Price Optimization

Learn how consumer goods companies can use AI-based pricing models to adapt to consumer behavior and improve sales and profitability while navigating challenges like consumer trust and data accuracy.

At its core, PPA is not about pack resizing for its own sake. It is about engineering product formats that align with how consumers perceive value, shop across channels and evolve their usage behaviors in response to economic pressure.

While advancements in consumer insights have provided CPG brands and retailers with a looking glass of the drivers behind shopper behavior and trends, the image can be sharpened and personalized using merchandising tactics that fuse data and AI to truly embrace the why, the how, the when — and even the will do — of consumer actions and motivation.

Brands can no longer afford to ignore fragmented RGM processes. Learn how they can more effectively leverage all the data at their disposal.

Tim Schneider, head of sales engineering at Buynomics, shares his insights on how CPG companies can benefit from this shift, offering a deeper understanding of the challenges and opportunities that come with unifying pricing, promotions, trade spend, and assortment strategies.

For a company like Diageo that relies heavily on cross-border sourcing and production practices, the potential impact of tariffs on partnering countries poses considerable volatility.

Traditional RGM approaches have limitations in today's dynamic marketplace. Learn how companies can optimize efforts to shift from reactive pricing to proactive strategies.

A survey of 303 U.S. consumers conducted in October found that 68% reported that dynamic pricing made them feel like they were taken advantage of. Learn more.