Farmstead's Smart Shopping Lists Help Customers with Machine Learning
Laura McQuarrie — May 3, 2019 — Lifestyle
References: farmsteadapp & globenewswire
To help consumers keep their households full of nourishing products, online grocer Farmstead introduced smart shopping lists that use predictive machine learning. This new feature offers customers more than just recommendations, as it uses data on a customer's weekly shopping history, buying signals and items that are already in a cart.
Rather than trying to remember the items on one's list in-store, consumers are able to make use of Farmstead’s Smart Shopping List, which generates a list of personalized products, which will be a mix of old favorites and new products to discover. The smart shopping list is tailored to one's behaviors and wellness preferences, and will be comparable to others who share the same favorite products.
With this new feature, Farmstead is able to make intelligent recommendations based on the day of the week, season and products that pair well together—like bagels and cream cheese.
Rather than trying to remember the items on one's list in-store, consumers are able to make use of Farmstead’s Smart Shopping List, which generates a list of personalized products, which will be a mix of old favorites and new products to discover. The smart shopping list is tailored to one's behaviors and wellness preferences, and will be comparable to others who share the same favorite products.
With this new feature, Farmstead is able to make intelligent recommendations based on the day of the week, season and products that pair well together—like bagels and cream cheese.
Trend Themes
1. Predictive Shopping Lists - Smart shopping lists that use predictive machine learning to offer customers personalized products and recommendations.
2. Behavior-based Recommendations - Using data on a customer's weekly shopping history, buying signals and wellness preferences to make intelligent recommendations.
3. Personalization in E-commerce - Providing personalized experiences to consumers through machine learning and data analytics in online grocery shopping.
Industry Implications
1. E-commerce - Integrating machine learning and data analytics in online grocery shopping for personalized experiences.
2. Retail - Utilizing predictive machine learning to make intelligent recommendations based on consumer behavior and preferences.
3. Food and Beverage - Offering personalized product recommendations and shopping experiences to consumers through predictive machine learning and data analytics in an online grocery store.
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