Global SKU Tracking Insights

Global SKU Tracking Insights
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At Nomad Data we help you find the right dataset to address these types of needs and more. Sign up today and describe your business use case and you'll be connected with data vendors from our nearly 3000 partners who can address your exact need.


Understanding the intricacies of global markets has always been a complex task, especially when it comes to tracking sales and performance at the SKU level across different regions. Historically, businesses relied on manual counts, periodic surveys, and broad market analyses to gauge product performance. These methods, while useful in their time, offered limited insights and were often outdated by the time they were compiled. Before the digital era, companies operated in a data vacuum, making decisions based on intuition rather than hard facts.

The advent of sensors, the internet, and connected devices has revolutionized data collection, making it possible to gather detailed information in real time. This shift was further accelerated by the proliferation of software solutions that track every transaction and interaction, storing vast amounts of data for analysis. The importance of data in understanding market dynamics cannot be overstated. Where businesses once waited weeks or months to understand changes in consumer behavior, they can now access this information almost instantaneously.

SKU level POS (Point of Sale) data has emerged as a critical tool in this landscape. Sourced from retailers and mapped to specific products and brands, this data offers unprecedented visibility into sales performance across the globe. With coverage spanning multiple continents and years of historical data, businesses can now track trends, identify opportunities, and make informed decisions with a level of precision that was previously unimaginable.

The transition from antiquated data collection methods to modern, digital-driven analytics has opened up new avenues for understanding consumer behavior and market trends. However, accessing and interpreting SKU level POS data requires a nuanced understanding of the various data types and sources available.

In this article, we will explore how different categories of data can help business professionals gain better insights into SKU level sales performance. From marketing intelligence to financial data, we will delve into the history, applications, and potential of each data type to shed light on global market dynamics.

The journey from data scarcity to data abundance has transformed the way businesses operate, making data-driven decision-making the cornerstone of modern commerce. As we explore the various data types, it's important to remember the transformative power of data in unlocking insights and driving business success.

Marketing Intelligence Data

Marketing intelligence has played a pivotal role in understanding consumer behavior and market trends. Historically, this data was gathered through consumer surveys, focus groups, and market analysis, offering a snapshot of consumer preferences and attitudes. However, the advent of digital technology has dramatically expanded the scope and accuracy of marketing intelligence.

Today, marketing intelligence encompasses a wide range of data, including SKU level POS data, which provides detailed insights into product sales and performance. This data is invaluable for businesses looking to track sales trends, understand consumer preferences, and optimize their product offerings. With coverage spanning Europe, North America, Brazil, Australia, and SE Asia, marketing intelligence data offers a global perspective on SKU level sales.

The technology advances that have enabled the collection and analysis of marketing intelligence data include sophisticated POS systems, online sales tracking, and data analytics platforms. These tools have made it possible to gather and interpret vast amounts of data, providing businesses with real-time insights into market dynamics.

The amount of marketing intelligence data available is accelerating, offering businesses an ever-expanding view of the market. This data can be used to:

  • Track sales trends across different regions and time periods.
  • Analyze consumer behavior to identify preferences and purchasing patterns.
  • Optimize product offerings by understanding which products are performing well and which are not.
  • Inform marketing strategies by identifying successful promotions and campaigns.

Examples of how businesses have used marketing intelligence data include identifying emerging market trends, tailoring product offerings to meet consumer demand, and optimizing pricing strategies to maximize sales.

Point of Sale Data

Point of Sale (POS) data is at the heart of understanding SKU level sales performance. This data, which captures every transaction at the retail level, offers a granular view of sales activity, providing insights into consumer purchasing behavior, product popularity, and sales trends.

Historically, POS data was limited to physical sales receipts and manual inventory counts. However, the digital transformation of the retail industry has enabled the collection of detailed POS data, including SKU level information. This data is now used extensively across various industries, including food and beverage, household and personal care, and consumer electronics, to inform decision-making and strategy development.

The technology advances that have facilitated the collection of POS data include advanced POS systems, inventory management software, and data analytics platforms. These tools allow for the real-time tracking of sales data, providing businesses with up-to-date insights into market performance.

The volume of POS data available is growing rapidly, offering businesses a comprehensive view of the retail landscape. This data can be used to:

  • Analyze sales performance at the SKU level across different retailers and regions.
  • Identify sales trends and seasonal variations in consumer purchasing behavior.
  • Optimize inventory management by aligning stock levels with sales patterns.
  • Inform product development by identifying popular features and consumer preferences.

Examples of how businesses have leveraged POS data include optimizing product assortments, improving supply chain efficiency, and developing targeted marketing campaigns.

Financial Data

Financial data provides a different lens through which to view SKU level sales performance. This data, which includes sales figures, revenue, and profitability metrics, offers insights into the financial health of products and brands.

Historically, financial data was gathered through company reports, industry analyses, and market research. However, the availability of real-time financial data, including SKU level sales information, has transformed the way businesses assess product performance.

The technology advances that have enabled the collection of financial data include financial reporting software, data analytics platforms, and POS systems. These tools provide businesses with immediate access to financial metrics, allowing for more informed decision-making.

The amount of financial data available is increasing, offering businesses a detailed view of the financial landscape. This data can be used to:

  • Evaluate product profitability by analyzing sales revenue and cost of goods sold.
  • Assess market potential by comparing sales performance across different regions and categories.
  • Inform pricing strategies by understanding the financial impact of pricing decisions.
  • Guide investment decisions by identifying high-performing products and brands.

Examples of how businesses have used financial data include optimizing pricing models, assessing the viability of new product launches, and evaluating merger and acquisition opportunities.


The importance of data in understanding SKU level sales performance cannot be overstated. From marketing intelligence to POS and financial data, the variety of data types available offers businesses a comprehensive view of the market. Access to this data enables real-time insights, informed decision-making, and strategic planning.

As organizations become more data-driven, the ability to discover and leverage relevant data will be critical to success. The trend towards data monetization also highlights the potential for businesses to unlock new insights from data that has been collected over decades.

Looking to the future, the development of new data types and the application of artificial intelligence (AI) to analyze historical and modern datasets promise to provide even deeper insights into SKU level sales performance. The role of data in understanding market dynamics and driving business success is only set to grow.

In conclusion, the transformation from data scarcity to data abundance has revolutionized the way businesses operate. By harnessing the power of data, companies can gain a competitive edge, optimize their operations, and achieve sustainable growth.


Industries and roles that can benefit from SKU level POS data include investors, consultants, insurance companies, market researchers, and more. These stakeholders face challenges such as understanding market trends, optimizing product offerings, and making informed investment decisions.

Data has transformed these industries by providing detailed insights into consumer behavior, sales performance, and market dynamics. The future of data analysis, particularly with the advent of AI, holds the promise of unlocking even greater value from existing and new datasets.

As businesses continue to navigate the complexities of global markets, the role of data in informing strategy and driving success will only become more critical. The potential for AI to analyze decades-old documents and modern government filings offers a glimpse into the future of data-driven decision-making.

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