New platform combines deep learning, image analysis, and a proprietary Purchase Path Neural Network to present you with products tailored to your personal style
MONTREAL, Canada – Thursday, Feb. 2, 2017 – Online shopping can be frustrating. Between the countless hours spent browsing through inventory and the annoyance of retailers recommending products you already purchased, the entire experience leaves you exhausted and often without a single item in your cart. Enter Propulse, a new e-commerce purchase prediction platform founded by a former Saks Fifth Avenue executive that launched today to provide retailers with the right sales tools to present customers with new items, not previously purchased ones.
Just as sales associates offer personalized shopping experiences designed around a client’s style, Propulse brings that experience online to retailers and presents shoppers with products tailored to what they want to buy next. This means no more ineffective “Because You Bought XYZ” or “Customers Who Bought This Item Also Bought That Item” recommendations.
Without any personal data, Propulse uses artificial intelligence, machine learning and image analysis technology to recreate the offline shopping experience online. Features include:
Adapting to Consumers Shopping Behavior: Propulse recommends products using its proprietary deep learning, image recognition engine called the “Purchase Path Neural Network”. This new algorithm recreates the offline shopping experience online and adapts to consumer preferences over time–helping fuel personalization and product discovery for shoppers.
Machine Learning Determines What You’ll Purchase Next: Current machine learning can’t account for nuances in personal taste. But Propulse analyzes thousands of variables simultaneously for each product image to determine what the shopper is looking for at the moment, as well as offering products they’ll want to purchase after.
Enhances Buying Effectiveness with Shadow Inventory Analysis: If a customer is recommended an item while shopping online but the product is not available based on inventory, Propulse logs this interaction between customer and product in its “Shadow Inventory” and feeds that intelligence to retailers helping them understand what they should buy and to reduce retail markdowns.
“When you look at companies currently trying to customize online shopping experiences, you can’t help but notice a massive gap has emerged between ‘personalization’ and ‘recommendation,’” said Eric Brassard, CEO of Propulse. “Recommendation tools today fall flat because it’s not a true reflection of consumer shopping habits. With Propulse, we’re providing retailers with a new, multi-level approach to personalization. We developed a Purchase Path Neural Network that truly recreates the in-store shopping experience online.”
Propulse meets the demands of a changing customer. It’s no secret that e-commerce expectations have shifted drastically in the last year as today’s shoppers crave a highly personalized experience that mimics offline shopping. In fact, consumers have become re-attracted to the physical shopping experience–a recent poll by Adweek found 87 percent of shoppers say their in-store purchase decisions are influenced by store associates. In contrast, more than half of shoppers feel that similar service is lacking online.
"Frank + Oak has always been about offering an incomparable level of experience to its customer base through personalization and innovation,” says Ethan Song, CEO and co-founder at Frank + Oak. "With Propulse, we're able to complement our democratized current personal stylist offer by showcasing new items to our customers that pair well with existing ones they selected - That’s what keeps them coming back for more and deepens our relationship with our community."
To learn more about Propulse and how they’re ushering in personalization to online shopping, visit www.propulseanalytics.com/en/.
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