More than 30,000 new products are launched every year, and 28,500 of them (or 95%) fail. This staggering failure rate underscores the importance of gathering customer feedback early and often. Without understanding the true needs and pain points of your target audience, it’s nearly impossible to develop a successful product that will resonate in the market. Seeking customer feedback is not just a common practice – it’s a vital step that can make the difference between success and failure in the highly competitive world of product development.
Humans thrive on feedback; we create ideas, we test ideas, and we improve ideas. In fact, we’ve built large industries, like market research, designed to acquire feedback. We’ve become obsessed with data as a proof point to help us make decisions. Even more, we’ve adapted our means of gathering data to become faster and more economical.
Now, none of this is revelatory, but there is a purpose in bringing it up. In about 20 years, market research has gone from phone and mail surveys that take weeks to digital data acquisition with live face and eye tracking that takes just hours. These developments mean that we’ve become very efficient at gathering data, but we are incredibly inefficient at learning from it.
For the first time in nearly a decade, the way we learn from feedback is changing. Artificial intelligence has stormed on the scene to change our view of data and how we can use it to enhance innovation. It doesn’t just process information; it understands it, collating and translating our disparate feedback into meaningful consumer understanding.
Where humans thrive on feedback, AI thrives on data. While human intuition can be a valuable tool with some data, too much data makes it categorically impossible for a human to understand its nuances. Details begin to fall through the cracks and disconnected data sets only tell part of the story.
By leveraging AI’s data processing and pattern recognition capabilities, businesses can channel everything they’ve learned to create an initial product concept from scratch.
After testing these ideas and getting the rich feedback from core audiences, we can add this feedback into our system, creating a learning loop powered by AI.
Combining the relative strengths of AI and humans, we can usher in a new era of how we connect and mobilize feedback. With the right partnership across data, AI and humans in the loop, you can become more agile and drive meaningful innovation and market success.
Source : TechRadar
