In the traditional business-to-business world, sellers don’t know how much product to order. Even in well-managed companies, 20% to 30% of inventory is either dead (not selling) or obsolete, according to one source. The impact on profitability can be severe. Sellers and manufacturers of dead stock can charge up to 11% of their revenue, reports Katana, which makes raw materials and materials tracking software.
Wanting to give sellers more visibility into product demand, so they can make informed decisions, Ella Zhang co-founded Trendsy, which connects sellers with suppliers in the back-end supply chain for a customer base. Trendsi closed a $25 million Series A round that brought its total capital to $30 million after the pandemic saw many retailers turn to retail, a key risk-reducing option, instead of buying inventory.
Lightspeed Venture Partners Basis Seth Ventures, Footwork VC, Peterson Ventures, Sierra Ventures, Liquid 2 Ventures and individual investors, Zoom CEO Eric Yuan and Zola CEO Shan-Lin Ma participated. The new cash will be used for investments in data infrastructure, supply chain technology, new product categories and international expansion, Zhang told TechCrunch.
“We’re building a new platform that lowers the barriers for anyone to start selling online or offline,” Zhang told TechCrunch in an email interview. “With Trendsi…influencers, creators and others can sell through social media without worrying about sourcing products, managing warehouses, packaging and shipping, etc., so they can focus on the brand they love and their customers.”
Image Credits: trendsy
Zhang comes from the venture world, serving as an investment director at Kleiner Perkins at Google, Tencent and Binance (where she founded its startup investment arm, Binance Labs). Zhang met Trendsi’s co-founder Sherwin Xia while in graduate school at Stanford, and the two participated in Stanford’s Startup Garage Incubator. Xia was one of the first employees at e-scooter startup Lime and previously worked as an analyst at a16z (Andresen Horowitz).
Zhang, Xia and Trendsi’s third co-founder, Maddie Davidson, sought out with Trendsi to build a service that applies AI and machine learning to streamline tasks like inventory and sales forecasting. Using data collected across the platform and from third parties, Trendsy attempts to predict sales down to the SKU level, allowing sellers to reduce overstock and prevent out-of-stock issues. Beyond this, the platform taps into sales and behavioral data to rate products and recommend them to sellers.
Recently, Trendsi launched a feature called “just-in-time” manufacturing that aims to help manufacturers find products faster based on real-time sales data and forecasts. “[This] “By building our production and sales forecasting models and providing the shipping service, it allows retailers to take only the minimum and take no risk,” Zhang explained. “The initial risk of purchasing inventory is now shared between the retailers, the Trendsy platform and the manufacturers.”
Despite competition from inventory optimization startups like Flibber, SyrupTech, and BlackCrow AI, business has remained strong in the two years since TrendC was founded, Zhang says, with new users growing 10x year-over-year. (She declined to provide figures.) Next year, the company plans to expand its work with retailers and manufacturers in industries with strong upward momentum.
“For both our suppliers and retailers, especially in fast fashion, excess stock means locked-up capital, wasted storage space, increased inventory costs and unnecessary losses,” Zhang said. “This outbreak has shown the true costs associated with inventory management. So Trendsy really got attention.
San Francisco-based Trendsi currently has 105 full-time employees and expects to hire 15 more by the end of the year.
Not all retailers are getting on the AI train. Half of respondents to the KPMG survey cited cyber security breaches and potential biases as major threats to the technology, while 75% believe AI is “more hype than reality.”
But broadly speaking, AI in retail is a growing category, with most retailers surveyed saying their employees are ready — and have the skills — for AI adoption. Retail leaders expect AI to have the biggest impact on customer data, inventory management and chatbots for customer service, creating a virtuous adoption-investment cycle in the coming years.
