Retail Revenue Management 2.0

Retail revenue management (RRM) emerged when a few vendors brought causal forecasting (price elasticity of demand), business rules maintenance, and optimization to bear on an intractable problem – setting regular, promotional and markdown pricing. RRM vendors have grown up, many have been acquired, and promising new ones have appeared. Solutions have matured, with most complemented by adjacent capabilities: price distribution and execution, trade fund optimization, and calendaring and coordinating campaign and event management.

Let’s call this footprint RRM 1.0. It focuses on product lifecycle pricing – maximizing financial objectives and burnishing a retailer’s price image.
I started covering RRM 11 years ago – the first analyst on the beat. Retail has changed a lot since then. Omni-channel commerce, customer-centricity, localization and personalization were little more than strategic objectives. Mobile phones offered POTS – plain old telephone service. Concepts like the mobile Web, social networks and social media could be found in Silicon Valley business plans and a few collegiate dorm rooms. Google was emerging in first-generation search; its roles in marketing and commerce were business plan milestones. These erstwhile nascent trends now dominate retail.

Today, retailers face the twin perils of bolder, empowered shoppers called “swing shoppers,” once-loyal customers with a sharpened, changed and evolving sense of value, and “scan and scram shoppers,” who are swing shoppers armed with mobile commerce tools at the shelf to compare prices, check product evaluations, and frequently change a purchase intention within arm’s reach of a product.

RRM 1.0 wasn’t designed for these challenges, which are threats to what retailers invested in RRM 1.0 tools to achieve – better financial objectives and differentiated, price-enabled value.

These new challenges require RRM 2.0, which has to manage a second lifecycle, one that includes a customer’s sense of value before, during and after each shopping episode as well as across shopping episodes. This also includes the customer’s lifecycle relationship with the brand.
RRM 2.0 adds hard customer-centric metrics like same-shopper sales and lifetime customer value, and softer ones like social media influence and share of need met.

To drive the distinction between RRM 1.0 and RRM 2.0 home we need to assign precise meanings to promotions and offers. Product promotions serve the objectives of RRM 1.0 by setting prices to the cadence of marketing calendars and seasonal events.

As the graphic “RRM 2.0 Meets Customers’ Lifetime Needs” shows, customer offers serve RRM 2.0 objectives by moving toward the direction of crafting offers that anticipate a customer’s own cadence of concerns and contextualizing offers within them.

To illustrate, take a smartphone or shopping-buddy wielding grocery shopper. Loyalty data says she buys small pack, premium products and displays a price-inelastic preference for organic produce. What she’s scanned into her basket depicts the shopping mission she’s on today. With this information in hand a food retailer should contextualize and present a high-margin upsell or cross-sell she’d be delighted to take. When she does she is a happy customer with a bigger basket and a fatter margin for the retailer. That’s one example of RRM 2.0 in action. Others abound.

Consumer power necessitates, and today’s information assets enable, coordination of product price and customer offer optimization.

Greg Girard is program director, merchandise strategies at IDC Retail Insights, a business unit of International Data Corporation (IDC). He is author of “Business Strategy: The RRM 2.0 Manifesto – Omnichannel Price, Promotion and Offer Optimization,” which can be accessed by going to the research section at

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