Jason Schwab doesn’t like to shop, yet he is the man behind MiAlio, a personalized, online shopping portal.
Schwab (left) created MiAlio to simplify the clutter of the online shopping process and bring products that specifically cater to what he likes and needs directly to him.
The site acts as a personalized shopping consultant, taking the experience of gathering the basic – “What are you looking for?” – combined with personality-related information to make suggestions for products that best serve the user.
“MiAlio becomes the ultimate browser’s dream,” Schwab said. “It’s a great way to shop based on who you are.”
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Close to five years ago, Schwab said, there was a different attitude about consumer behaviors. Today, because information sharing is more common, users are more willing to become interactive. Acting on this trend last fall, Schwab assembled a team of developers and investors, and the idea to create the customized shopping experience began to come to fruition.
From collectively forming the idea to designing and executing the concept, the folks at Web Pyro, an Ohio-based new media firm, assisted Schwab and developed the customized program to augment product data
Schwab said that oftentimes product searches and suggestions on the web are strictly based on previous online purchases and may have little relevance to what customers are truly looking for. MiAlio’s program puts more power in the hands of users to yield search results that relate to them.
MiAlio users complete free profiles based on ranked demographics that include information on eight key feelings of influence. Among these indicators are: interests in activities, the age you feel, family roles and buying habits. The profiles reflect who a user is as a shopper and, more importantly, as a person. “The profile is used to reflect layers of users’ personality,” which can be indicative of the products users will search for, Schwab said.
Based on similar qualities from their profiles, users are matched to other users in groups, or “gaggles.” Within gaggles, product suggestions can be made to each user based on trending purchases by other users. MiAlio assesses the gaggles daily, allowing for consistent behaviors in the gaggles to accurately display the products users could have potential interest in.
(Left: screenshot from mialio.com)
When shoppers sift through the list of suggested products, they choose to “like” or “next” products. The data from each user’s preference is collected and placed into a gaggle. The list of “liked” items can then either be purchased or sent to other users. In this way, the online shopping experience enters into a social dimension, Schwab said.
With its unique matching system of product and personality analysis, MiAlio functions as a “layer on top of e-commerce,” Schwab said. Through affiliated marketing, the company integrates its service with products listed on Amazon and endless. When users move to purchase an item, the site directs them to the affiliated site where the transaction can take place. As a third party in the purchase, MiAlio receives commission by directing traffic flow to each site.
Currently in public beta, MiAlio was first released to friends and family of the startup earlier this year. Before the site has its official launch, Schwab said it will undergo a series of updates and refinements. Schwab said he hopes to “ramp up product selection” as MiAlio grows and that he wants MiAlio to reach “across all product silos.” The startup’s strategy is to increase users and not only the amount of products but the quality of products. As the user number grows, the feedback on products hopes to narrow gaggles for more succinct browsing on the site. MiAlio also plans to focus efforts on user experience and to optimize more on mobile features.
For a video of Schwab presenting MiAlio, see our post: “Cornstalks Demo Night: MiAlio demo by Jason Schwab.”
Here’s a promotional video of MiAlio featured on its homepage:
