Consumer Goods briefing
Consumer Goods' Brands Conquering Data Struggles with Agentic-driven Insights
mTab
· 2 min read
Fast-moving consumer goods brands, like Kimberly-Clark, Procter & Gamble, Colgate-Palmolive and SC Johnson, to name a few, have struggled with fragmented data for decades, ranging from syndicated studies and customer surveys to sales reports and promotional datasets. Siloed data has made it hard for teams to clearly understand market shifts and consumer trends, and to align Product, Sales, Marketing, and Inventory to expand sales and drive innovation.
Reckitt CIO of North America, Varun Kakaria, recently discussed this pressing issue at the CGT Analytics Unite conference, saying, "In this age of AI and algorithms and compute becoming higher, could we use data to better predict?" He pointed to the need for deeper insights from integrated sources like customer datasets, cost reports, Nielsen studies, demographic dashboards, seasonality data and promotional surveys to determine which stores have struggling sales and identify inventory issues.
Industry research indicates messaging misalignment can cost brands two to four equity points annually. Beyond this, data misalignment is contributing to a consumer product failure rate across FMCG of upwards of 85% within 12 months. Brands also struggle with effective inventory management predictions and anticipating product enhancements aligned with changing consumer preferences.
These issues showcase the necessary shift toward AI-driven decision intelligence across the consumer goods sector. As brands navigate a $12 trillion market, maintaining market alignment while addressing local priorities is becoming increasingly important. Brands like Reckitt that embrace AI can expect a 40 to 50% improvement in messaging consistency and a upwards of a 35% increase in product success rates. Beyond this, many brands struggle with out-of-stock predictions at a 10 to 20% accuracy rate. Within months agentic AI can increase this to 45% and even upwards of 75% with optimization.
"Navigating global markets demands deeper insights into both high-level strategy and local execution nuances," explains Mark Lummas, Vice President Customer Success at mTab.ai. "Agentic AI decision intelligence insights offer consumer goods companies smarter, faster decisions across Product, Marketing, Sales and Inventory teams with an ability to predict market shifts."
As an example, mTab unifies brand trackers, consumer surveys, syndicated market studies, sales reports and other siloed datasets to deliver faster insights and increased alignment across markets with early risk detection systems. Consumer goods brands embracing this AI-driven brand intelligence are not only gaining a massive competitive edge and valuable brand equity, but also enhancing the efficacy of their teams and resources.
See why leading global consumer goods brands like Nestlé, Kellanova and Danone trust mTab to unify brand, market, product and consumer datasets to spot positioning risks early and align their product benefits with consumer needs.
