How Black Swan Powers Nestlé’s Foresight Capability

How Black Swan Powers Nestlé’s Foresight Capability

By Hugo Amos 

At IIEX Europe 2024, I was very lucky to be joined on stage by Ritanbara Mundrey, Global Head of Innovation & Insights at Nestlé Dairy. We discussed how Black Swan’s Social Prediction technology is powering Nestlé’s foresight capability and helping to bring consumers to the heart of innovation. 

Events like IIEX bring together market research (MRX) providers and consumer focused businesses on the hunt for cutting-edge insights. I’ve attended conferences across the globe over the last year. And everybody’s talking about AI. It’s the buzzword at every event. By now, most MRX providers have infused AI into their technologies and methodologies in some way.  

So how does a global business like Nestlé choose between the dozens of vendors? How do they determine which vendor has the underlying data-quality and know-how to successfully harness AI for new product innovation? And what new uses cases and capabilities has this unlocked for Nestlé's Global Dairy Team?

Nestlé is the world’s biggest CPG. Unsurprisingly, they had no shortage of trends and trend reports at their disposal. In fact, they had too many trends. As Ritanbara explained, they were overwhelmed by a deluge of reports with no clear data-based guidance on where to place their bets. 

They needed to find a partner that could help them predict and prioritize the trends in a way that would make business sense for Nestlé.  

Ritanbara was also clear that they didn’t want just another platform built by technologists. They were looking for cutting-edge technology topped with human expertize.  

This combo would help the Dairy Team make better, more confident innovation decisions.




Why Nestlé chose Black Swan Data 


Nestlé had three core objectives for their foresight capability:  

  • To enhance the centricity of consumers in the innovation journey 
  • To ensure trends permeate and inform R&D product development in daily decision making 
  • To empower the custodians of the categories to accurately identify the “tense of the trends” and win with tomorrow’s trends, today

These objectives lined up perfectly with Black Swan’s offering. Our technology applies AI and predictive analytics to millions of social and online data points to understand long-term behavioral trends. It captures every relevant category conversation topic being spoken about, meaning you never get blindsided by an unseen trend again.  

And it connects and predicts emerging future consumer needs with 89% accuracy, helping to fuel the innovation process with robust, scientific metrics that aid decision making. 

Brands leverage this data through our platform and consultancy solutions. The combination of consultancy and access to our platform meant the Dairy Team could utilize our consultants for deep-dive analysis on specific opportunity areas. While having an always-on, self-serve source of trend intelligence to monitor the landscape and feed into key innovation decisions, as and when required.

 



Re-activating Nestlé’s demand frameworks 


The Black Swan x Nestlé Dairy partnership was launched in 2023. It began with a demand space mapping project. Their demand frameworks needed a refresh and more granularity to make them actionable for innovation teams.  

So we mapped our data containing 10,000’s of micro-level, trending topics onto Nestlé’s framework. This infused real-time, consumer trends into their demand spaces, and helped uncover whitespace opportunities in their target markets. This process was applied across multiple markets. Providing them with a global and localized view of consumer behavior.  

This piece of work was the foundation of our partnership. We then went to work on developing strategies for activating the opportunities in each specific demand space.




Analyzing product and marketing mix decisions 


Ritanbara went on to discuss how Black Swan helped her team unpack and understand consumer preferences for different product formats. In this case, Powder versus Liquid in the beverages category. Nestlé wanted to understand the key benefits and drawbacks that consumers associate with each format. 

Ritanbara spoke to the importance of tapping into naturally occurring consumer conversation. She believes insights from real consumers on-the-ground should drive key innovation decisions.  

Using our data, Nestlé was able to look at this product format question from both a 30,000 and 3-foot view.  

To understand the wider context, they analyzed thousands of consumer conversations across Instagram, TikTok, X and 100+ other online and social sources. This identified and helped prioritize consumer tension-points and opportunities.  

On finding a focus area, her team were able to look at individual consumer posts and dialogues to understand actual verbatim, sentiment and emotions. It helped them understand ‘the why’ behind their purchasing behavior and illustrates how flexible social intelligence can offer both quantitative and qualitative solutions.




Concept optimization  


Finally, Ritanbara and I walked through a concept optimization use case, specifically for one of Nestlé Dairy’s Brazilian brands.  

Before moving into concept testing, Nestlé used our social data to optimize the benefits, themes, and ingredients in the original product concept versus our top predicted trends in each space. This ensured they were better aligned with the consumer preferences that are forecasted to grow in the future.  

It allowed Nestlé to test fewer concepts more successfully, and ultimately launch products that consumers will want to buy on shelf. 

This approach also helped one of our customers in the beverages category generate $64 million in ROI through optimizing concepts. You can discover how we enhanced five underperforming concepts HERE.





I'd like to thank Ritanbara for joining us in Amsterdam for IIEX. And for joining me on-stage to discuss our partnership.  

We are incredibly proud to be working with her and the Nestlé Dairy team and look forward to the projects ahead.