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eCommerce Solution Provider Constructor Launches AI Shopping Assistant

Constructor launched a generative artificial intelligence-powered AI Shopping Assistant (ASA) for use on eCommerce websites and mobile apps.

The new ASA helps shoppers discover and explore products while enabling eCommerce companies to boost engagement and conversions, the company said in a Friday (Jan. 12) press release.

“ASA makes suggestions based on detailed requests from a shopper — like a trusted, in-store associate would — while also instantly factoring in everything it knows about the shopper at hand,” Constructor CEO Eli Finkelshteyn said in the release.

While Constructor already offers product discovery solutions for shoppers who know what they want and just need to search for it, the company’s new ASA is designed for more complex cases, according to the release.

ASA enables shoppers to explain what they are looking for in natural language, like, “I need healthy items for a picnic” or “I want a trendy shirt to go out in,” Finkelshteyn said in the release.

Potential use cases for ASA include finding recipes and procuring their ingredients, finding occasion-appropriate apparel, and identifying relevant items across categories, per the release.

To answer a broad range of queries from shoppers, ASA features intent-based, natural language prompting that returns relevant suggestions and refines results, according to the release.

It also provides support for a variety of results, including product recommendations, guides and how-to instructions, the release said.

ASA also includes Constructor’s connected product discovery algorithms, so it can learn from every action in the consumer’s shopping journey and personalize the shopping experience, per the release.

“By applying AI to enable shoppers to search for products in new, flexible and interactive ways with ASA, eCommerce companies can better meet shoppers on the pathway to purchase and build brand affinity and loyalty,” the press release said.

By analyzing clickstream data and learning from customer behavior, AI can adapt and improve its search filters and results over time, Finkelshteyn told PYMNTS in an interview posted in July, discussing the company’s use of the technology in B2B applications.

“B2B has needed to put up with bad software for a long time, or one-size-fits-all software, that wasn’t really built for them,” Finkelshteyn said.

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