Help identify optimal offers and placement to execute profitable promotions
IBM® Promotion Optimization is designed to enable retailers to optimize offers and placement to execute more effective and profitable promotion plans. IBM Promotion Optimization is part of End-to-End Promotion Management, a comprehensive solution for managing virtually the entire promotions process, from collaborative promotion planning and deal management to in-flight and post-event analysis. IBM Promotion Optimization uses advanced consumer demand management science to help retailers develop promotional offers and placement that maximize the total store impact across categories.
Develop more profitable promotional plans.
- Make best use of offerings and ad placements to get full advantage of promotional activities
- Take advantage of advanced consumer demand management science to develop promotional offers and placements that maximize the total store impact across categories
Maximize the incremental lift and total store impact of promotions.
- Quickly determine the optimal discounted price for virtually any item or promoted item group with IBM Promotion Optimization
- Calculate the optimal type of temporary price reduction, such as buy one get one, percent off and multiples
- Determine the optimal use of merchandising support (ads, displays and others) as well as specific placement within an ad
Create category plans to help achieve objectives.
- View category plans in a master calendar that provides a single, unified view of planned events across categories
- Access an integrated forecast that shows promotions as well as pricing types
- Using this integrated forecast within IBM Promotion Optimization, ensure that promotions meet company goals
- Continually monitor and measure the results of events, weekly promotions and partial-week promotions
Strategically allocate space in ads and displays using insight into lift from various tactics.
- Use IBM Promotion Optimization to create alternate scenarios to see what could happen if the ads or displays were changed
- Compare multiple iterations of various promotions to identify the right combination of discount and merchandising support
- Analyze pull-through effects, cannibalization between promoted items and regularly priced items, cannibalization between stacked promotions, and the pantry-loading effects of successive promotions
- Access analytics and recommend a product or price based on specific goals — such as volume, margin or revenue — that are set for the event and category