NIQ says:

“AI’s potential to automate data collection is nothing short of transformative.

Data lakes, the reservoirs of vast information, have become foundational tools, setting new standards for information processing. Beyond data collection, the “sweet spot” really comes with the integration and enriching of data. It’s about transforming raw and previously siloed data into actionable insights. AI plays a pivotal role in this transformation, making the process more efficient and less labor intensive.

While AI offers unmatched potential to extract insights from countless data points, we at NIQ believe that the emphasis must remain on data quality and depth and breadth of data. For CPG and retail players, let it be clear that the sheer volume of data should not be a singular focus; data quality will be the X factor. At NIQ, a principle we steadfastly uphold is this: the caliber of AI’s insights is intrinsically linked to the quality of data it receives. Should CPG and retail brands compromise on data quality, their AI-driven insights will reflect that shortcoming, risking ill-informed strategies. In essence, without prioritizing top-notch data, they risk entering the “garbage in, garbage out” trap.

Operating with inaccurate or incomplete data sets poses a significant challenge, especially in an environment where numerous brands report only a 50–60% data accuracy level. In contrast, NIQ boasts a remarkable 90% accuracy rate. It’s essential for CPG and Retail companies to critically evaluate whether their confidence in their data inputs is substantial enough to support their future business decisions.”

Troy Treangen, Chief Product Officer, NIQ  

NIQ says:

“We wholeheartedly believe that CPG and Retailers should leverage AI for Data Quality Assurance. Yet, the true value lies in the depth, granularity, and quality of the data utilized.
At NIQ, our extensive experience with AI and Machine Learning has underscored the importance of not just harnessing data but refining its quality continuously. Our vast library of reference data, unmatched in its comprehensiveness for CPG and retailers, sets the gold standard for ensuring precision and reliability in our insights.

Central to our approach is AI-driven automation for detecting and rectifying data discrepancies. This is not just a passive, one-off process but an approach that is active and continuous. Our AI algorithms are designed to automatically scan through massive volumes of data, pinpointing anomalies and inconsistencies with remarkable accuracy. This automated detection and correction mechanism is a critical component to Data Quality Assurance.

This automation offers a wide range of advantages for CPG and Retailers. Firstly, it significantly optimizes people-powered resources. By automating the tedious and error-prone process of data verification, CPG and Retail team members are free to focus on higher-value tasks. Secondly, it reduces inconsistencies in data, ensuring that decisions are based on reliable and up-to-date information. This reliability is paramount in a landscape where data-driven decisions can make or break market success.

Undeniably, the transformative potential of AI’s continuous learning promises to elevate Data Quality Assurance. With data quality front and center and at the top of our list, the path forward for CPG and Retailers is not just about adopting the right tools but ensuring these tools evolve through the richest data sources.”

Troy Treangen, Chief Product Officer, NIQ  

NIQ says:

“To thrive in today’s competitive landscape, it’s crucial to stay a few steps ahead. Companies are increasingly harnessing AI and Machine Learning (ML) to delve into comprehensive data sets, streamlining production, predicting demand, and enhancing inventory management. Those proficiently using ML for demand forecasting position themselves to not only meet but anticipate consumer needs, optimizing their supply chains and augmenting profitability.

Consider this: tasks that once took months of forecasting, planning, and executing now unfold within moments. The focus isn’t just on meeting consumer expectations but preemptively gauging their next move.

For CPG and Retailers, in practice, NIQ’s global RMS data, rich with historical sales insights, offers a robust foundation for model training. By analyzing years of this data, the models can discern subtle trends and consistent patterns, laying a solid groundwork for precise demand forecasts.

Yet, mere reliance on past patterns doesn’t cut it, given the swift evolution in consumer behaviors. ML models are engineered to constantly assimilate and decode new market data, capturing real-time shifts in consumer preferences across the omni landscape, market entries by rivals, and significant global economic shifts.

Seasonality, from prominent holidays to regional festivals, also plays a pivotal role in demand dynamics. Advanced ML models factor in these elements, adjusting predictions using a blend of real-time panel data and historical patterns, while also peering into forthcoming market developments.

Furthermore, beyond basic forecasting, companies employ ML to simulate scenarios stemming from potential market changes. Imagine an ML model forecasting the repercussions of a rival product’s debut, a likely supply chain hiccup, or the rollout of an innovative marketing strategy.

World class CPG and Retailers are grounding their modern ML models in quality data with the recognition that continuous learning is occurring. With every new data piece, the right and most powerful models recalibrate, fine-tune their predictions, and bring forth strategic pathways, grounded in the most up-to-date insights, available.”

Troy Treangen, Chief Product Officer, NIQ  

NIQ says:

“In light of recent and enduring inventory and supply chain challenges faced by CPG and Retailers, the role of AI in inventory optimization cannot be stressed enough. AI-driven inventory management systems have emerged as indispensable tools in navigating the intricate waters of today’s dynamic business environment.

The last three years alone have seen numerous shelf stock disruptions across channels and categories. Each incident was characterized by a blend of supply deficits and a sudden wave of demand, frequently exacerbated by news coverage and visible stock shortages captured on social media.

While consumer stockpiling, or “pantry-loading,” can sometimes result from promotional strategies, unexpected shortages drive a fundamentally different kind of consumer behavior, one that can be challenging to anticipate but can be mitigated with the right data insights.

Such shifts spell complexities for retailers—from lost clientele due to stock unavailability to challenges in promotion and pricing dynamics. Herein lies the essence of an AI-anchored inventory management strategy, rich in the ability to uncover unforeseen data insights.

At NIQ, we regard on-shelf availability (OSA) as the linchpin of business acumen for CPG retailers. Tapping into our expansive shopper behavior data, retailers can discern early pantry-loading patterns, laying the groundwork for proactive maneuvers. This extends to timely ordering tweaks, promotional recalibrations, pricing adaptations, and optimized shelf assortments. Our real-time insights into stock conditions ensure retailers pivot swiftly, equipped with factual on-shelf product data crucial for sound category and promotion planning.

For CPG and Retailers, using data-driven tools like AI for inventory management is crucial. The integration of AI technology with top-tier inventory management data leads to reduced carrying costs, prevents overstocking or understocking, and minimizes product wastage. This combination results in a more resilient and efficient supply chain. By leveraging NIQ’s supply chain and on-shelf availability insights, aligned with data on customer demand, product variety, and pricing, businesses can gain a better understanding of market shifts. This ensures optimal inventory levels and enhances the consumer shopping experience.”

Jean-Baptiste Delabre, VP, Retail Analytics,

NIQ says:

“Imagine a world where companies are able to better meet, understand and anticipate the needs of consumers. AI doesn’t just predict consumer demands across various categories but also pinpoints how competitors respond to these trends, dissecting them by region and unveiling their global repercussions. In this envisioned world, Natural Language Processing (NLP) evolves beyond its conventional scope of skimming social media, news, and reviews for immediate consumer sentiments. At NIQ, we are at the forefront of this evolution, harnessing the power of NLP and blending it seamlessly with our extensive global consumer data.

The true strength of this approach emerges in the union of AI, including NLP, with datasets from NIQ. This merger does more than reveal “what” consumers are doing; it provides a window into the “why?” behind their behaviors. By intertwining AI with data such as panel data, we offer brands insights into complex consumer patterns and the driving forces behind their decisions. This formidable alliance empowers brands to detect and respond to market trends with unparalleled accuracy. It enables them to not just fulfill current consumer demands but also to understand them. Truly delivering on the Full View. This is the transformative journey we’re pioneering at NIQ, equipping brands to navigate the market landscape with an unmatched level of foresight and adaptability”

Pascal Sauve, Head of Emerging Technologies, NIQ