AI Strategy for Consumer Packaged Goods (CPG) with focus on Recommender Systems

In today’s fiercely competitive Consumer Packaged Goods (CPG) industry, success hinges on strategic advantage. This article explores the pivotal role of advanced CPG analytics and AI, shedding light on how these tools can empower CPG companies to drive growth, enhance efficiency, and deliver personalized experiences. Dive into the world of data-driven strategies that are reshaping the post-pandemic CPG landscape.

Rahul S
6 min readSep 15

--

The consumer-packaged goods (CPG) industry is fiercely competitive, demanding a strategic advantage. Even more today, in a post-pandemic world, advanced CPG analytics and AI have emerged as crucial tools for success.

1. POWER OF CPG ANALYTICS

Let’s delve into seven ways CPGs can harness the power of data to drive growth and profitability.

Pricing Strategy Optimization: We use historical sales data to identify price elasticity. From AI perspective, we deploy AI/ML models to predict the impact of price changes on sales volume for informed decision-making.

Enhance Supply Chain Efficiency: CPG data insights are used to identify bottlenecks, reduce lead times, and minimize inventory costs. The idea is to integrate AI for optimizing supply chain operations, anticipating disruptions, and predicting demand patterns.

Improve Product Development: Advanced CPG analytics helps us discover consumer preferences and emerging trends. So, we can develop new products based on CPG data insights, optimizing packaging and environmental impact.

Custom Marketing Strategies: CPG data insights can be used to segment your consumer base. We have to analyze purchasing patterns and demographics for targeted marketing. And for that we can leverage AI for data-driven personalization and increase in marketing ROI.

Assess and Monitor Competitor Activity: AI helps us analyze SKU data, inventories, consumer perception, and marketing campaigns; and in…

--

--

Rahul S

I learn as I write | LLM, NLP, Statistics, ML