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Searchspring Launches Personalized Recommendations for Ecommerce

Searchspring delivers 1:1 personalization for ecommerce merchants in its new Personalized Recommendations.

Searchspring today announced the beta launch of its new Personalized Recommendations feature. Early adopters are already trialing new Personalized Recommendations to display hyper-relevant products that engage shoppers and boost conversions.

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“Searchspring’s vision for personalization is to equip merchandisers with the most productive combination of AI and human creativity”

With ecommerce experiencing accelerated growth during the pandemic, this release comes at a time when online retailers are looking for automation to enhance their overburdened merchandising team’s capabilities, without massive investment.

“Searchspring’s vision for personalization is to equip merchandisers with the most productive combination of AI and human creativity,” said CEO, Peter Messana. “With personalized recommendations, merchandisers can tailor their site to the individual shopper at a scale that wouldn’t be possible without this technology, while still retaining complete control over their online store.”

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Without relying on developers, ecommerce merchandising teams using Searchspring’s Personalized Recommendations will gain deep insight into behavioral data and automatically curate product recommendations site-wide. AI models learn from shopper history, real-time behavior, and preferences to:

  • Personalize product recommendations: Display top items for each shopper, curated based on purchase and browsing behavior.
  • Drive cross-sell and upsell: Recommend complementary items to the product being viewed, or suggest similar results with a higher price point.
  • Activate return purchases: Recommend recently viewed items, and items similar to recent purchases.
  • Curate high-performers: Boost trending products based on category or site-wide top sellers.
  • Control which products are displayed in the moment: Boost recommendations of preferred brands or product lines based on specific attributes.

Merchandisers are able to analyze the business impact of their recommendations with powerful product performance and shopper insights, revealing segments of customers who are most likely to respond to retargeting.

This release comes as a result of the company’s recent acquisition of 4-Tell and its AI-driven personalization engine. It is the first in a series of updates that will deploy personalization functionality across its entire search and merchandising suite.

“Borsheims has used Searchspring’s search and merchandising, and 4-Tell’s personalized product recommendations for a number of years. Shoppers that engage with our current recommendations are four times more likely to convert, with a 35% higher AOV, so we’re excited for the enhanced personalization that 4-Tell’s engine will bring to Searchspring’s solutions,” said Andrew Brabec, Director of Marketing & Ecommerce, Borsheims.

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