“First automated trend forecasting platform” predicted the Rainbow Bagel

A Rainbow Bagel.

The makers of a new trend-forecasting platform claim they predicted the Rainbow Bagel before it was a thing.

Santa Monica, California-based Tilofy is currently in a private, invitation-only beta of its new platform, which it says is the first automated trend forecaster. Unlike services that, say, spot current trends in social media, Tilofy utilizes machine learning, artificial intelligence and machine vision of imagery to forecast trends weeks or months before they become mainstream.

“There’s a bagel store in Brooklyn that was doing something interesting, tapping into the LGBT community” by creating a rainbow-colored bagel, CEO and founder Ali Khoshgozaran told me.

He recalled that Tilofy predicted the future mainstream popularity of the Rainbow Bagel in November of last year. In February, The Wall Street Journal wrote an article about it, and now The Bagel Store is restructuring around its hit product. Khoshgozaran acknowledged he has not yet tasted the concoction.

Also predicted by Tilofy, which was founded in 2013: the rise of the minimalist lifestyle, the success of Chef Ray Garcia (who recently won a Chef of the Year award), and the trends of millennials traveling solo and more women smoking cigars.

Khoshgozaran suggested that such forecasting knowledge could be useful on many marketing fronts, such as a video network looking to create content that will be popular in a few months.

To date, about 140 businesses have requested and been granted access to the platform. Khoshgozaran said any business can request access. Although the required 12-month subscription is “not cheap,” the platform currently is not self-service, and the present emphasis is on creative agencies, brand and marketing agencies and video networks.

By the end of this year, he said, the platform will be released to the public, at which point it will be self-service, after initial training.

The platform monitors over 40 million subjects for months, looking for interest swings in a topic, concept, brand or individual, not just a count of the mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing the possibility of breaking into the mainstream.

Trend detection then results in demographics, psychographics, geographic and other contextual depictions. Data sources include several years of social media, news sites and blogs and a variety of RSS feeds.

Khoshgozaran noted that existing trend prediction leaders like Nielsen and CB Insights “rely mainly on researchers to look at historical data,” he said, while Tilofy is fully automated.

“We have replaced an army of hundreds of thousands [0f] human curators and data-gathering individuals,” he said, “with 600,000 lines of code and machine intelligence for forecasting trends.”

Opinions expressed in this article are those of the guest author and not necessarily MarTech Today. Staff authors are listed here.

About The Author

Barry Levine

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.