This fall, 81 organizations across New York City — ranging from Fortune 500 corporations and nonprofits to cutting-edge startups — provided 260 students enrolled in Product Studio a list of some of their biggest business challenges and a not-so-simple request: How might we solve it?
Small teams of students were created to build a specific, technology-based product to address the challenging company's broad problem. In order to do that, many teams realized their client wasn’t just their assigned company: “The client was the real people who would be the final users of what we were developing,” said Joao Gilberto Campagnaro, Johnson Cornell Tech MBA ’18. They needed to go past the hypothetical to find out what consumers actually needed.
Here’s how two different teams handled the challenges of creating consumer-facing products:
Samsung asked: How might we increase consumers’ understanding of how to take advantage of Smart Home tech?
Having previously worked at a startup that explored hardware applications in the Internet of Things (IoT), Campagnaro immediately knew he wanted to tackle Samsung’s Smart Home challenge. But where would his group — also made up of health tech, connective media, design, and computer science students — begin? The answer lay in figuring out which type of consumer they’d best serve.
“After a lot of thinking … we came to the conclusion that one segment who can benefit from smart home technology that might not be getting addressed is the elderly,” he said. Specifically, the elderly population living in nursing homes. “When you put someone you care about in a nursing home, you’re invested in their well-being. But even the best nursing homes can have difficulty monitoring everyone all the time. We could help with monitoring and providing long-term data.”
In order to figure out how to best serve nursing home residents, teammate Fani Maksakuli, Master of Computer Science ’18, said they talked to doctors, scholars, nurses, and “visited four different nursing homes, some which had more resources than others.”
After talking to one nursing home’s CIO, the team was told that even though the facility had looked into smart home tech in the past, there weren’t service providers who could install smart home hardware and sensors and then present the resulting data in a clear way. There was a lack of connectivity, so the team created a platform that provided and could connect to any kind of smart technology. They’d then transmit the data to an easy-to-read dashboard that would show nursing home staff their patients’ behavioral patterns.
“An example of this is measuring an elderly person’s bathroom visits with motion sensors,” said Maksakuli. “If the bathroom pattern is increasing and they’re using it much more than usual, it could be a sign of a UTI. The earlier nurses can see it, the earlier it can be treated.” Staff could also monitor sleep patterns and even whether their clients were taking their medications at proper time intervals.
“Our client is a company, but we had to show that we cared about their clients,” Campagnaro said.
Grammarly: How might we help people write more clearly, effectively, and grammatically?
For the team working with Grammarly — an online platform that instantaneously checks writing for grammar, punctuation, spelling, and word choice — identifying consumer needs was somewhat simpler considering that they were the target demographic.
“Grammarly is a tool that a lot of international students, including myself, were using,” said Israel Krush, Johnson Cornell Tech MBA ’18, whose team was composed of students born in China, Israel, India, and Uzbekistan who were all interested in natural language processing. “We related to the challenge.”
Since there were already products which scanned writing samples for grammar and spelling, the team decided that their product would relate to grammar and tone, making writing more effective.
“We first wanted to put a style filter on a piece of text, similar to how you use a photo filter on Instagram,” said Maksimilian Shatkhin, Master of Computer Science ’18.
The group began testing this product by having users type in a sentence and then select a filter through which they wanted it to be read — for example, they'd select "professional" if it was intended to be a work email. Then group members would change the input themselves by manually editing the text into a new sentence.
After some experimentation, however, the team realized that manual translations weren't the most efficient or helpful way to give feedback. Thus, they pivoted to an algorithmic-based model. Zheyuan Gu, Master of Computer Science ’18, said, “Our end product provides visual feedback and is a suggestion tool for our users, and users will edit it by themselves.”
Basically, a consumer will add writing into a website and use a drop-down menu to specify context (are they seeking advice? Detailing a mistake?) and the audience (is it to a boss or a subordinate?). The consumer would then click a button to receive a radar chart that ranks various stylistic aspects of the writing. It’d highlight toxic language in red, to point out any overly complex or passive sentences, as well as rate the formality and specificity.
“Since not everyone is an engineer, we gave users actual recommendations of how to change their language,” said Krush. “We didn’t change it for them, but it’s easy for them to do it.” That way, users maintain agency over the language they use.
“It isn’t a mass product, but we do have some early adopters,” Shatkjin said. “When classmates had to write a cover letter for homework, many of them sent us a draft and used the tool to simplify it.”
The fact that the tool has resonated with its intended customer base is a sign of success both for the team and for its Grammarly advisor.
As Campagnaro from the Samsung team put it, "The main thing about being successful in B2B2C (Business to Business to Consumer), is that you as the first 'B' have to convince the second 'B' that you understand their 'C.'" If the consumer is happy, the company will be as well.