Suggestr
InactiveAmazon-level personalization for Shopify merchants
About
Suggestr is a self-serve, no-code personalization solution for the 20M+ e-commerce brands that sell on platforms like Shopify. Marketplaces like Amazon drive up to 30% of their sales from personalized surfaces (recommendations, bundles, frequently bought together, et cetera). They have large data science teams that build such in-house recommendation engines. However, DTC brands can't afford to do this, and they don't have enough customer data to make the conventional recommendation approaches work. Suggestr uses innovative multi-modal AI technology that sees and understands products (needs 100x less data), allowing it to work with brands of all sizes (SME, mid-market, enterprise). The solution takes less than 30 minutes to integrate and helps merchants increase online store revenues by up to 10% with AI-driven upsells and cross-sells.
Founders · 2
Aditya is a technologist that has built and sold recommender systems to banks. He has operational experience in e-commerce and knows the pain points of sellers first-hand. Before building Suggestr, he built a talent marketplace startup, where recommendations were used for talent matching.
Oleksii is an AI Researcher with 15 papers published in ML and AI and 900+ citations. He's a serial founder with two exits (Slise.xyz, and DiseCRM.com). He has been a part of the Vision & Language team at Facebook AI Research (USA), and the Experimental Psychology lab at the University of Oxford (UK), applying AI to the analysis of human behavior.
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