NIQ says:

“In the realm of personalization—it’s all about understanding the consumer and consumer needs. Panel data is at the heart of understanding consumers. Personalization in CPG and retail hinges on detailed consumer insights, typically gleaned from Consumer Panel Services (CPS) which consists of a community of consumer panel members who have agreed to share their purchase data information. Through our panel measurement, we are able to track home and out-of-home purchases and provide data on household demographics and consumer behavior.

The future of panel data, augmented by AI, promises even greater precision in understanding consumer behavior. AI-enhanced, synthetic panels will enable companies to simulate respondent demographics. However, these synthetic panel models can only be built on richly accurate, integrated, informed data points — such as deep historical panel data, historic sales data (to provide context of what has driven dollar sales), and extensive global coverage across regions and demographics. This comprehensive approach allows for the creation of highly accurate consumer profiles, leading to more effective personalized product creation, recommendations and marketing strategies

Foundationally, AI-enhanced, synthetic panels should be built on a foundation of robust and reliable data.

By tapping into powerful AI to analyze complex and varied data, CPG and retail data providers can offer insights that are not only deeper but also actionable, paving the way for products and services that closely align with evolving consumer preferences. This has the potential to not only drive sales, it enables companies to truly win over consumers — enhancing brand loyalty, making personalization through AI an indispensable tool in the modern CPG and retail landscape.”

Kris Ewing, President, Global CPS, NIQ 

NIQ says:

“Breakthrough innovation sits at the intersection of great ideas colliding across categories. AI’s ability to canvas and synthesize information, generating infinite combinations of product ideas, attributes, or even usage occasions, is already helping manufacturers jumpstart the creative process and optimize product offerings. It can be used to brainstorm new concepts, expand on ideas, and fine-tune product details and messaging.

Leveraging our access to the world’s richest behavioral and transactional data that reflects real-time purchase activity by consumers around the globe, our proprietary AI tools using humans-in-the-loop are already helping manufacturers refine product features, benefits, and formulations to deeply resonate with targeted consumers. NIQ’s BASES Optimizer is a reinforcement learning system that uses multi-participant, interactive, evolutionary computation techniques to generate highly preferred bundles of product attributes in real time. BASES Creative Product AI is a breakthrough solution in the sensory space with multiple capabilities — predicting the appeal of formulation in different geographies, recommending modifications to existing formulations, and generating novel formulations with high appeal for specific categories and consumer segments.

The advent of Generative AI is rapidly opening even more possibilities for innovators, with potential applications for data collection, open-ended analytics, ideation, and desk research, to name just a few. Our data access, along with responsible experimentation practices, offer unparalleled insights into the exciting potential of AI-driven product innovation that goes beyond the hype.”

Ramon Melgarejo, Managing Director, NIQ BASES and Global Analytics

NIQ says:

“We recognize the crucial role of AI in revolutionizing pricing strategies in the CPG and retail sector. Without question, AI’s capability to process real-time data is pivotal in navigating the complexities of today’s market, from inflationary trends to competitive pricing pressures. Integrating AI-driven predictive analytics allows for a more nuanced, consumer-focused approach to pricing, enhancing both personalization and efficiency. Notably, this aligns pricing with promotional strategies and ensures these strategies are scalable and effective across diverse product lines. Ultimately, leveraging AI in price optimization is about maximizing profitability while staying attuned to the dynamic needs of the consumer and market conditions.

AI has the potential to revolutionize how CPG and retail sectors approach dynamic pricing, with good data at the center of this transformation. Data is critical for understanding promotion price elasticity — it reveals how much flexibility there is to price promotions for optimized performance. Good data in the CPG space identifies degrees of elasticity and the ideal times for promotion.

By automating the analysis of promotional data, AI enables companies to efficiently evaluate promo and non-promo volumes over extensive periods, such as 52-week cycles, providing critical insights into the effectiveness of various promotions. AI’s continuous monitoring of market dynamics on a weekly basis offers a comprehensive understanding of share shifts influenced by competition and broader economic factors like inflation or geopolitical events. This leads to a more informed strategy for pricing and promotions. Additionally, AI’s capability to assess ROI for each promotion equips sales teams with rapid, data-driven tools to enhance decision-making and compliance. These AI-driven approaches can significantly evolve dynamic pricing strategies in CPG and retail, making them more responsive and effective in a rapidly changing market environment.

In practice, imagine a world where a grocery retailer uses AI to dynamically price fresh produce. The AI system analyzes data points like seasonal availability, competitor pricing, and consumer buying patterns. For instance, as strawberry season peaks and supply increases, the AI adjusts the prices lower to encourage quick sales, preventing waste. Conversely, if an unexpected frost impacts the strawberry supply or competitors increase their prices, the AI responds by raising prices carefully. This precise, responsive pricing strategy, enabled by AI, ensures the store remains competitive, maximizes profitability, and aligns with consumer demand and market conditions.”

Steve Zurek, VP of Advanced Analytics, U.S. Thought Leadership, NIQ  

NIQ says:

“Integrating AI into operational strategies, particularly in supply chain optimization, is no longer just an option for CPG and Retailers; it’s a necessity. AI brings a new level of sophistication to supply chain management through enhanced route planning, accurate demand forecasting, and streamlined inventory management. This not only curtails costs but also amplifies overall efficiency. Embracing AI, businesses can nimbly adjust to market fluctuations, ensuring effective inventory control and reducing challenges like stock imbalances. Partnering AI with in-depth data insights, exemplified by NIQ’s offerings, empowers companies to cultivate a robust, effective supply chain, guaranteeing ideal inventory levels and enriching the consumer experience.

Furthermore, NIQ’s Precision Areas, harnessing groundbreaking data science and diverse datasets, facilitates precise, localized strategies, thereby refining inventory distribution and execution. When this type of data is used to inform AI-driven insights, companies are given a significant leap in supply chain optimization and competitive strategy for CPG and Retailers.

It should also be noted that the strategic implementation of clean rooms has become a focal point in data analytics conversations. These secure, digital environments enable the processing and analysis of sensitive data without revealing it to users. By allowing amalgamation while ensuring privacy, clean rooms prove invaluable, particularly in handling sensitive financial or personal information. This method unlocks potent insights, compliant with data privacy regulations and safeguarding proprietary data.”

Pascal Sauve, Head of Emerging Technologies, NIQ

NIQ says:

“In the realm of CPG and Retail, leveraging AI for Risk Management is a strategic imperative. By integrating AI into risk management strategies, CPG and Retail data providers can safeguard their operations against unforeseen variables, ensuring a more stable, resilient business model that is adept at navigating the uncertainties of today’s market. That said, incorporating AI for Risk Management in CPG and Retail becomes even more potent when combined with the use of clean rooms. These secure environments allow for the safe analysis of crucial data, such as financial information, without exposing sensitive details. By integrating sensitive data into AI models within clean rooms, companies can gain deeper insights for risk assessment and mitigation. This approach not only protects sensitive data but also enhances the AI’s ability to identify and manage potential supply chain disruptions and market fluctuations, offering a robust and confidential solution to manage risks more effectively.”

Pascal Sauve, Head of Emerging Technologies, NIQ