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Oracle Retail Blog helps retailers stay current on customer successes, hot retail trends and industry best practices.

Unlock the Potential of Data-led Commerce Solutions

Ananda Chakravarty
Director, Retail Omnichannel Strategy

In retail, the customer is king – except when they’re not. Several cases exist where the business cannot meet customer demands – either because it’s physically impossible, financially unprofitable, or ethically untractable. The retail organization needs to adjust for unplanned, unintentional, or changed behaviors without alienating the customer. This is where data comes in. Relevant data can be used to prevent, mitigate, or divert these scenarios where the business is unable to meet customer demands. From Forrester VP and Principal Analyst Brendan Witcher’s (@BrendanWitcher) definition below, the implicit concept of data-led capabilities is using data for the customer’s benefit (rather than the retailer).

Let’s explore three use cases where the customer’s demands aren’t met and how data-led solutions can help mitigate disasters in customer experience:

Experiential cases: Stockouts/Merchandising

One place where retailers may be challenged to meet consumer demands is online stockouts. A customer may be seeking a product on the retailer’s ecommerce site, but stores don’t have the product and DC's are unable to distribute it within a reasonable timeframe. In some cases the customer may even be seeking a product that the retailer doesn't sell. The power of data to provide alternatives and substitutes, as well as anticipation of customer actions, can help to mitigate such a situation to avoid customer rejection and a poor experience for the brand. Here is where it’s important to put in data-led engagement that allows for customer options to be positive and continue to maintain a pleasing customer experience. For example, Neiman Marcus embeds quantity limits into their site messaging as a customer goes through the process of selecting a product online. This data-led action prevents major headaches after the customer has already driven to the store.

 

Figure 1.  Neiman Marcus Website – Details in Red Identifying Quantity Limits

 

Experiential cases: Personalization

According to Accenture’s 2018 Personalization Pulse Check Report2, 48% of consumers have left a brand's website and purchased somewhere else due to a poorly-curated experience. Personalization is critical to retail and pretty complicated – especially because customer stats are fluid and changing. Unfortunately, many retailers base personalization on limited data or even a single data point. The perfect example where retailers blunder is the “already bought that” syndrome. A customer wanders onto a website, selects a new blender, then abandons it in their cart or maybe just views the product and leaves the site.

During the next few weeks, the customer is overwhelmed with retargeted ads focused on blenders across every site he or she visits. Nerve-wracked, the poor customer caves in and buys a new blender at the local appliance store. A few weeks later, the customer needs a new toaster, so they return to the original website. Unfortunately, all the recommendations, visual search listings, and special offers on the site are tied to blender features – quiet blenders, multi-purpose blenders, long-lasting blenders, digital blenders, and more. The epic fail on the part of the retailer comes with a cost, and the customer’s needs for a toaster are left unmet. Context for the customer becomes the heart of a strong personalized experience. Data tools can diminish exposure to the ‘blender’ and focus on other products based on clickstream information with simple business rules or more complicated AI tools. Despite prior customer demand, data-led site dynamics can provide the customer with what they need in real time.

Experiential cases: Poor Fulfillment

Almost all retailers face fulfillment issues where shipments are late, products are damaged, or shipments are sent to the wrong place. In some cases the retailer can do little about the Teamsters strike that prevented products from being loaded at port or the cyber-attack on the freight carrier that routed packages from New York to Atlanta. However, tracking and data points are available that identify the situation for the customer, and many times transparency is key. The right data-led actions can offer the customer options on next steps – which are much more appreciated than keeping them in the dark.

An automatic data-triggered email with options to continue the current shipment, reorder, or cancel the current shipment and order a replacement product can be a powerful engagement tool for the retailer. Even a notification to the customer that the shipment is late will provide more clarity than leaving the customer in the dark. These data-led actions would allow for unforeseen circumstances to still allow a satisfactory customer experience. The right tools online can even identify and adjust shipping paths to ensure the customer receives their rerouted package.

Customer demands will drive business, but data will be the savior when resources fall short to meet them. A data-led business operates with data that supports the goals of the customer, encouraging messaging and options that mitigate situations to provide satisfactory customer experiences. 

Watch On-Demand Webcast: Oracle and Forrester Guest Speaker Brendan Witcher Get Personal: How to Deliver Individualized Experiences in Modern Retail

1Forrester Analyst: Retailers Are Still Catching Up To Customer Expectations, May 2018 article from Retail TouchPoints

2Accenture's 2018 Personalization Pulse Check Report

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