How to Launch Innovative Products
Most product launches fail - not because the product is bad, but because customers don’t see why it matters.
A common mistake is to ask customers directly what they want. The problem: people don’t really know. They tell you stories they believe are true, but these rarely predict behavior. This is why traditional research methods often disappoint.
Importance ratings make everything look equally relevant.
Conjoint analysis works with synthetic scenarios and limited features.
MaxDiff gives importance of having a feature, not the lever of improving it
The result: teams build strategies on noise, not on clarity.
A Case in Point: Sonos
When Sonos expanded from in-home Wi-Fi speakers into mobile devices (Move and Roam), they expected fast adoption. Instead, concept tests signaled low demand.
The reason was not the product itself. It was perception. To many customers, these new models looked like “just another Bluetooth speaker.” What really set them apart - Wi-Fi capabilities and the benefits that came with it - wasn’t understood.
The lesson: even experts inside the company struggled to see the product through the eyes of everyday customers.
Three Essentials for Successful Positioning
Over more than a decade of helping brands launch products, we’ve seen that successful positioning requires three things:
Importance vs. Improvement
It’s not enough to know whether a feature exists. You need to understand if having it at all is essential, and whether improving the perception further makes a real difference. For example: a two-hour battery might be unacceptable, but moving from three to four hours may not matter.Features vs. Barriers
Features describe what your product does. Barriers explain why customers hesitate to adopt it. Research shows there are eight recurring adoption barriers: weak brand, poor design, low usefulness, uncertainty, complexity, difficult onboarding, lack of habit fit, and absence of uniqueness. Every category has its own critical barrier.Realistic and Complex Research
The closer you get to a real buying situation, the more valid your results. Showing a product in context - or better, simulating the purchase decision - gives far more reliable insights than abstract surveys. At the same time, methods need to handle the real complexity of products, not just a stripped-down short-list of features.
A Better Way
At SUPRA, we built Implicit Product Intelligence to address these gaps. It measures willingness to buy and willingness to pay implicitly, and evaluates both features and barriers. Causal AI then identifies not just correlations, but true drivers of adoption.
The outcome: clarity on what really matters, where to focus product development, and how to communicate positioning.
Because in product launches, one truth always holds: No research means no chance. The wrong research leads to the wrong position. The right research gives you growth.
Yes, strategy before tactics - but clarity before strategy.
This is how you 10x growth.