Goodbye consumer panels: The smarter, faster way to predict what shoppers really want

Touted as the first new permanent flavor addition to Coca-Cola's North American lineup in three years, Coke spiced was designed to appeal to younger consumers with its unique blend of the classic Coke taste along with raspberry notes.

However, just seven months after its launch, Coca-Cola announced the discontinuation of Spiced due to lackluster consumer interest and sales. This isn’t an isolated incident. The 85% failure rate of new products within their first year is a decades-long statistic that highlights a systemic issue: Traditional consumer panels don’t work.

Consumer panels, particularly Central Location Tests (CLTs), have been the industry standard for decades. But these outdated methodologies, relying on flawed metrics, artificial  tested environments, and limited and unrepresentative samples, consistently fail to predict real-world consumer behavior.

We’ve moved beyond these outdated methods. Our innovative digital twin platform, doesn’t just replace consumer panels—it redefines product development entirely.

The limitations of consumer panels

1. They measure the wrong things                                                                
   
   Consumer panels rely on hedonic scores to gauge product appeal. These scores capture how much participants "like" a product in the moment but fail to reflect the complexity of consumer decision-making. Factors like emotional engagement, contextual relevance, repeat consumption and long-term consumption patterns are entirely overlooked. Research consistently shows that liking alone is a poor predictor of market performance. Products that perform well in panels often fail to resonate with consumers  in the market because these tests miss the nuanced drivers of long-term loyalty and real-world success.
   
   
2. Sample representation                                                                          
   
   Traditional consumer panels often fail to include key demographics such as Gen Z, rural populations, or affluent consumers, leading to skewed results that fail to reflect the diversity of the broader market.
   Validation studies executed with our clients, comparing liking outputs from our models to those from CLTs have revealed a critical flaw: achieving good correlation with CLTs requires isolating a specific subset of the general population. This subset is disproportionately biased toward individuals who are more open to trying new products—a stark contrast to the real world, where such openness is significantly less prevalent. This mismatch highlights the fundamental limitations of CLTs in accurately predicting broader consumer behavior.
   
   
3. Artificial and static testing                                                                  
   
   Consumer panels typically take place in controlled environments that fail to replicate the dynamic, real-world contexts in which products are actually consumed.
   
   
   • Context Matters: For example, a snack consumed at home during a movie night will be perceived differently than one sampled in a sterile lab.
   • Consumption Patterns: Research from the Monell Chemical Senses Center shows that variables like the number of bites or sips significantly influence consumer perceptions.
                                                  Figure 1: How liking changes with repeated sipping.
     
     These nuances are lost in traditional panel tests, resulting in insights that lack relevance and applicability to real-world consumer experiences.
     
     
4. Misaligned metrics                                                                                 
   
   Hedonic scores focus on momentary liking, ignoring the broader factors that drive real-world behavior:
   
   
   • Repeat Consumption: Does the product retain its appeal over time?
   • Emotional Engagement: Does the product create a deeper connection with the consumer?
   • Situational Relevance: Does it fit the occasions for which it’s intended?

The future of NPD: Rethinking the process

Replacing consumer panels with digital solutions isn’t enough.  We need to think of the entire process. Headspace with its AI tools changes the entire product development process, much like Uber redefined the taxi industry. Uber didn’t just replace taxis—it changed how people thought about transportation, making it faster, more accessible, and more personalized. Similarly, Headspace isn’t specifically about “no more consumer panels.” It’s about enabling faster, smarter, and more collaborative innovation across industries. It is about making predictable product innovation a reality.

Here's how: 

1. R&D becomes agile and data-driven                                                  
   

   With Headspace, product development no longer depends on months-long consumer panel cycles. Ideas can be tested and validated instantly using digital twins of consumers —virtual representations of your target consumer grounded in diverse, real-world data.

   • Speed: R&D teams can experiment with new concepts rapidly, cutting development time by a factor of 10.
   • Precision: Insights are based on robust, unbiased data, eliminating the guesswork of traditional panels.
     
     
2. Marketing aligns directly with consumers                                      
   
   Marketers no longer need to rely on retrospective insights or speculative surveys. With Headspace, prototypes are evaluated by digital twins in real-world contexts, allowing Marketers to fine-tune messaging, packaging, and positioning before launch.
   
   
   • Efficiency: The time from concept to consumer shrinks dramatically. 
   • Relevance: Campaigns are grounded in real-world insights, ensuring they resonate with target audiences. 
     
     
3. Consumer Insights teams work seamlessly with R&D and Marketing                     
   
   Traditionally siloed, these teams can now collaborate on a single platform, integrating insights from purchase intent, sensory data, and competitive analysis.
    
   • Unified data: Eliminates redundancies and inconsistencies.
   • Holistic approach: Creates a seamless, data-driven product development process.
     

The Headspace revolution: A vision for the future

Imagine a world where launching a product becomes as fast and seamless as updating software.

• R&D teams: Identify trends, test dozens of potential recipes with digital twins in minutes, and launch the winning product in weeks instead of months.
• Marketing teams: Optimize packaging and advertising in real-time, ensuring the product resonates with consumers the moment it hits the shelves.
• Consumer Insights teams: Derive insights from constantly evolving datasets, free from the biases of traditional panels.

This isn’t just about improving speed and cost—it’s about transforming behavior. Just as Uber unlocked new possibilities for mobility, Headspace through predictable product innovation unlocks new ways for companies to innovate, collaborate, and deliver value to consumers.

Why this matters: The end of an era

The 85% failure rate of new products isn’t just a statistic—it’s a symptom of an outdated system that prioritizes control over relevance, speed over precision, and tradition over innovation.

Consumer panels were once the best available method for approximating real consumer feedback. However, they were built on inherent limitations and assumptions that fell short of capturing the full complexity of consumer behavior. Today, with advanced methods and technology like digital twins, we have far superior tools to understand and predict what truly drives consumer decisions.

With Headspace, the industry has the chance to leave these failures behind. By enabling faster, smarter, and more collaborative innovation, Headspace doesn’t just replace consumer panels—it redefines the entire process of product development.

The myth of consumer panels is over. The future is here.