and aggregated purchase data, alongside static product data, Billabong improved their precision and effectiveness in cross-selling and upselling efforts.
4.
Result
Replication and Revenue Impact
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15.2% increase in conversion rates.
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533% uplift in recommendation conversions.
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Easily replicable campaigns enhance results.
The deployment of Barilliance's technology across Billabong and its sister brand's web assets resulted in significant conversion and revenue lifts. With a notable 15.2% increase in eCommerce conversion rates on product recommendations and a 533% lift in conversion rates, their strategy proved successful. The solution provided flexibility in managing campaigns across different geographic regions and brand assets, allowing for the easy duplication of successful personalization strategies without additional strain on IT resources. This adaptability resulted in increased engagement, improved ROI from marketing efforts, and ultimately, higher profits across the board.
Keywords
BILLABONG
BARILLIANCE
AI PRODUCT RECOMMENDATIONS
PERSONALIZATION STRATEGY
ECOMMERCE CONVERSIONS
CUSTOMER JOURNEY OPTIMIZATION
COLLABORATIVE FILTERING
CROSS-SELLING
UPSELLING
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