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Retail Science: Engaging Omnichannel Consumers with Next-Gen Offer Optimization

Dj O'Neil
Solutions Manager

Research shows that consumers want to be understood and engaged with relevant and personalized offers. Our recent global study specifically found that,

  • 50% want personalized offers based on interactions with a retailer.
  • 65% said personalized offers are most important in their shopping experience, and it compels them to buy. 

According to the RIS News / Gartner 2018 Retail Technology Report, increasing customer engagement, developing personalized marketing capabilities and pricing optimization are top technology-driven strategies for retailers over the next 18 months. However, retailers also report slow progress from initiating their digital transformation initiatives to harvesting business results.  

Engaging omnichannel customers with personalized offers, while increasing profits for the retailer requires modern applications in retail science. Growing digital transformation initiatives to maturity requires an integrated and modern cloud strategy. Oracle Retail provides a common connection and single view of the enterprise, enabling retailers to innovate at the speed of their customers and their business. Oracle Retail Sciences uses what customers share with retailers - information like sales, loyalty and browsing data - to understand and engage their customers. With the introduction of next generation Offer Optimization capabilities, retailers can delight their customers with promotions, targeted offers and markdowns while maximizing business results. 

Next-Gen Offer Optimization

Oracle Retail’s recent launch of Offer Optimization Cloud Service reflects the evolution of price optimization capabilities into a lifecycle optimization solution that recommends promotions, targeted offers and markdowns.

Offer Optimization enables retailers to:

  • Automatically evaluate the trade-off between temporary promotions and permanent markdowns, while also engaging customers with targeted and contextual offers that maximize redemption. 
  • Ensure consistency between strategy and execution by incorporating everything from markdown budgets and promotional campaigns to projected receipts and forecasted returns. 
  • Simplify decision-making through high-automation, exception-driven processes and on-demand scenario-based optimization.
  • Maximize accuracy and scale using artificial intelligence, machine learning and decision sciences on Oracle’s Retail Science infrastructure.

Optimizing the Item Lifecycle

The following example illustrates the lifecycle promotion, markdown and targeted offer recommendations that Offer Optimization provides in conjunction with planned business initiatives, such as a marketing campaign ran during spring.  

  • The initial price of a generic red women’s t-shirt is $24.99, with a planned marketing campaign in week 2 for a brand-wide 10% off Spring Sale.
  • The process is oriented around the imminent pricing decision, which is the 10% off promotion in week 4.
  • Along with this promotion, the solution provides the complete lifecycle context in support of the recommendation, including a second promotion in week 7 and clearance starting in week 10. 

Targeted offers that reflect both the deal type (e.g. 25% and BOGO) and channel (e.g. text message and email) are also recommended throughout the lifecycle, with the objective of driving customer redemption. This multi-scenario strategy is important, as certain customers may be more responsive to text messages over email and this enables retailers to deliver a higher level of personalization.  

Of the hundreds of promotions that a retailer may be running, only a handful of offers are relevant to each customer. For example:  

  • In week 4, trendsetters are targeted with a special 25% off promotion, above the 10% that the typical customer would receive. 
  • In week 7, customers most interested in the 15% off promotion are targeted. This effectively maximizes the impact of the promotion by engaging customers for which this promotion is relevant.  

In both cases, the optimization is recommending that these customers be engaged through mobile text messaging, as this is the channel that would maximize redemption.

 (Description: Optimized Pricing, Promotion and Offer Schedules from Beginning of Life to End)

Simplify Execution with Intelligent Dashboards

I am a fan of simplicity. During my 10 years in consulting, I worked with end-users across 30 implementations of planning, merchandising and supply chain solutions. The barrier to better outcomes in many cases was segregated processes, inconsistent recommendations and uncertainty of ‘where do I start’. With Offer Optimization’s intelligent dashboards, end-users are guided through a common and visual workflow, consistent results and exception-driven processes, enabling them to deliver those better outcomes.   

At the intersection of science and simplicity is where intelligent customer engagement strategies are transformed into action, at scale. This is the principle that underlies the day-in-the-life workflow of the end-user.

The Optimization Run dashboard provides context and status around optimization runs, letting users know:

  • what’s new (e.g. ready for review)
  • what’s been reviewed (e.g. user has gone through the work)
  • what has been submitted for execution

This enables end-users to efficiently work through results, by prioritizing and organizing by status.


The Results dashboard reflects the insights and recommendations within each run. This includes strategic optimization insights; such as projected revenue and inventory productivity potential, as well as detailed recommendation context; such as optimized lifecycle pricing cadence.

From here, users can review results and respond via mass approvals, what-if’s and overrides prior to submitting for execution. While there is more that goes into defining optimizations and what-if optimizations, these activities represent the exception. It’s easy to see that this allows users a simplified view so they can prioritize and organize optimization runs and review and respond to the results faster than before.


The Power of a Single View

Delivering an effective pricing strategy that engages the customer in an omnichannel environment requires a single view of:

  • Customer; providing the foundation for understanding and engaging each customer as they interact with the retailer across multiple channels.
  • Inventory; ensuring optimized results reflect accurate potential that is inclusive of current inventory and projected receipts and returns.
  • Order; enabling the retailer to maximize customer service and inventory efficiency from the point of commerce to the point of fulfilment. 
  • Demand; driving the enterprise – from planning to operations – with common forecast that underlies each optimization and incorporates every demand driver.
  • Pricing and promotions; ensuring that the strategies that underlie the optimization are consistent with the pricing decisions as a whole. 

A single view is mission critical in today’s retail landscape. When optimized results are presented appropriately and pervasively across the enterprise (e.g. directly as a promotion or indirectly as a forecast), then retailers can maximize the value of a unified pricing, promotion and markdown optimization strategy. The operational discipline to achieve this necessitates a holistic and integrated enterprise ecosystem, and this is what Oracle Retail delivers with modern retailing in the cloud.

Other Related Items:





1 Forecasting Customer Channel Choice Using Cross-loyalty Variables. USPTO 14/845,792 (pending). Sep 4, 2015.
2 Computerized Promotion and Markdown Price Scheduling. USPTO 14/989,932 (pending). Jan 7, 2016.
3 Computerized Promotion and Markdown Price Scheduling. USPTO 14/989,932 (pending). Jan 7, 2016.

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