fligoo is a gift suggestion platform that uses a unique algorithm to analyze social media data to provide customized gift recommendations from the best online stores, such as Amazon, Barnes & Noble, Urban Outfitters, Uncommon Goods, and more.
fligoo identifies and interprets activity and interests on Facebook, and translates that data into accurate gift recommendations and gift ideas for friends or the person shopping.
fligoo not only analyzes the interests people show and share on social networks, but it also analyzes every interaction users have on the platform, which provides fligoo with a profile of the person. This profile is a combination of more than 50 personalities, and fligoo determines how much of each personality the person has. We choose the top five personalities and provide recommendations based on these top personalities. For example, a person could be 23 percent ‘Geek,’ 17 percent ‘Sports Fan,’ 30 percent ‘Trendsetter,’ 12 percent ‘Music Lover,’ and 18 percent ‘Hipster.’
The idea of fligoo came from a situation that Juan Cruz, fligoo’s CFO, was stuck in. It was his mother-in-law’s birthday, and he couldn’t find her a gift that she liked. We began to create a solution to this problem—not knowing what to give as a gift. As young entrepreneurs, this is the first startup we have all been involved with.
Our gift suggestions platform is currently a web application that allows Facebook users in Argentina and the United States to login and find gifts from top retailers. fligoo is marketed through the Facebook App Center, Google Chrome Store, and we plan to have a mobile app launched at the beginning of next year to expand our reach and make finding the perfect gift even easier. With a strong presence in the United States, we will continue to add partnerships with the best retailers to expand the gift options on the platform.
The $60 billion gift return market is a big opportunity for retailers. As consumers turn increasingly to ecommerce shopping over in-store purchases, we feel no one has created a site quite like this. fligoo can help anyone with Facebook to connect and select the best possible gifts for friends and loved ones.
The main difference between fligoo and other gift recommendation engines is that fligoo’s algorithm has three main parts—physics, statistics, and consumer behavior. In this last component lies fligoo’s competitive advantage. fligoo does not do literal iterations from ‘likes’ as many of the other gift recommendation websites do. Instead, fligoo does a complete analysis of peoples’ interactions on social networks, our algorithm determines a specific profile this person has, and then makes the most accurate gift recommendation according to this profile.
fligoo established a base of more than 7,500 users in the first month, with an average of $10 per transaction per user. As we continue to ramp-up partners and general awareness, particularly in the all-important holiday retail season, we are aiming to increase our user base to 100,000 by February. We believe the secret to our success is our approach to solving the entire problem when it comes to finding the perfect gift, in a new way that no other company is doing.
Currently, fligoo collects a fee from its retail partners, depending on products sold through them. As the site grows, we intend to renegotiate our partnerships into bigger revenue-sharing agreements. fligoo also plans to collect revenue from retailers for access to a forthcoming reporting tool that will show them details about their products and shoppers, such as which items have the most Facebook Likes or are most-added to wish lists.
We are currently spreading the word about fligoo in the U.S. market. Part of our team has made the move to the U.S. and our goal in the coming months is to continue expanding the fligoo platform and gain brand recognition so we can launch new features on the site with success. We are in the process of raising $500,000 over the next eight-to-ten months. Half of that amount has already been committed.
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Headquarters: Palo Alto
Investors: NXTP Labs (Seed funding: $250,000)
Year Founded: 2011