Quick Pitch: A shopping discovery engine built on the Twitter platform
Genius Idea: Although many retailers, brands and consumers share information about discounts and other offers on Twitter, it's not easy for shoppers to browse these deals in aggregate.
Tweetalicious, a six-person startup out of Pennsylvania, is aiming to address that very problem. The team has released a Twitter client for the web and iPhone devices [iTunes link] that surfaces deals shared on Twitter based on a users' preferences by category, such as apparel or home, and designer.
Users can give offers a thumbs up to help Tweetalicious better understand what they like, as well as save deals to a wishlist for later perusal. Deals are refreshed every few days to make sure they are up to date and relevant, says CMO Harrison Lee.
The client isn't robust enough for a heavy Twitter user, but it will serve the needs of casual users primarily interested in shopping, particularly as its algorithms are further refined. The company currently scrapes deals from Twitter and a handful of online retail partners, but is working with mall operators to facilitate offline shopping at the local level as well.
"We don't just want [Tweetalicious] to be a community of online shoppers," Lee says. "We also want to reach people who primarily shop within [their own] general vicinity."
Tweetalicious, which has not yet raised any funding to date, is currently focused on improving its existing product and growing its userbase. Soon, the startup hopes to incorporate deals pulled in from other social networks, including Facebook and LinkedIn, and to add verticals for users with interests outside of shopping.
An Android app is in the pipeline but no launch date has yet been set.
Series Supported by Microsoft BizSpark
