On the surface, understanding social metrics may seem simple. However, some analysts find it’s a bit more complicated than it seems.

That’s where Nichefire comes in. It’s looking to help its users dig past the most basic  elements of understanding metrics to more meaningful, sophisticated place, so its clients can get more out of the data.

“The importance of identifying product market fit beyond what our past experience was our obsession for a bit.”

“Nichefire is your solution to better, quicker social media insights and competitive analysis,” its website says. “We take the tech out of data, so you can compete with the big guys.”

CEO Michael Howard started the business with college friends Khalil El-Amin and Steven Brown.

“We’re building a benchmarking platform that uses machine learning to classify, score, predict, and recommend actions by leveraging content performance, brand loyalty, ad spend and customer conversations for any brand,” Howard said.

The journey to Nichefire’s development involved many trips back to the drawing board.

“We started off approaching investors with an idea and a few designs, but quickly realized more work needed to be done,” Howard said. So, “the importance of identifying product market fit beyond what our past experience was our obsession for a bit.”

The team went through HCDC, where they learned more about things like business model canvases and more. Additionally, they spent a considerable amount of time interviewing more than 100 marketing professionals from a variety of agencies and brands. It was an effort “to learn about their process and pains.”

Through these interviews, they found that mid-sized agencies were still analyzing social data, such as social media, searches, reviews, SEO and more, manually. Some were even spending upwards of 100+ hours a month on this kind of work for one client.

They wanted to build a subscription-based software where marketers could analyze the data without spending a lot of time doing it themselves.

“This allows our users’ to be proactive in with their business and marketing initiatives without having to succumb to ‘analysis paralysis,'” he added.

Artificial intelligence and predictive analysis are how Nichefire’s software does just that.

“We built a way to deliver insights that originally had to be manually analyzed and collected — taking many hours to do — in minutes, in a self-service integrated analytics platform,” Howard said. “We focus on brand analysis and competitive response modeling, developing predictive insights as to what competitors will do on a particular platform, what consumers will say and what the user should do in response.”

Currently, they have a provisional patent for their software.