5 Ways AI Can Deliver Rapid ROI to Consumer Products Companies

Not long ago, a global consumer products company began applying artificial intelligence- and machine learning-driven tools to its demand plans, promotional strategies and media plans in an effort to uncover new cost savings and revenue growth opportunities. To say the program has been a success would be an understatement. For every $1 the company has invested in the effort, it is realizing a robust $11 of additional revenue.

Set aside for a moment the talk about all the potentially sinister applications of AI, why the technology needs stricter government oversight and how it’s causing workers replacement anxiety, and you’re left with use cases like this that illustrate the real value AI can bring today to a CP company. Yes, there are valid concerns about AI. But they shouldn’t overshadow the immense potential it holds for helping companies better understand consumers, retailer customers, supply chains and their own operations.

For CP companies, tapping that potential starts with putting in place a digital foundation to support AI and ML capabilities, and in the process, saying goodbye to exclusively using the humble spreadsheet, for all the ways it handicaps a business. An integrated enterprise resource planning system should be part of that foundation, for its ability to provide a single version of the truth — a central source of trusted data on consumption, pricing, promotions, product mix, etc., across the business. That foundation also should include a forecasting engine built on predictive modeling capabilities.

See also: Empowering CPGs: Becoming the Smartest in the Room During Joint Business Planning

Once those foundational elements are in place, now you can put your AI capabilities to work. Here are five areas where, in my work supporting CP companies in their revenue growth management programs, I see AI providing the most value:

1. In evaluating and managing trade promotion plans

As much resources as CP companies dedicate to promotional programs —16 to 24% of their gross revenue goes to promotional rebates for retail partners, according to estimates —  60% of trade promotions are not profitable. Given how heavily retail partners depend on them, trade promotions aren’t going away anytime soon.

So CP companies must find ways to make them more profitable. Because CP companies run so many promotions, moving the needle even a little in terms of the bang for the buck these programs provide can mean tens of millions and even hundreds of millions of dollars in additional revenue and profitability. AI tools can provide that magnitude of impact, with their ability to rapidly analyze a company’s promotional plans, then, based on a wide range of data inputs, forecast with a high degree of accuracy which promotions are bound to underperform and which should be most profitable.

Given a series of parameters, AI tools also can provide recommendations on how to strengthen the impact of a promotion, along the lines of “spend more on this type of in-store display” or “run this sunscreen promotion two weeks later, in these specific markets.” To make these types of recommendations as understandable and actionable as possible, you want them delivered by the AI tool in natural language, so account managers don’t have to spend an inordinate amount of time trying to interpret a lot of data. 

2. In shaping pricing strategy

How far can you push pricing without materially impacting demand for a product? AI tools are enabling CP companies to accurately model price elasticity across a vast number of scenarios and amid fast-changing market conditions.

3. In resolving supply chain and scarcity issues

CP companies can only sell what they can make. Not only can AI tools provide them with early insight into potential product, ingredient, component and packaging shortages, and other potential production disruptions, it can recommend optimal replacements in a product assortment for specific geographies and retail outlets, informed by historic sales and demographic data, and recent buying trends.

4. In optimizing price pack architecture

What’s the threshold where consumers will notice a product is being sold at a smaller volume? At what point will offering less of a product without lowering its price impact consumer demand? An AI-powered forecasting engine can provide valuable predictive insight on price pack architecture.

5. In optimizing promotions across channels

With the ability to run multiple parallel scenarios quickly, AI enables the business war-gaming that helps CP companies prioritize promotional spend across multiple channels. Based on an understanding of the interplay between promotions, profitability, demand and cannibalization, for example, it can offer on-target recommendations for how to allocate media campaign and marketing resources across channels for a particular promotion to maximize its profitability. 

For CP companies, AI and ML capabilities such as these are like having a jetpack to propel you in a world where everyone else is crawling, walking or running to get from point to point.  That is, until your competition catches on and realizes they better get a jetpack, too.