We built Pi because of the obvious drawbacks of most recommendation services. Basic recommendation engines require a whole lot of data about a customer in order to offer them worthwhile product suggestions that are geared towards conversion. And unless you're Amazon, it's hard to come by such data. In the absence of such in-depth data about shopper preferences, most mature recommendation engines have limited information such as age, geography, and gender. As a result, their product recommendations are far from exact and lead to low conversion rates.
Pi, on the other hand, removes any friction that exists in the path to purchase by showing shoppers the kind of products they are most likely to buy. A scalable personal assistant to every shopper on the site, it custom curates a personalized mix of outfits in the right sizes. What you get is a personalized shopping experience designed to mimic the attention and service you would get from a sales assistant at a store. Except, it's designed to know you even better.
We're all set to launch Pi on Indonesia's www.mapemall.com
. Watch this space for more.