FEATURES
determine vendor rebates while placing an order, assuring optimized rebates and cash flow.
Speed Decisions That Affect the Business Real-time information lets users focus on processes
that accelerate revenue generation and brand loyalty. Personalized, targeted or cross-sell offers are enabled based on items already in shopping baskets. After a return or complaint is received, one can quickly discern whether others have had the same problem. (Alternatively, this customer has complained many times and needs special attention to avoid a negative experience.) In-memory computing can also improve location-specific pricing—for example, by analyzing sales of perishables midday to determine if a markdown is needed to maximize margins.
Simplify and Unify Business Processes Sophisticated real-time data analysis reduces
complexity and opens up new avenues to excite customers and increase competitive differentiation. Orders can be fulfilled based on enterprise-wide stock availability, maximizing a positive shopper experience and satisfaction across sales channels. A noteworthy application for in-memory computing is inventory management in multichannel retailing (including online and in-store sales), where retailers often struggle to get up-to-date inventory information. A consumer might order a camera online, choosing to pick it up at a local store. Or, if a consumer is in the store and the camera is out of stock, a salesperson could find it at another store for immediate pickup or have it delivered to the customer’s home.
Precision Retailing Using In-Memory to Support Precision Retailing As demonstrated in the opening scenario, SAP
Precision Retailing seeks to influence in-store buying decisions via one-to-one marketing and special offers based on past purchases and identified preferences. It requires an in-memory, analytics-driven approach to improve product assortments, pricing and promotions. Many Web retailers already use real-time visibility into
a shopper’s “search-and-decide” process to customize sites and offer products and services to fit specific interests. For example, with dynamic preferencing, an online retailer can change how a shopper navigates, offering personalized promotions and recommending additional products based on viewing history. In-memory computing makes a similar personalization process possible in the store. Retailers can analyze market
INTERNATIONAL COUNCIL OF SHOPPING CENTERS 33 4
research, product ratings, previous purchase history, loyalty programs, and lifestyle choices and preferences— then make product recommendations or pitch new offers. A large multi-format food retailer, for example, can
use precision retailing to promote one-to-one customer relationships, aligning consumer lifestyle preferences with the shopping experience. Using an interactive mobile application, the retailer can incorporate personalized product information, special offers and social media to develop an optimized shopping list for each customer. The customer uses the list to manage in-store shopping, while the retailer extends up-sell or cross-sell offers based on fair trade, organic food, gourmet, health or eco- friendly preferences. Shoppers receive product recommendations that
include accessories, private-label alternatives, bestsellers and best-rated products they might not otherwise consider, as well as product-discount or loyalty-program offers. For example, a shopper has an optimized online shopping list in the grocery store. Before she reaches the coffee aisle to purchase her usual brand of ground coffee, she is offered a promotion for a fair-trade organic brand at a slightly lower price point. Since she prefers to buy fair-trade products when she can, she opts to purchase the new brand. The store’s promotion is successful.
Moving Forward With In-Memory Computing To benefit fully from in-memory computing, retailers
should assess in-memory opportunities, build a solid technical foundation, and then use in-memory scenarios to fully transform the organization. (See Figure 6-2).
Figure 6-2 Getting Started With In-Memory Computing
Source: SAP Precision RETAIL PROPERTY INSIGHTS VOL. 20, NO. 1, 2013
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