Catalina Debuts New Product Launch Pad

Shopper intelligence specialist Catalina has introduced a solution called Launch Pad, which uses the firm's proprietary big data - encompassing two years of shopper intelligence and purchase behavior - to help clients find the shoppers most likely to purchase their new product.

From its headquarters in St. Petersburg, FL, and operations in the US, Europe and Japan, Catalina offers access to a shopper history database used by CPG brands for timely targeting of consumers via mobile, online and in-store channels. The new Launch Pad solution delivers relevant marketing, ads and/or promotions to shoppers 'anytime and anywhere', to encourage trial and repeat purchase on all channels. Catalina says it can guarantee results on a massive scale across 85 million US households.

Launch Pad offers an outcome-based pricing model which enables customers to pre-determine the amount they want to spend to acquire a new buyer, a repeat buyer and/or sell a specific number of units. In addition, the Catalina Catalyst team uses Launch Pad to deliver shopper insight reports - Item Tracker to understand trial and repeat behavior; Source of Volume to identify where new consumers are sourced; and Brand Buyer Profiles to analyse specific new product buyers, their preferences, and what motivates them to buy.

Gregory Mann (pictured), President of Emerging Brands, comments: 'In a world where 30,000 new products hit the shelves each year and shoppers tend to buy the same 150 items repeatedly, the challenge for emerging brands is daunting. Historically, research shows that the cost of customer acquisition for consumer goods has been incredibly expensive - on average $22 per individual buyer. And it's long been a challenge to create the right marketing program that connects with shoppers who match a brand's core values at the right time and in the right place whether on mobile, in store, or online. Launch Pad does all that and more - and at a fraction of the cost - guaranteed'.

Web site: www.catalina.com .

All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.