Data topics

Most CPG teams can see that market share moved, but not why—because they rely on slow, manual “share analysis” that stops at charts instead of diagnosis. The blog explains how proper market share decomposition should break a change into concrete drivers (distribution, velocity, price/mix, and competitive moves) at retailer, region, and segment level, instead of confusing simple correlations or national averages with true attribution. It shows how AI automates the hard parts—data integration, baseline modeling, and competitive tracking—so brand managers can ask “Why did share drop at Kroger last month?” and instantly see quantified drivers and recommended actions. With this always-on decomposition, teams move from week-long investigations and stale insights to fast, retailer-specific decisions that actually recover and grow share.

AI agents are not a “nice-to-have”; they’re a must-have if you want to break free from analysis paralysis, truly democratize data-driven decision-making, and scale your analytics across hundreds (or thousands) of business users. The real promise of data democratization is not just in enabling more people to ask questions, but in enabling those questions to be answered comprehensively and autonomously.

The next era of analytics is goal-driven, adaptive, and intelligent. Tellius brings this to life by combining deep analytics with conversational intelligence, multi-agent reasoning, and business-aware feedback loops. It’s not about replacing analysts—it’s about scaling intelligence across your business with a system that gets smarter every day.