Amazon netted $29 billion from retail media advertising last year, and their ad business is deeply embedded within native product discovery, placing Particular Audience in an attractive position to service the rest of the online retail market, offering up a share of the rapidly growing retail media pie.
Founder and CEO James Taylor said that with the growth of eCommerce, people have more options.
“If you have a million customers with unique intent, tastes and preferences, then you need a million versions of your website, however subtle, to make shopping experiences as relevant and convenient as possible. Our platform makes this easy.” So easy that Particular Audience is approaching $100m in gross merchandise value run rate, 19x growth in the last 2 years.
Within PA’s platform, retailers receive extensive inventory analytics, and can expose this to vendors, predicting demand and manage supply chains. Merchants can optimize inventory by promoting high margin or overstocked items within relevant journeys, maximising margins, increasing cash on hand and most importantly: reducing waste.
Users of PA’s platform get to tap into insights from PA’s consumer product, similarinc.com, providing internet scale visibility on what items are trending, in what regions, and how competitors are pricing to market. Similarinc.com’s eCommerce data network effect helps Particular Audience’s clients compete on price automatically and predict demand using data far larger than they have access to within their own business.
Less waste and lower costs mean better prices for the consumer.
Similarinc.com, a browser plugin, is an online community of shoppers and retailers contributing 100% anonymous real-time search, product price and availability data to help one another find the best prices in the fastest time possible. It is a data community making online navigation easier, similar to what Waze does for its users in the real world.
With one of the richest real-time shopping data sets in the world, Particular Audience saves online shoppers and merchants time and money, accurately predicting demand from over 1 billion first-party data points on its retail-focused machine learning platform. Every data point is 100% anonymous and cookie-free, positioning the company well ahead of privacy first trends and the coming deprecation of third party cookies.