How Colgate-Palmolive’s Proprietary Analytics Tools Are Fueling RGM, Media Success

Lisa
Colgate-Palmolive

When it comes to build vs. buy, Colgate-Palmolive says taking certain things in-house is increasing their revenue growth management and media analytics flexibility and scalability.   

An in-house, full-stack application leveraging proprietary algorithms to support their RGM strategy has scaled to the top 30 global markets, said Diana Schildhouse, chief analytics and insights officer, at the Consumer Analyst Group of New York (CAGNY) investors conference last week. 

With built-in predictive price elasticity, scenario planning, and promotion and assortment optimization capabilities, the tech serves up a performance snapshot that in turn enables more precise and surgical actions down to the SKU level.   


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In Brazil and Mexico, integrating the cross-elasticity models and predictive scenario planning into decision making identified more than $110 million in opportunities in 2023, according to the company. 

“We've heard from our teams on the ground just how much value they're seeing out of this analytics both in terms of surfacing revenue opportunities, but also time saved that can be spent on actually actioning the analytics and reacting more quickly to changes in the market rather than spending time on data preparation and visualization,” she noted. 

Schildhouse said they built the algorithms and code in-house to better focus on adaptation and scalability across different market dynamics. 

“We still have partners that we work with in terms of data platforms,” she said. “But in terms of the actual analytical models and the algorithms, we found that for our most important areas, building those in-house with our own team of experts gives us that flexibility to be able to scale more easily than an off-the-shelf solution.” 

Like many, Colgate-Palmolive is exploring generative AI in myriad ways. Among the efforts include internal tools producing product innovation concepts based on proprietary consumer insights, which will be tested with digital consumer twins to increase speed to market. 

Media Analytics Growth

The No. 34 publicly owned consumer goods company has also scaled media analytics across the markets that represent more than 85% of global sales. 

Fueled by machine learning, the tools and strategies are impacting marketing mix modeling, retail media, e-commerce, CRM, and first-party data to optimize spend levels, consumer targeting, and personalization efforts. 

“We've seen consistent double-digit ROI improvement over the last few years, both when we look at overall media ROIs as well as when we break it down by digital ROIs and traditional media ROIs,” Schildhouse said. “We're driving increased effectiveness and efficiency at the same time that we're increasing our advertising spend.” 

As the CPG builds out its data foundation, they’re leaning into data clean rooms. In one example, a data clean room that Schildhouse said was proactively initiated by the Hill Pet Nutrition team with a key specialty retailer is helping reach new audiences through personalized content and precision targeting, as well as increase ROI and household penetration.

Upskilling Marches On

To keep these new initiatives flowing and ready for generative AI, Schildhouse pointed to the company’s Data Literacy & Analytics Academy, an internal upskilling program where employees take courses customized to their function and role. 

Colgate-Palmolive has also brought in around 150 new employees over the last several years to elevate their data science and engineering capabilities, said CEO Noel Wallace

“The key is scale. What we don't want to do is be putting places that are unique to certain markets,” Wallace noted. “And Diana and the team have been very deliberate working with our IT folks and our tech stacks to ensure that what we do, we can then roll out across the world because otherwise, we'll never get the efficiencies.” 

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