When Amy Errett set out to create Madison Reed, an online shop for hair coloring products, she and her team thought a 12-question, quiz-based algorithm was all they needed to determine the right dye for each customer's hair. But from the moment the San Francisco startup launched in 2014, women began sending in their selfies--they wanted a more visually-based assessment.

Madison Reed, which prides itself on customer service, was happy to have its representatives review the selfies and assist customers, but the key to success for any tech business is the ability to scale. That's why in 2016, Madison Reed began experimenting with computer vision, a technology that applies artificial intelligence to interpret and act on visual data. Errett and her team were hoping to create photo-recognition technology that could analyze women's selfies, identify their hair, determine the color, and match it to one of the company's 46 available shades.

"We saw right away that our users were demanding a mechanism for someone to look at a picture," says Errett, noting the discomfort they had had with relying on a quiz, no matter how accurate it was.

After nearly a year of development, the company finished the photo-recognition feature in October and began rolling it out to its most frequent users. By December, Madison Reed was using it with any consumer interested in its hair dyes. Talk to Madi, the company's Facebook Messenger and SMS chatbot, send over a selfie, and within seconds, Madi will respond with the two best dyes for your hair.

"Using the technology is allowing us to make better matches in larger numbers," says Jon Callaghan of True Ventures, one of Madison Reed's investors. To date the company has raised more than $45 million in venture funding. It declined to disclose its revenue or whether it is profitable.

Tapping into computer vision as a way to scale was no small feat for Madison Reed, but the timing was ideal.

Computer vision is a technology and a market that have begun to explode. In 2016, funding for computer-vision startups reached $522 million over 69 deals, up from $186 million and 47 deals in 2015 the previous year, according to CB Insights. Fueling this growth are advances in various technologies, most notably the processing capabilities of computers and in algorithms with machine-learning technologies that are used to identify visual data sets.

"We're seeing an increasing number of these sort of applications for computer vision, either for marketing purposes or the personalization of products," says Nick Ingelbrecht, research director at Gartner. "This is certainly a growing area."

The objective of Madison Reed is to give consumers who are doing home coloring a salonlike yet quick and convenient experience. Madison Reed estimates there's a market of tens of millions of women in the U.S. who color their hair. For them, the options are shopping for home-coloring kit at their local pharmacy or supermarket, where they can only guess on the best shade for their hair, or going to a professional coloring salon, which usually takes a couple of hours and costs north of a hundred dollars per visit.

Errett and her team aim to do for hair coloring what Dollar Shave Club does for razors: give the consumer an online option for a high-quality experience that is also quick and convenient. Providing consumers with visual confirmation of what color they should use is a key part of the experience.

"What we really wanted to do with computer vision, if you will, was give eyes to our technology," says Dave King, Madison Reed's chief technology officer. "Now, through computer vision, we're taking out that element of fear and uncertainty that our customers had about picking from a swatch on the web, which was similar to the struggles they'd go through at stores."