Playvox has grown to over 175 employees, establishing itself as a leading CRM-connected omnichannel provider of WFM solutions for contact centers.

With typical results such as a 30% increase in agent productivity and 43% reduction in time taken to complete quality assurance processes, Playvox remains a top player in powering fast-growing brands while serving expanding digital experience pioneers such as Noom, NuBank, StitchFix, X, and AfterPay.

Historically, WFM customers were corporate entities such as large banks and blue-chip companies. However, as the market evolved and smaller and mid-sized enterprises tapped into the WFM market, more companies found that they had to manage bigger volumes of data with increasing levels of complexity. For its part, from its earliest days, Agyle Time needed to serve new, agile, small and mid-sized set-ups with support teams that required flexibility from WFM solutions.

The company’s initial workloads were on relational database MySQL, but it encountered scale challenges at a time when applications were evolving and the business was more than doubling in size each year. Customers were demanding new and intricate features, but working with relational databases made adding new levels of complexity a laborious process.

“When you’ve got a traditional audience table with tens or even hundreds of millions of records in it, making schema changes is a traumatic event,” says Alex Bullen, Chief Product Officer at Playvox. “It got to the point where we were too scared to make changes, because of the complexity of traditional relational tables.”

Rapid growth in the WFM market demanded that Playvox be equipped to help financial services, retail, and technology contact centers adapt to shifts in e-commerce, flexible remote working, and omnichannel interaction.

Playvox was also keen to stick to a NoOps philosophy, according to Cheyne Wagner, SVP Global Engineering at Playvox. Its priority was delivering features to clients with high levels of scalability and reliable infrastructure. “We don’t want to spend time on the plumbing if we don’t have to,” Bullen adds. “That was the most important thing for us.”

Real-time data was also key. Playvox needed to meet customer demand for live information, which for many is crucial for profitability. One major Playvox customer in Australia monitors real-time news, as it affects volumes to its contact centers. This customer needed information on deviation for more accurate forecasts, and turned to Playvox to process it while keeping costs and complexity under control.

“We also needed to provide timely aggregated metrics on top of that data,” Bullen notes. “We needed to combine that asset with all the main datasets, plus real-time data science.”

Playvox wanted to leave behind the slow and cumbersome processes of traditional databases. MongoDB Atlas was a natural fit for the team and its Amazon Web Services environment. Using MongoDB Atlas, Playvox discovered that as a managed developer data platform, it offers a flexible schema design, and has scaling benefits well suited for high-volume and high-traffic applications. This would give developers an intuitive way to work with data and manipulate complex structures.

With 100’s of millions records a month to manage, and growing client demands, Playvox knew the deployment of MongoDB Atlas was crucial. Playvox found that it was easy to work with MongoDB Atlas; with operational overheads taken care of, its team is free to innovate and further enhance the company’s products.

“It was minimal investment from our operational focus,” Bullen says. “It also allowed us to focus on product development.”

MongoDB Atlas also allowed for storage and retrieval of simple hierarchical data and made it far simpler to manage complex dynamic data.

Having the freedom to organize high volumes of data is critical, and MongoDB Atlas’s flexibility gave Playvox the opportunity and reason to migrate from relational databases. More importantly, however, was the capacity it would give Playvox to innovate.

“It was more about product direction and what was available to us,” Wagner notes. “We wanted to reimagine how the next generation of features will work on the platform.”

Bringing in new features to support multiple versions of schemas was a significant challenge for a relational database; however, Wagner adds that the experience with MongoDB Atlas was about seizing the opportunity to develop a real-time view and “get data organization closer to a truly event-driven flow”.

The MongoDB Atlas architecture not only helped workflow and productivity, but differentiated itself by offering a unique developer experience.

“We don’t have a large ops team. We get teams to run the products they build, so they are comfortable doing that, but Atlas handles much of the workload,” Wagner says. “That works well with our developer stack because we use Node.js for all APIs. There’s great alignment across the end-to-end developer experience around how all these things come together.”

Ultimately, both Wagner and Bullen emphasize that while Playvox is 100% focused on the customer, MongoDB is now the critical underlying data layer for new services and innovations currently in the pipeline. These include real-time-based targeted dashboards that still support traditional analytics workloads.

“We’re targeting the ideal customer experience to provide fast access to data and information, " explains Wagner. “From there we can add further insights and other features to the roadmap.”

Playvox now wants to expand its use of MongoDB Atlas and explore its serverless features, and is using MongoDB Realm to publish events in the context of data flows. More importantly, the agility of MongoDB Atlas in managing large data volumes has given Playvox the confidence to respond quickly and dynamically in a complex, fast-changing market. Having a close relationship with MongoDB’s team was also a key factor fuelling that confidence.

“MongoDB helps us build better products,” Wagner concludes. “That's one of the most powerful elements of our journey.”