Powerful solutions for more loyal shoppers

Link information from all of key systems into one powerful platform that is continuously updated and available to everyone in your organisation and, optionally, to manufacturers. Quickly identify specific shopper, sales, promotion, distribution and cross-purchase opportunities to grow sales and drive loyalty.

• Point-of-sale can be augmented by loyalty, supply chain weather, economic indicators and other data assets.
• 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 segment shoppers, dynamically identify trip missions, understand key shopper trends, better target households and track the impact of activation on store performance.

Communicate to the right people with the right content, and measure the impact with our retailer CRM solution.

• Create impactful dynamic content that is relevant for your shoppers.
• Measure the impact of campaigns in near real time.

Profile baskets, customers or stores based on behaviour and attitudes, including toward specific custom client views, to match to a client’s own proprietary segmented databases.

• Segmentation solutions based on retail transactional data profile baskets, customers or stores based on attitudes toward major shopping trends, including the economy, technology, health care, aging, and nutritional and eating habits, and consumption/usage behaviour among key segments.
• Timely segmentations help marketers understand how a particular trend or issue affects their trip missions, target group costumers and stores.

Access robust modelling to optimise 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 maximise sales.
• Understand what types of items and product attributes have the most incremental impact on the category and what types drive the most cannibalisation.
• 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.