Mastering Assortment Price Pack Architecture: How AI streamlines product development & distribution across multiple retailers.
In the dynamic and competitive world of retail, Consumer Packaged Goods (CPG) brands are constantly seeking ways to protect their brand portfolio and help grow the retailers' category. AI is becoming an indispensable tool for CPG brands to find new incremental growth. With the power of store-level insights, AI offers retailers innovative assortment strategies. This blog post will explore how leading CPG brands have leveraged AI capabilities to inform price pack architecture and optimize their product portfolios across multiple retailers.
AI empowers retailers and CPG brands to harness store-level shopper data, providing valuable insights into consumer behavior and preferences. Its advanced AI algorithms facilitate rapid assortment strategy evaluations, enabling businesses to create locally relevant, efficiently merchandised, and operationally streamlined plans. This powerful tool has allowed leading CPG brands to optimize their portfolios across various retailers, making informed decisions that drive retail success.
Informing Price Pack Architecture with AI by Retailer
In any given retailer, such as Walmart, Target, and Dollar General, the role of pack size by brand varies. Our analysis of many CPG brands has discovered that certain brands and pack size combinations are important to different retailers. For example, with one client, we found that large packs were vital at Target, while Dollar General shoppers preferred smaller packs, and Walmart dominated most with one type of pack size. With this discovery, our AI model can run space-aware strategies to create ideal category plans for different retailers, growing revenue and volume equally while considering our client's brand portfolio by retailer. Discoveries like this have opened the door to gaining insights into specific distributors. In other words, AI enables us to ask not whether we need to make changes but rather what is the ideal mix.
Leading CPG brands have utilized AI to analyze their categories and product brands across multiple retailers. By running unlimited rapid simulations, these brands have gained a deeper understanding of the financial impact of their assortment and space decisions. This valuable information has informed their price pack architecture strategies, allowing them to optimize their product mix and maximize profitability.
One notable example is a prominent CPG brand that leveraged HIVERY Curate's capabilities to optimize its product portfolio across various retailers. The brand utilized the tool's data-driven insights to make informed decisions about SKU rationalization, product introduction, and space allocation. As a result, they were able to tailor their price pack architecture to cater to different retail environments and shopper preferences, ultimately driving increased sales and shopper satisfaction.
What does this all mean?
AI-driven models like HIVERY Curate allow businesses to optimize their assortments and reduce supply chain complexities. By leveraging the power of AI, CPG brands can tailor their brand portfolios to each retailer based on unique shopper purchase behavior. This ensures that CPG brands are always locally relevant, efficiently merchandised, and operationally streamlined in their plans by retailer and category.
Connect with our team of experts and explore the benefits of using HIVERY Curate as your reliable co-pilot. Run different supply chain scenarios and see the impact. By leveraging store-specific data, you can reduce supply chain complexities with better assortment plans that cater to local shoppers' preferences and distribution center constraints while streamlining store operations.