What’s the Most Promising Trend in Digital Quality?
Trends in digital quality never get the same buzz as development tools. For many, the ability to create is more appealing than the ability to validate. Yet, the latter is fundamentally more important from the customer’s perspective. A big, fancy app that makes use of the latest cutting-edge whatevers and AI whozits is guaranteed to fail if it isn’t thoroughly tested.
Guests of the Ready, Test, Go. podcast, thankfully, understand the value of validation and the customer experience. They bring different perspectives, expertise and approaches, but it all boils down to a high-quality experience for the customer. And, so, their attention is often on the latest tools, trends and methodologies that enable digital quality — even if their answers vary.
In our Lightning Round questions from the podcast, I ask a standard slate of digital quality questions. Our expert guests responded below to the question: What is one digital quality trend that you find promising? Let’s check out their answers, which offer a roadmap of both opportunity and caution.
Data innovation: synthetic, federated and debiased
In an era where data is the backbone of every digital system and AI proliferates throughout the product roadmap, it’s no surprise that the way we generate and govern data was a big theme for our guests. However, each guest had a different wrinkle on the subject.
Nathan Chappell, author and Chief AI Officer at Virtuous, spent the duration of his episode speaking to the need for caution with AI, even as it offers tremendous opportunity. Then, he threw us a curveball, telling us that synthetic data, in which AI creates data to train itself, offers tremendous promise.
“I think there’s some technical breakthroughs in synthetic data that are letting us round out some big gaps and holes in data right now and allowing us to do that in a pretty transparent way,” Chappell said.
This kind of innovation could be a game-changer for overcoming data scarcity and bias without compromising user privacy.
Speaking of privacy, Sandra Matz, author and Associate Professor of Management at Columbia Business School, highlighted federated learning as a standout trend. This approach enables training machine learning models locally on user devices using the data stored there. However, instead of uploading personal data to a central server, only small, encrypted updates are sent back. That way, companies can improve models and services using insights from user behavior without directly accessing or storing sensitive personal information.
“[Federated learning] is essentially a way for users to have it all,” Matz said. “To have privacy and self-determination, but also get convenience and service.”
Payal Arora, author and Professor of Inclusive AI Cultures at Utrecht University, also thought about how to train AI models in a more humanistic way. In combating AI bias, Arora recommended a proactive approach, rather than reactive, to open up models to a new way of thinking.
“I think about how we can de-bias data with creating new forms of data to basically train AI to make the world see it differently,” she said.
Generative AI and agent-based systems: promise with caution
How we train models was one discussion, but how we deploy AI itself was another.
Jason Mills, VP Solution Engineering at Snowflake, emphasized the transformative power of generative AI. But he also underscored the potential problematic nature of its capabilities.
“Audio, video and image creation — I think what’s happening here in this space is really groundbreaking,” Mills said. “I think we need to pay attention to the ethical use of generative AI. Because, obviously, you can’t get the inferencing that we’re seeing or the results that we’re seeing without the data that it was trained on. There are some legal implications, even ethical implications, around how these things were trained.”
But, echoing the perspective of many innovators, he remained optimistic that AI-infused products could not only help businesses become more efficient, but also offer benefits to humanity itself.
“Once we get this right, I think it opens up new opportunities for people to live a better life,” he said. “We just have to be really careful about the fairness around it and how we’re approaching it.”
Ben Van Roo, CEO and Co-founder of Legion Intelligence, took a systems-level view. Agentic AI might be the next step in innovation, as organizations will look to models that can perform autonomously, but it has a long way to go.
“The whole agent-based world of artificial intelligence is very intriguing,” Van Roo said. “It is far from baked. I would encourage people to not think that these agents are going to go off and do everything. But I very much like the idea of having slightly more complex systems and tooling help us accomplish more tasks and chains of tasks. Its potential lies in helping us scale and automate complex digital operations responsibly.”
Real-world experience: measuring the customer impact
Several guests turned the conversation toward arguably the most important aspect of digital quality: the user experience. User friction derails digital initiatives, while brands that delight customers establish long, loyal relationships.
Richard H. Miller, author and AI/design strategy consultant, champions user metric-driven development. It’s ok to start with a rudimentary measurement of the user’s experience — the point is to continue to make informed decisions based on what your customers value.
“I would even settle for something as simple as a net promoter score, if I had to start with something really trivial,” Miller said. “Some people don’t think it’s enough. I can agree with that, but at least it’s a start. So, just getting data-driven decisions, I think, is a big deal now.”
Todd Unger, Chief Experience Officer at the American Medical Association, took it one step further. He argued that teams should work toward “automation of friction collection,” a growing trend for orchestrating these user challenges, so that blended teams are constantly able to improve upon the digital experience.
“Our friction indices have had the most impact on us,” he said. “Just basically the number of problems that people are having over total sessions. And that’s not just in aggregate, but that’s with each individual product. If you’re tracking that carefully, you can pretty much see, are people able to do what they want to do, what they’re trying to do.”
And then there’s Irene Pereyra, Designer and Founder at Anton & Irene, who prioritizes the user experience without all of the machinery attached to metrics. “I don’t like any of them, to be very honest,” Pereyra said. “I think they all are flawed in their own way. I think nothing beats actually talking to real human beings one-to-one and observing them in their own environment.”
A multi-dimensional future for digital quality
The most promising trend in digital quality might not be a single technology or practice. What works for one organization might not for another. Yet, some of these broader trends can certainly inform how brands prioritize their customers’ privacy and experience. Data, AI, user metrics and human insights all factor into a bigger, more integrated picture.
As a global leader in digital quality, Applause is built by innovators and powered by people. That means we’re always pushing the boundaries of technology while prioritizing the fundamental humanity of the products our clients are building. We offer fully managed community-based testing solutions that empower brands to quickly release apps, devices and experiences that are functional, intuitive and inclusive. Our solutions provide a cohesive view into every aspect of the digital customer experience. Our goal is to be your release partner for all aspects of digital quality, helping you release faster with confidence by providing real-time insights and actionable reports.
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