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DataWeave unveils counterfeit products detection solution
30 Apr '18
2 min read
Courtesy: DataWeave
DataWeave, a competitive intelligence as a service provider for retailers and consumer brands, has announced the launch of its counterfeit products detection solution. The new detection solution will enable consumer brands to discover and curb the presence of counterfeit products on ecommerce websites using AI-powered image and text analytics.
Counterfeits are observed across several product categories in ecommerce, such as electronics, apparel, footwear, and furniture. While online retailers are torn between expanding their merchant ecosystem and enforcing merchant compliance, consumer brands feel compelled to track and report counterfeits themselves.
DataWeave’s unique approach, which leverages its proprietary data aggregation platform and robust deep-learning models, involves analysing the catalogue images and content of millions of products across diverse product types, enabling ecommerce executives and brand managers of consumer brands to detect counterfeit products at an accuracy of over 95 per cent. Fake products are identified by capturing minute discrepancies in catalogue images and content, while unauthorised white labelling or image theft is spotted when the image of a product matches perfectly with the original brand’s, but other catalogue content details are dissimilar.
Karthik Bettadapura, co-founder and CEO at DataWeave said, “As online retailers and marketplaces aggressively add thousands of merchants on their platforms, unauthorised white labelling, listing fake products, and image theft have become persistent causes for concern. In addition to creating consumer dissonance, counterfeit products are often sold cheap, which erodes the price perception carefully cultivated by the original brand manufacturer.”
“Armed with relevant insights on counterfeit products, consumer brands can work with online retailers to crack down on defaulting merchants, protect their brand equity, and take appropriate measures to ensure only authentic products are sold online,” he added. (GK)
Counterfeits are observed across several product categories in ecommerce, such as electronics, apparel, footwear, and furniture. While online retailers are torn between expanding their merchant ecosystem and enforcing merchant compliance, consumer brands feel compelled to track and report counterfeits themselves.
DataWeave’s unique approach, which leverages its proprietary data aggregation platform and robust deep-learning models, involves analysing the catalogue images and content of millions of products across diverse product types, enabling ecommerce executives and brand managers of consumer brands to detect counterfeit products at an accuracy of over 95 per cent. Fake products are identified by capturing minute discrepancies in catalogue images and content, while unauthorised white labelling or image theft is spotted when the image of a product matches perfectly with the original brand’s, but other catalogue content details are dissimilar.
Karthik Bettadapura, co-founder and CEO at DataWeave said, “As online retailers and marketplaces aggressively add thousands of merchants on their platforms, unauthorised white labelling, listing fake products, and image theft have become persistent causes for concern. In addition to creating consumer dissonance, counterfeit products are often sold cheap, which erodes the price perception carefully cultivated by the original brand manufacturer.”
“Armed with relevant insights on counterfeit products, consumer brands can work with online retailers to crack down on defaulting merchants, protect their brand equity, and take appropriate measures to ensure only authentic products are sold online,” he added. (GK)
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