Ukrainian startup Watched has raised $450,000 from local venture fund QPDigital to ramp up sales and hire new staff, according to its cofounder Oleksii Shaldenko.
Shaldenko and its partner Artem Melnichenko have developed an online platform that helps directors, advertisers and production companies to analyze how viewers respond to videos, commercials and TV shows.
Businesses that use the service first have to upload their videos to the website and send them to the target audience. The platform scans the expression on viewers’ faces through the camera on their devices and analyzes how people behave while watching a video.
To make sense of this data, the company uses artificial intelligence that detects human emotions and gestures. The data helps understand whether viewers like the video or not, what parts of the story are the most interesting and how long the audience stays focused.
For example, just by analyzing the expression on the viewer’s face, the company can say whether the video induces laughter, fear or disgust, how the audience responds to advertised products and whether people want to continue watching further.
By using the service, TV show producers or owners of streaming platforms can test pilot episodes of their shows to analyze the reaction and then decide whether they need to continue the production.
Eventually, this analysis may help businesses save money on production and advertising — they can learn in advance what the viewers need, Shaldenko said.
Investors see great potential in this technology. “The service is very up-to-date and works with one of the trendiest technologies,” said Denis Valvachev, chief executive at QPDigital.
Technology like artificial intelligence and facial recognition that Watched uses to develop its service are in demand in 2021, according to research platform Gartner. The emotion detection and recognition tech market is expected to grow from $21.6 billion in 2019 to $56 billion in 2024, according to analysts Markets and Markets.
Shaldenko and Melnichenko knew that the demand for their service will grow when they launched a platform in 2019. Shaldenko had experience working with Hollywood projects that use similar tech so he understood what the industry needed.
To date, many streaming platforms, TV channels and production studios do not have fast and cheap tools that analyze the response to their content before or during the production, so they usually follow their gut feeling.
Shaldenko thinks that his approach to content analysis will help businesses to create better videos, TV shows and commercials.
On the global market, Watched competes with companies like Affectiva, Neurodata Lab and Realeyes. These firms also develop tech that analyzes human emotions and helps businesses better understand their customers.
Although Watched is a newbie in the industry, it has already got support from big-name partners like tech giant Amazon, computer chip manufacturer Nvidia and Ukrainian innovation park Unit.City.
Since 2019, the company raised $600,000, of which $55,000 came from Shaldenko.
Among the company’s customers are online cinemas, marketing agencies and TV channels. In the interview with the Ukrainian media MC.Today, Shaldenko said that Ukrainian TV channel 1+1 and local streaming platform Megogo have already tested the product.
In Ukraine, it is still hard to grow a business that works with the so-called “deep tech,” which tries to resolve intricate engineering challenges.
“Creating a deep tech startup in Ukraine is suicide. It is extremely difficult,” Shaldenko said in the interview.
In the future, the company wants to start working in the U.S. It also sees demand in Southeast Asia and China.
Apart from movies and commercials, the company wants to use its product in video game development, education and medical diagnostics.
This video demonstrates how the technology developed by Ukrainian startup Watched works. The company uses a smartphone or laptop camera to scan a facial expression on the viewer’s face. Then, artificial intelligence analyzes the data and shows how a person responded to the video and what kind of emotions the video induced.
