3 Ways CPGs Use AI to Increase ROI

Every CPG strives to maximize its return on the money and effort it places into investments. The question is:

Which parts of these investments will drive the biggest and most certain returns?

Optimized category management, assortment planning, and revenue growth management are the key factors to success, profits, and market share.

Don’t take chances on your success – using artificial intelligence to make decisions ensures optimal outcomes. Here’s how CPGs are using it:

1. Category Management

Spend precious technology and data dollars on the product most likely to help you succeed. This means using a solution that continually monitors and uses data to create all outcome scenarios possible.

These scenarios use past, present, and future-possible data to show you and your retail partners which products should be on shelves and at what price.

Key benefits of AI-driven forecasting in category and assortment:

  • Selling the right quantity of product that accounts for upcoming sales, trends, advantage over competitors, and promotions
  • Better optimization of assortment ratios
  • Improved understanding of demand drivers and customer behavior, right down to the SKU level
  • Decreased lost sales / missed sales opportunities
  • Better alignment between products and locations where demand exists
  • Improved GMROI

An AI-based forecasting system, is a focused on the CPG major upgrade to existing systems where brands attempt to manually cluster and define data and patterns. Unsurprisingly, results are often disappointing and lead to lost sales and market share.

Store-level forecasting is a difficult endeavour with traditional systems, especially when CPGs are dealing with millions of possible product, price, and store combinations.

By alleviating the need for so much manual intervention and by accounting for so much information at any given time, artificial intelligence-based forecasting can deliver far more accurate decisions.

2. Revenue Growth Management

Advanced forecasting combines with historic sales with seasonality, trends, product lifecycle effects, and statistically-tested assumptions to improve accuracy. Increased accuracy is the single biggest driver of direct savings, revenue, and total return on
investment. Improvements to revenue growth management will be realised in the following ways:

  • Customized decisions for granular levels such as individual store, SKU, particular time, price elasticity, and demand changes
  • Making optimal pricing decisions to make you more money and take market share away from your competitors
  • Opportunity for improved use of strategic discounting

3. Operational Efficiency

In the face of increasing competition, CPGs are all looking to ensure their products remain a focus over their competitors, and that their retail accounts keep them top of mind.

More accurate simulations for decisions can help CPGs optimize category, assortment, trade fund, and pricing/promotion. This is while ensuring they’re able to offer retailer partners the right discounts and provide exact pricing recommendations for optimal outcomes on either side. It’s important that assortment is accurate at individual store levels, using both micro and macro views for trends, seasons, demand, and changes to ensure customer demands are being served at a granular level. Product imbalances often occur right after seasonal peaks. One of the biggest reasons CPGs fall into this trap is because they’re often forced to act retroactively with top-up
orders, transfers, or pricing changes. Providers such as Insite AI provide highly accurate, data-driven scenario decisions at store levels ahead of time to keep ahead of competitors.

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