Research is invaluable.
Companies need research on prospective and current customers to analyze trends, evaluate purchasing decisions, and produce the best products that they can.
Customers need research on what to buy, where to buy, and who to buy it from.
Phonic is a research software startup with a mission to break down the barriers between quantitative and qualitative research to allow businesses to collect genuine insights at a scale that they can trust.
Phonic CTO Mitch Catoen says that the pain point the company is addressing revolves around scaling.
“Qualitative research is really good, and yields really good information, but it doesn’t scale quite like quantitative research does,” Catoen explains.
The key, Catoen says, is that Phonic takes an analytics-first approach.“When we think about emotional intelligence, multimodal sentiment, and tag extraction, these are things that were built for our research platform, and the research platform sits on top of them. The customers of Phonic know they can trust our analytics more than any other platform,”
When it came time to decide how Phonic was going to build its technology, one of the most critical pieces the company wanted was a NoSQL database.
Catoen wanted Phonic to pick a NoSQL database and a document-based database because Phonic was changing schema so frequently, and did not have a rigid data model from day one.
For these reasons, Catoen says that working with MongoDB Atlas was "a pretty obvious choice."
The decision to go with MongoDB meant that Catoen and other company leaders could spend their valuable time thinking about the business and how to provide actual business value for their customers.
“With MongoDB, we effectively leverage the entire core feature set,” Catoen says. “We run a lot of aggregation pipelines, which are super, super useful with dealing with large amounts of data. We can scale up and down with our cluster to support more, and that’s been fantastic.”
Phonic’s tech stack is pretty simple in order to keep developer velocity high, Catoen says, the same motivations the team had when picking its NoSQL database. Phonic runs a React frontend, a Python backend, communicates with their MongoDB cluster, and uses RabbitMQ for event streaming.
Google Cloud has been a critical part of Phonic’s success, as well, Catoen says. Phonic utilizes its cloud functions on Google Cloud, including its storage for distributed file storage, and on App Engine because of Google Cloud’s auto-scaling, especially when the company gets hit with a jump in traffic overnight.
As for plans for the future, Catoen says the company is looking for a Series A round of funding and will launch an asynchronous research product.
“Building up this conversation intelligence suite is going to be very important to the Phonic ecosystem going forward,” Catoen says. “We’re very excited about that.”
Learn more about the MongoDB for Startups program.