Kantar Retail offers a robust portfolio of analytics and tools around Promotional Leadership, designed to enable our clients to best improve trade strategy and productivity for their business. Ranging from tactical promotional principles around specific products groups, to strategic endeavors around the role of Trade in consumer behavior, the outcomes of this data-driven offering address a wide spectrum of critical business questions arising from a competitive retail landscape.

The primary business goals for which Kantar Retail’s Promotion offer provides solutions are:

  1. Maximizing Promotion Efficiency and Effectiveness
  2. Developing Promotional Strategy around Consumer Behaviour
  3. Integrating and Expediting Promotional Analysis through Promo360

Promo360 serves as a powerful, flexible component of our clients’ toolkit, as they approach and negotiate with their customers. It provides a simple mechanism to import new data, build a Trade library, include external consumer and company metrics, and export results as visually compelling outputs.

In summary, Kantar Retail’s proprietary solutions enable our clients to take control of their promotional activity, and efficiently analyze returns in order to optimize their trade budget.

Promo360 Kantar Retail Analytics
Key Features
  • Promotion Lift Decomposition
    Lift Decomposition
    Understand who are your early buyers, net loaders and new buyers
  • Promotion Cannibalization
    Identify key SKUs and groups where volume is sourced from when running a promotion
  • Graphical Calendar
    Graphical Calendar
    Visually displays a yearly calender that lets you view and plan your promotions effectively
  • Ad-Hoc Reports on Promotion
    Ad-Hoc Reports
    Choose the most relevant insights between multiple reports
  • Net ROI
    Net ROI
    Allows you to determine the net return of your promotional dollar spend and accurately assess its effectiveness
  • Historical Database
    Historical Database
    Allows you to enter all past promotion data in order to accurately forecast future implementations