How do you update the qualitative research analysis software thousands of professionals rely on? With research, of course!
In episode 67 of Between the Data, host Dr. Stacy Penna dove deep into how Lumivero’s team of product managers and engineers developed NVivo 15. To explain the development process, Dr. Penna spoke with David Rubert, Senior Product Manager for NVivo and Citavi.
In this article, we’ll cover the highlights from their conversation, specifically the processes that led to NVivo 15’s new artificial intelligence (AI) integrations and Rubert's general philosophy for creating products that meet customer needs.
Balancing Customer and Company Needs
In working to create the next generation of NVivo, Rubert noted that his role as product manager is to deliver solutions for customers that don’t clash with the goals of the commercial side of the company.
“It’s one thing to solve a problem [for customers],” Rubert said. “It’s another thing to solve a problem in a way that it kind of creates business problems internally.”
For example, in considering whether and how to bring AI into NVivo, Rubert and his team had to ask themselves the following questions:
- Do our customers want AI functionality in NVivo 15?
- Are the AI tools that exist now capable of producing results that match the high standards academics must meet?
- Is it technically feasible to integrate AI into NVivo without compromising other functionality?
Their initial impression from customers was one of ambivalence to AI. Many academics seemed skeptical as to how it could support their work.
To better understand sentiment about AI, Rubert’s colleague Silvana Di Gregorio, Product Researcher Director, formed an AI Advisory Board by recruiting a range of NVivo customers to gauge their concerns and needs. Capturing and distilling this information required – you guessed it – qualitative analysis.
Using the Tool to Build the Tool
Rubert, Di Gregorio, and the rest of the Lumivero product development team conducted surveys and video interviews with AI Advisory Board members. Interviews included focus group-style sessions and individual breakout sessions. Using NVivo 14, the Lumivero team stored these conversations, coded them, and began to identify themes and concerns the customers had with NVivo 14, as well as with any potential integration with AI.
The next step was to extend their research to the sales and support teams. From the sales team, the team learned that some of Lumivero’s competitors had adopted AI early – prompting some customers to switch products. It’s important to note that they also learned that some of these early adopters had integrated AI poorly – prompting other customers to switch to Lumivero.
The team also gathered insights from customer support, training team members, and various Lumivero partner organizations.
“Quite frankly, they’ll let you know if your last version that came out didn’t quite hit the mark,” Rubert said. “It’s good to learn that, not just skate along thinking it went fantastic.”
Observation, Iteration, and Demonstration
It’s one thing to capture what customers want. It’s another thing to implement features that meet those needs.
“The customer is not always right,” explained Rubert. “They’re always right if you’re looking for their desired outcomes,” or what they want in a product. When it comes to how to make that product better, however, the customer is not usually the best resource to consult. That’s where the importance of industry research comes in.
Rubert described his approach to research by repeating a remark attributed to the legendary hockey player Wayne Gretzky: “Skate to where the puck is going, not to where it used to be.” This quote is about the importance of anticipating movements within your industry.
To accomplish this in product development, Rubert explained that he stays ahead of the puck through constant observation and note-taking. He tracks new developments in software, reads books, and attends conferences – not just software conferences, but qualitative research conferences, too.
Iteration is the next step – filtering customer needs and ideas for design into product development tools. Currently, the Lumivero team uses a tool called Product Board, which integrates with project management software. Tasks are constantly being aligned with prevailing themes in customer feedback – what Rubert called a “leaderboard” of feedback.
When a demo is ready, Rubert tries not to push the customers to focus on one particular feature. Instead, he simply asks them to give their feedback freely so that he can understand how they view the product, and not how he hopes they will view it.
Products Exist in an Ecosystem
Finally, Rubert shared two major pieces of advice for product managers. The first is that they should develop a deep understanding of the problem domain – that is, the entire set of challenges that your customer faces, plus the challenges faced by the people who rely on the work that they do.
For example, if a qualitative researcher can’t reliably analyze their interview data, how can the policymakers who rely on their research develop informed legislation proposals?
The second piece of advice is to learn how to communicate the same ideas about your products to different audiences. Using technical software jargon, for example, is probably not going to help a social scientist with no background in computer science understand what they can do with qualitative research software. Similarly, explaining the product as you would to a social scientist may not be useful when talking to a sales representative or member of the engineering team. Listening closely to the language of each stakeholder involved will help.
“Don’t speak with your voice,” Rubert said. “Speak with the voice of your customer.”
Learn More About NVivo 15 + Lumivero AI Assistant
With additional coding features, the ability to search across projects, and the Lumivero AI Assistant, NVivo’s newest release has been built with input from qualitative researchers (and with qualitative product research) that make the best qualitative data analysis software* even better.
Interested in learning more about how the Lumivero team approached product development? Listen to the full podcast episode.
Want to see NVivo in action? Request a demo today!
*Source: Scopus Data Analysis 2024