Simporter Uses AI to Help Brands Launch More Successful Products

The startup’s ideation tool uses predictive data to automate the product research process.

Written by Ashley Bowden
Published on Sep. 14, 2022
Simporter Uses AI to Help Brands Launch More Successful Products
Simporter co-founders Tim and Dillon Hall. | Image: Simporter / Built In

Sure, the latest initiatives from the Teslas, Apples and Googles of the industry tend to dominate the tech news space — and with good reason. Still, the tech titans aren’t the only ones bringing innovation to the sector.

In an effort to highlight up-and-coming startups, Built In has launched The Future 5 across 11 major U.S. tech hubs. Each quarter, we will feature five tech startups, nonprofits or entrepreneurs in each of these hubs who just might be working on the next big thing. Read our round-up of Atlanta’s rising startups from last quarter here.

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Consumer behavior evolves at a constant rate. Trends shift so frequently that businesses often face challenges creating new products shoppers want. In the age of social media, online reviews and fast-paced e-commerce, what consumers are looking for can change on a dime. Simporter wants to help direct-to-consumer businesses stay ahead of the game by predicting the products of the future.

At its core, Simporter is an AI-powered software tool that automates new product research for consumer goods companies. The platform uses machine learning to recognize trends and uses AI to generate new product concepts. Based on data from search queries, social media posts and similar sources, Simporter predicts consumer demand around certain product attributes. 

Brands can peruse that data and make edits to generated product concepts. From there, the solution scores a brand’s product idea and forecasts sales for that item before it enters the market. 

“If you invest in consumer opinions of today, by the time your product launches, their demands have already changed.”

Dillon Hall and his father Tim co-founded Simporter in 2018 with the goal of taking the guesswork out of launching new products. The startup’s mission is to help companies increase their new product success rate.

“Consumer demand is so fragmented today … that traditional market research approaches no longer work,” Dillon Hall told Built In via email. “If you invest in consumer opinions of today, by the time your product launches, their demands have already changed. By providing a quicker, more predictive tool to identify unmet white space opportunities, Simporter lets our users be first to market and increase data-driven actions.”

Being the first to market a particular idea is one of the main challenges for brands when it comes to launching a new product. Just as well, brands tend to make product decisions based on previous sales or consumer surveys, according to Dillon Hall. By referencing this historical data, brands often build products that are nearly obsolete by the time they’ve been developed. 

Simporter’s main purpose is to help brands take advantage of opportunities where they can fulfill unmet consumer needs and be the first to do so. Rather than depending on findings from several research agencies and software tools to do this, Simporter’s machine learning tech pulls together disparate data and connects it for brands in one place.

“We want Simporter to be a tool used by every major consumer goods brand across the United States,” Dillion Hall said. “With this achieved, consumers can begin to see a lot more new, trendy items in stores that are addressing their unmet needs. With Simporter, brands launch products quicker and more successfully.”

The company currently works with around 20 Fortune 500 brands helping them launch various products, Dillon Hall said.

Looking ahead, Simporter is focusing on organic growth and plans to launch new features over the next few months.

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