Author: Laura Wishingrad

Picture of Laura Wishingrad

Laura Wishingrad

Laura Wishingrad specializes in ecommerce personalization, customer data platforms (CDP), and omnichannel customer engagement strategies. Her expertise includes personalized product recommendations, algorithmic decisioning, conversational AI, analytics instrumentation, and UX-driven product design focused on helping enterprise retailers deliver more relevant shopping experiences. She focuses on building personalization strategies that align customer experience, data, and business outcomes across digital commerce channels. Laura writes about ecommerce personalization, recommendation engines, customer engagement, conversational AI, and digital experience optimization.

Laura Wishingrad
Laura Wishingrad specializes in ecommerce personalization, customer data platforms (CDP), and omnichannel customer engagement strategies. Her expertise includes personalized product recommendations, algorithmic decisioning, conversational AI, analytics instrumentation, and UX-driven product design focused on helping enterprise retailers deliver more relevant shopping experiences. She focuses on building personalization strategies that align customer experience, data, and business outcomes across digital commerce channels. Laura writes about ecommerce personalization, recommendation engines, customer engagement, conversational AI, and digital experience optimization.

Yellow gradient background designDigital Experience Personalization

How Optimization Managers Can Harness ‘User Affinity Sorting’ to Fine-tune Their eCommerce Personalization Strategies

Recommend™, Algonomy’s personalized product recommendation platform, offers optimization managers a way to test how different affinity-based personalization strategies influence how shoppers interact with product recommendations.
Recent Posts
Resources

Guides

Dynamic Content Personalization: How Active Content Brings Dynamism into Your Campaigns

Let’s face it—customers nowadays expect deeper and relevant communication, not cookie-cutter-styled messaging across every channel.

Case Study

Personalizing Beauty at Scale: How Matas Grew Attributable Sales by 36% with Personalized Recommendations

Deliver a best-in-class customer experience, increase online sales, and drive operational efficiency at scale

Get Recording Now