InSparq Trending Product Engine Boosts Sales 7.8%

Social merchandise recommendation engine inSparq has driven a 7.8% lift in online sales for online apparel retailer
The platform enables retailers to showcase trending products to all web site visitors, including those without a past purchase or browse history. The engine is designed to differentiate from traditional recommendation engines such as Amazon that are catered more toward repeat customers.

“With up to 80% of customers being new or infrequent shoppers, most online retailers do not benefit from traditional recommendations,” said Eli Katz, CEO of The EMob. “There is not enough data on the customer’s wants and needs.” 

To branch out beyond repeat customers, inSparq leverages social data and a proprietary trending algorithm that has been built and refined over the last two years.
“Combining social data with purchase data for recommendations creates a perfect balance — shoppers can easily find ‘what’s hot’ and gain social validation for their purchase decisions,” said Veronika Sonsev, CEO of inSparq.  “People tend to share aspirational products, while purchasing products they ‘need.’ 
When a retailer showcases these aspirational products shared on social media, other shoppers engage and buy more of these products, thus increasing sales through lift in conversion rate and average order value. This is because aspirational content inspires customers to buy things they didn’t know they wanted.”



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