Plant-Based Milk Sales Data

Plant-Based Milk Sales Data
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Understanding consumer preferences and market trends in the grocery sector, particularly for plant-based milk products, has historically been a challenging endeavor. Before the digital age, firms relied on manual surveys, point-of-sale records, and anecdotal evidence to gauge market demand and consumer behavior. These methods were time-consuming, often inaccurate, and provided data that was quickly outdated. The advent of sensors, the internet, and connected devices, alongside the proliferation of software into many processes, has revolutionized data collection and analysis. This technological evolution has enabled the storage of every transaction and consumer interaction in databases, providing real-time insights into market dynamics.

The importance of data in understanding consumer preferences for plant-based milk products cannot be overstated. Previously, businesses were in the dark, waiting weeks or months to understand changes in consumer behavior. Now, with access to real-time data, companies can quickly adapt to market demands, optimize inventory, and tailor marketing strategies to consumer trends. This shift has not only improved operational efficiency but also enhanced the ability to predict future market movements.

Historically, insights into the consumption of plant-based milk products were limited to traditional sales data and consumer surveys. However, the digital transformation has enabled the collection of detailed data, including brand, SKU, pricing, and repeat purchasing behavior, across both physical and online channels. This wealth of data provides a comprehensive view of the market, allowing businesses to make informed decisions and stay ahead of the competition.

The transition from antiquated data collection methods to modern, data-driven approaches has been pivotal for the grocery sector. The ability to track sales and consumer behavior in real time has transformed how businesses understand and respond to market trends. This article will explore how specific categories of datasets can provide better insights into the consumption of plant-based milk products in the US, focusing on brand, SKU, pricing data, and repeat purchasing behavior.

Inventory/Purchasing Data

The advent of inventory/purchasing data has been a game-changer for tracking the sales and distribution of plant-based milk products. This type of data provides granular details about daily inventory, sales, and prices of products down to the SKU- and store-level. Drawn from public sources and tracking changes in publicly displayed inventory statistics at a high frequency, this dataset offers a precise view of what's selling and where. Technology advances in data collection and analysis have enabled the assembly of this data, providing insights into sales trends, price variations, and market share changes among different brands.

Examples of how inventory/purchasing data can be used include:

  • Daily sales tracking of specific brands by state across all stores.
  • Price analysis, including mean price and price variation on a weekly basis.
  • Market share insights, such as week-over-week sales share change between brands.
  • Product ranking, identifying top products for each plant-based milk brand.

This data is invaluable for roles and industries such as retail managers, market researchers, and brand strategists, who rely on accurate and timely data to make informed decisions.

Transaction Data

Transaction data offers another layer of insight into consumer behavior and market trends for plant-based milk products. With high-resolution data at the UPC/SKU level, businesses can gain visibility into long-term household trends and repeat purchasing behavior. This data category includes customer loyalty information and insights into online partnership purchases, providing a comprehensive view of consumer preferences across different retail channels.

Specific uses of transaction data include:

  • Long-term trend analysis, leveraging customer loyalty information.
  • Online purchasing behavior, understanding patterns through online retail partnerships.
  • Repeat purchasing insights, analyzing customer loyalty and brand preference.

Industries such as e-commerce, retail, and consumer goods find transaction data particularly useful for tailoring marketing strategies and optimizing product offerings.

Point of Sale Data

Point of sale (POS) data provides a direct look into consumer purchases at the moment of transaction. Sourced from retailers' EPOS systems, this dataset covers sales in various store types and includes online purchases through major retailers. POS data is an industry standard used by manufacturers and retailers for trading negotiations and offers a historical view of sales trends.

Applications of POS data include:

  • SKU-level sales analysis, providing detailed insights into product performance.
  • Regional sales breakdowns, understanding market dynamics across different areas.
  • Repeat purchase analysis, diving deeper into consumer loyalty and switching behavior.

This data is crucial for roles such as sales managers, market analysts, and product developers, who rely on accurate sales data to drive business strategies.


The importance of data in understanding the consumption of plant-based milk products in the US cannot be overstated. With access to inventory/purchasing data, transaction data, and point of sale data, business professionals can gain comprehensive insights into market trends, consumer behavior, and sales dynamics. This wealth of data enables informed decision-making, allowing businesses to stay competitive in a rapidly evolving market.

As organizations become more data-driven, the ability to discover and leverage relevant data will be critical to success. The future of data in the grocery sector is promising, with potential for new types of data to provide even deeper insights into consumer preferences and market trends. The ability to monetize useful data created over decades will be a key factor in driving innovation and understanding in the industry.


Industries and roles that could benefit from access to data on plant-based milk consumption include investors, consultants, insurance companies, market researchers, and retail managers. Data has transformed these industries by providing insights into consumer preferences, market trends, and sales dynamics. The future may see AI unlocking the value hidden in decades-old documents or modern government filings, further enhancing the ability to understand and predict market movements.

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