By Steve Phillips, Co-Founder & CEO, Zappi
In the not-so-distant past, the marketing world relied heavily on focus groups to validate new product ideas and advertising campaigns. This approach, whilst once considered the gold standard, has developed a spotty reputation over the years.
Consider the infamous Sony Walkman focus group. Participants overwhelmingly endorsed a new “sporty” yellow version of the Walkman, only to unanimously select the traditional black model when given the choice. Similarly, in blind taste tests conducted for Coca-Cola’s introduction of New Coke in the 1970s and 1980s, researchers failed to account for the deep emotional connection consumers had with the original Coke formula and branding, forcing Coca-Cola to revert quickly to the original.
Historically, focus groups were high-leverage moments in a marketing campaign. That’s because getting a large enough and diverse panel of consumers in one place to review a product or ad campaign was prohibitively expensive. The available technology didn’t afford marketers the luxury of being able to speak to consumers directly online and get their feedback in a matter of hours like we can do today. It’s markedly faster, cheaper and more representative than a traditional focus group.
In many ways, our capability to test ideas has evolved, but our application of testing is still stuck in the past. The problem lies in the gravity we place on testing. Most brands use consumer testing as a stoplight. It’s a pass-or-fail process where consumers feedback on your creation, the data is weighted and your idea is either green-lit to see the light of day or it’s tossed in the bin to start from scratch. In order to truly leverage new technology, we first need to change our mindset around testing.
Embracing a Connected Mindset
To truly harness the transformative power of data, forward-thinking organizations must shift from a traditional project-based approach to one of continuous experimentation and learning.
Testing should be seen as a piece of the broader puzzle of understanding consumer needs and wants. By fostering a proactive, learning-centric approach, businesses can activate a “flywheel effect” where each technological deployment enhances the accuracy and depth of insights.
McDonald’s embraced this mindset shift, enhancing their innovation process, particularly in developing new menu items. By integrating continuous learning and connected data points, they were able to optimize product concepts at the same pace with which they formerly validated ideas. Instead of merely focusing on fast feedback to green-light ideas late in the process, McDonald’s started testing new product concepts earlier, where the goal wasn’t to approve an idea, but improve it.
Because McDonald’s saw testing as part of a larger puzzle, the marketing team actually began to test more, not less, as new data added to their flywheel. This meant they were able to not only assess what ideas work, but also understand why they work. McDonald’s was able to understand how individual ingredients could drive consumers to select a product. This ladders up to the ability to predict trends and take a more calculated, forward thinking approach to innovation.
Compare this with the processes of Sony and Coca-Cola in the prior examples. Beyond the benefit of decades of technology at their disposal, the team at McDonald’s builds new ideas around what consumers want, rather than spending millions in R&D only to hope for a green light at the last minute.
Evolving their testing into a continuous learning flywheel, McDonald’s demonstrated how brands can connect the dots within their data, understand larger trends, and make strategic decisions for long-term growth. More than that, they’ve created lasting change that will enable teams to work more efficiently.
This mindset shift will be critical in the AI era, where technology can become a massive competitive advantage.
AI + Connected Data Asset = Competitive Advantage
When you evolve your thinking from a rigid pass-or-fail process to a flywheel where each data point adds one more piece to the consumer puzzle, you can leverage AI to pave the way for more efficient, effective innovation.
AI becomes a competitive advantage that feeds off of your learning flywheel to augment the entire creative process. It can help teams connect the dots across the full data asset to predict trends and better understand what drives consumers.
In a futuristic model, and something we are experimenting with, generative AI can create, optimize, and localize your best product ideas. During the creation phase, data provides rich context to help large language models (LLMs) understand your customers, enabling AI to generate products aligned with customer preferences based on past interactions,
Optimization and localization go hand in hand. Starting with testing new product concepts, teams can use AI to action on consumer feedback to improve and refine ideas to better meet customer needs. At the same time, AI enables tailoring products to the best audience possible, whether regionally or based on specific interests and demographic information. This makes products more relevant and appealing to targeted consumer groups.
By developing a connected system that stores all their data and facilitates continuous learning, companies can generate more informed and creative ideas, driving innovation and staying ahead of the curve.
