Personalize the shopper experience to boost sales.

Quickly identify specific shopper, sales, promotion, distribution and cross-purchase opportunities and grow sales more than non-gateway retailers.

• Point-of-sale and panel data is augmented by loyalty, supply chain weather/gas and other data assets, along with trip and customer segmentation modeling.
• Retailers and manufacturers can look at the same category and shopper information to enable faster and better decisions, and more easily create win-win scenarios.
• Leverage best-in-class analytics across data assets to understand key shopper trends, better target households and track the impact of activation on store performance.

Access robust modeling to optimize everyday prices and plan effective promotions – in real time.

• Gain a deeper understanding of historical performance, current market dynamics and shopper preferences to develop a more robust go-to-market approach for pricing and promotion.
• Align objectives and success criteria based on robust analytics that include decision-support tools, prescriptive analytic capabilities and machine-learning algorithms that make sense of big data.
• Simulate the possibilities with scenario planning, which offers an accurate understanding of expected impact and associated trade-offs.

Boost store and category sales at scale with the right products on the right shelves.

• For each category, and even each shopper segment, understand which items should be removed, which should be added and which should be replaced from a shelf set to maximize sales.
• Understand what types of items and product attributes have the most incremental impact on the category and what types drive the most cannibalization.
• Determine how to make the shelf more productive by better aligning shelf space to current and potential demand, and understanding how assortments should vary by region or store group.