Mona, a new app from former Amazon.com employees launching now, wants to put a personal shopper on your phone. While many mobile shopping apps today work to provide users with recommendations on new products or highlight popular trends, Mona takes things a step further with a feature it calls “Missions.” This has it scouring online stores for products that meet a specific set of criteria, based on product type, style, price and more.
For example, you could ask Mona to tell you when a particular pair of shoes goes on sale, or when handbags from your favorite designer are available for under $200.
The Seattle-based, bootstrapped startup was founded last year by Orkun Atik, previously a senior Product Manager at Amazon; along with Nurettin Dag, also of Amazon, who worked as a Senior Software Development Engineer; and a third co-founder who prefers to stay anonymous. Atik in particular has experience with personalization technologies, having worked on various recommendation systems while at Amazon, including its Similarities system (e.g. “Customer Who Bought X Also Bought Y,” and “Frequently Bought Together”), among other things. Dag, meanwhile, worked on the logistics platform that powers Amazon’s same-day delivery services, as well as Amazon Fresh.
The idea for the app was largely prompted by Atik’s interest in working on data products. “I really like shopping, and thinking about all the dynamics in the marketplace and how consumer behavior is changing,” he says.
The founder explains there’s a lot of potential in developing a better product that’s more personalized to its end users, who have unique interests when it comes to their style, in addition to variances in the sizes of clothes they wear or different brand preferences. Plus, shopping search and discovery hasn’t changed much over the past 15 years, Atik says. “Everything is organized around products today, not people,” he adds. “Shopping should be organized around people and their existing missions.”
While Mona’s best feature is its ability to hunt down specific products and track your favorite items, the app will also surface the latest trends and deals, making it more of a general-purpose shopping app, rather than one you only use when you have a task in mind. Each day, the app suggests a “top 20” list of products, but these personalized suggestions will improve over time the more you use the product, the founder says.
To improve its suggestions, Mona mines your email. That is, it connects with your email account in order to look for marketing newsletters, order confirmations, and receipts – similar to the shopping app Slice, for example. This purchase data is the best data to power Mona’s personalizations, which is why it’s not an opt-out experience – consumers have to be comfortable trusting the company to analyze their data in exchange for better product suggestions.
At launch, Mona is tracking 100 of the top 300 retailers in the U.S., but plans to expand its selection. The company is working with these stores’ data feeds for now, as opposed to doing direct integrations. That means there could be some latency as related to the freshness of the data, at times.
The startup is also currently monetizing through affiliate links, but eventually wants to transition to the marketplace model.
“We have strong intent for purchase in the form of missions from consumers,” says Atik. “We can connect that purchase intent from the buyers with the sellers in a more efficient way than other marketplaces,” he states.
The app, which has been in private beta for the past 5 months, is now available as a public beta on the iTunes App Store. Users can request an invite to join from the Monahq.com homepage, and the company says they initially plan to allow around 500 to 1,000 new users per day as they prepare to scale the service.
TechCrunch readers, however, can use the access code TECHCRUNCH to join immediately. (This code will work for a week.) You can grab the new app here.
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