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Machine learning in insurance: Empowering executives to drive better business decisions
Early experiments and a long term strategy can help establish a competitive edge and help decision makers transform data into business critical solutions.
By Daniel Kalick · May 5 · 7 min read
Launching a new product is inherently risky. It’s impossible to guarantee success or predict exactly how customers will react. In short, there’s no crystal ball to tell you what value proposition will lead to a breakthrough, what features customers really want, or what type of user experience they crave.
But product development isn’t total chaos, either. While there are things you simply can’t know before bringing a product to market, risk can be reduced by focusing on the right customer problems. Nailing that part of the process is the key to constraining the potential set of solutions, reducing distraction, and ultimately increasing the chances of shipping a successful product.
Of course, this is easier said than done. Large companies are typically swimming in data from disparate sources, making it hard to separate signal from noise when analyzing the customer journey. Meanwhile, early-stage startups have the opposite problem — very little data to go on — and face pressure to ‘validate’ their ideas quickly, even if they’ve only interacted with a small sample of users.
So, if you’re a big company or a small one, how do you know you’re solving a worthwhile customer problem?
Part of the answer lies in where you look. At Fuzz, we’re often peering into less obvious places to discover unmet customer needs — investigating the end-to-end journey to find problems that are typically neglected. To do so, we draw on a range of methodologies, from human centered design (HCD) to data science. And we adopt a few key principles along the way:
It’s natural to begin the product development process with a great idea. And it can be motivating to start the ‘making’ part of the process in earnest. However, if the solution you’re excited to test is based only on assumptions — instead of hard-won insights — there’s a good chance you’ll waste effort fixing problems that don’t matter. Take the time to first assess what qualitative and quantitative insights you already have, and what knowledge gaps you need to close.
Once knowledge gaps are identified, it’s easier to plot an effective research plan. User interviews are table stakes for any product development effort, but to truly identify neglected customer problems and challenge the team’s assumptions, it’s important to go deeper, particularly for specialized products. Ethnographic methods are critical for understanding the mental model of your users, and identifying pain-points that would otherwise remain overlooked. And interviewing experts can shorten the time it takes to get smart on a particular space.
We’re often focused on the core part of the product experience — those key interactions that are essential to delivering customer and business value. But what happens before and after the core journey? And what about those critical ‘in-between’ moments of transition — from digital to physical touchpoint, for example, or from one digital service to another? The promise of frictionless design often breaks down in these areas. Plotting the end-to-end customer journey can help surface customer pain-points that too often slip through the cracks.
The customer is always the main protagonist. But they aren’t the only cast member. In any product experience, crucial supporting roles are played by a host of company employees. That means it’s important to understand, and solve for, the employee pain-points that stand in the way of best-in-class service. Applying the same research methods to the operations side of the business can help teams identify the neglected needs of employees.
Prototyping has by now become a core methodology in the product development toolkit. But we predict pressure testing will soon set a new industry standard, particularly for enterprise-level products that marry digital and physical experiences. Pressure testing entails the re-creation of realistic product usage conditions in a lab environment, helping teams identify customer problems in those tricky ‘in-between’ parts of the service journey, including pain-points that arise with technical performance issues — all before bringing a product to market.
Necessity is the mother of invention, and it’s no wonder the best solutions are often built by those who experience a problem firsthand. It’s therefore critical that product teams not only empathize with users through research, but also routinely step into their shoes. This means teams should regularly use the products they’ve launched where possible, developing a first-person perspective of customer problems and frustrations. This method can be a powerful tool for developing informed hypotheses for optimizing the product and solving customer needs.
Product development is an inherently risky endeavor. But the chances of success can be increased by focusing on the right customer problems. Identifying unmet needs is often a matter of where to look. By investigating the hidden parts of the customer journey, and adopting the right research methods and principles, companies can more easily discover the problems worth solving.
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