As a CPG supplier or retailer, understanding consumer preferences regarding pack size and the retailer generally buying from is more crucial than ever. It's in niches the rich like. The incremental insight can make a big difference. The decisions around these assortment elements can profoundly impact a brand's success in the market. However, decoding these preferences takes more work. It requires a nuanced understanding of consumer behavior, aided significantly by data insights.

The Challenge of Deciphering Consumer Preferences

Consumer preferences are highly diverse and constantly changing across brands, retail channels, and different pack sizes. For example, the conventional 12-ounce can has been a standard packaging size for energy drinks at convenience stores. However, it is unclear whether this is what consumers prefer or if it is simply what they have been offered. Retailers and manufacturers need help answering such questions because of the limited store-level insights. They often rely on syndicated customer research or shopper panel data, which may not provide a comprehensive or glandular picture of consumer behavior.

The Role of Store-Level Data Insights

Enter the world of data analytics. With technological advancements, particularly in machine learning and AI, companies now have tools to delve deeper into consumer behavior. Products like HIVERY Curate exemplify how data insights can be leveraged to understand and predict consumer preferences. Using data at the store level and machine learning models that are trained to understand the specific category and real-world contraints gives CPG suppliers the opportunity to:

1. Understanding Pack Size Dynamics: Data analytics can help brands understand how different pack sizes perform in various retail environments. By analyzing sales data, companies can discern which sizes are more popular and under what circumstances.
   
2. Assortment Optimization: Beyond pack sizes, the overall product assortment is crucial. Data insights can help brands determine which products to keep on shelves and which to replace - a decision that has significant implications for both sales and customer satisfaction.
   
3. Customized Consumer Experiences: Leveraging data allows for a more tailored approach to consumer preferences. Analytics can identify trends and preferences at a granular level, enabling brands to cater to specific demographics or even individual stores.

The Impact of Omni-Channel & Store-level Data

The rise of e-commerce has added another layer of complexity to understanding consumer preferences. Using store-level data can enable CPG suppliers to discover omnichannel insights into what consumers buy and how they interact with brands across different platforms at the granular level. This data is invaluable in creating a cohesive strategy that aligns with online and physical store consumer habits.

Leveraging data insights to decode consumer preferences in pack size and product assortment is beneficial and essential in today’s competitive market. As retail and CPG companies navigate these challenges, tools like HIVERY Curate are indispensable. They provide the insights needed to make informed decisions and offer a glimpse into the future of consumer behavior. With the right data, brands can stay ahead of the curve, ensuring they meet their customers’ needs in a dynamic and ever-changing marketplace.

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