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Constructor Unveils AI-Based ‘Attribute Enrichment’ to Optimize Product Discovery and Result Relevance Across the Buyer Journey

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Constructor, the leading AI-powered product discovery and search platform for enterprise ecommerce companies, today announced Attribute Enrichment, a solution that improves online product catalog quality using deep learning and machine vision, both forms of AI. Attribute Enrichment combines raw product catalog data with buyers’ behavioral clickstream data across touchpoints — correcting and auto-enriching product attributes to help buyers discover the items they’ll find most attractive, while improving personalization across their customer journey.

Attribute Enrichment addresses one of the most common pain points today among both ecommerce companies and their consumers. For ecommerce companies, needing to work around bad or missing product data is a problem as old as ecommerce itself, with site merchants either forgoing that data altogether or needing to rely on poorly tagged data from third parties. For B2C shoppers and B2B buyers, this leads to time-consuming and frustrating product discovery and search experiences. For instance, less than 3 in 10 buyers say their product-finding experiences are “quick,” and 62% will leave an ecommerce site if they can’t find what they’re looking for.

Ecommerce companies seek to remove this friction and provide visitors with highly contextual, hyper-relevant experiences that increase engagement and conversions. Consistent, comprehensive, well-categorized product data helps power these experiences… but getting it is often easier said than done. Relying on vendor attributes — the product information and categorization from third-party suppliers — is a gamble that often leaves “holes” hindering product discovery and personalization. And do-it-yourself efforts among ecommerce teams — including manual enrichment, categorization, retagging and harmonizing third-party data into a consistent catalog — is time-intensive and can be error-prone.

How it works
Constructor’s Attribute Enrichment uses deep learning techniques: that is, training AI models to identify products, categorize them and generate new product attributes to enrich product data and increase discoverability. The newly enriched data is delivered straight to ecommerce companies’ websites, without any effort on their behalf — giving visitors immediate access to better and more complete product information that drives purchases.

Attribute Enrichment provides ecommerce companies — including B2C retailers, D2C brands, distributors, manufacturers, wholesalers and other B2B organizations — with:

Benefits of Attribute Enrichment
By incorporating Attribute Enrichment into their product discovery strategies, ecommerce companies can:

“Constructor helps ecommerce companies turn their websites and apps into personal shopping assistants, and our new Attribute Enrichment solution is an important part of this,” said Eli Finkelshteyn, CEO, Constructor. “For too long, an excuse among search and discovery vendors for bad results was that the data they were given was bad. Attribute Enrichment aims to take away that excuse. We want to guarantee we’ll give the most compelling results to our customers and their shoppers, even in cases where their product catalogs aren’t perfect. Our goal is to not give excuses for poor results, but to give solutions. And Attribute Enrichment is just that.

“Using modern data science methods like machine vision, mixed with customer feedback via clickstream and behavioral data, we’re able to generate and auto-enrich product attributes, categories and metadata, all at the speed of AI. It’s a win-win for both buyers and ecommerce companies alike: fueling the best product discovery experiences for buyers, while driving sales and giving ecommerce teams time back in their days to focus on strategic initiatives.”

SOURCE: PRNewswire

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