Information Architecture: The Engine that Drives Retail

This Article originally appeared in CMSWire.

Under pressure from pure play e-Tailers such as Amazon and eBay, brick and mortar retailers are scrambling to defend their businesses. To stay competitive, most have now added an e-Commerce channel. The challenge for many legacy retailers is that e-Commerce has involved a long learning curve and now mobile and web channels have become part of core functionality rather than a cutting edge addition to the brand.  Add to this that many traditional retailers still lack a core competency in the technical nuances necessary to compete effectively with the Amazons and eBays.Top retailers have wisely chosen to focus more effort on delivering a superior omnichannel shopping experience. This means enabling consistent data about the product and about the customer across multiple systems and processes, which is no simple task. Legacy retailers may use hundreds of systems to run their operations. Many of these systems were not intended to talk to one another, a capability that is necessary if a purchase is to be started in one channel and completed in another.

Retailers are now considering the value of enterprise information architecture as a key to enabling omnichannel retailing. Web information architecture has traditionally been the domain of the online channel. The web experience is completely information driven. However, for the physical store, such product details were not needed — if they were missing in the information system, the customer could still find and buy the product. On the web, missing metadata could mean that your product becomes invisible.

Where the Sale Begins

Consider how people research what they want to purchase. Customers gain a great deal of knowledge from online searching before they walk into a store. Pricing information is transparent and not typically a differentiator. The differentiator is the customer experience — the ease of using the site, the presentation of product selections, the precision of search results. The omnichannel experience can strengthen the customer relationship or damage it.

After researching online, customers may want to complete the purchase in the store. If the online information is not the same as the information presented in the store (such as a price discrepancy, product description or dimensions, etc.), customers might decide they've been the victim of a bait and switch.

In its report, “The State of the Digital Store,” Forrester concludes, “No in-store digital experience can be effective by itself. Every investment will need to integrate with and leverage existing enterprise systems …” The key to omnichannel success is to provide customers with a seamless experience as they engage and interact with the retailer no matter how they interact — via the web, in store, using a smart phone, using a tablet or calling customer support.

A Holistic View of Customer and Content

The fundamental enabler of omnichannel retailing is an enterprise view of information architecture, which provides a holistic view of enterprise data, content and information assets. This view requires integration of systems across traditionally segregated processes. It cannot be achieved without cross-functional and interdepartmental communications and deliberate decision making controlled by governance mechanisms. Traditionally, decisions made by merchandisers might not directly impact customer support and self-service operations. This is no longer the case in the omnichannel world.

Retailers need to provide product information in the most convenient and consumable format in the context of the customer’s goal: a video for a detailed explanation of how a product functions, recommendations when the customer wants to select from among a number of choices, an independent product review data when the customer is considering long-term value — each of these contexts are driven by metadata and Enterprise IA.

From Psychographics to Predictive Analytics

The information requirements depend on multiple factors — from psychographics, demographics, behavioral attributes and predictive analytic attributes to buyer stage, task and intent. All of these customer attributes need to be matched with product attributes and product content characteristics in order to anticipate and support the stage of the buyer’s process and present it in the correct format for the channel, device and media.

In a store, a product may have only a SKU number, a product name and a brief description, while online and mobile channels deliver additional product content. For omnichannel service, however, the data needs to be consistent. The way to deliver a consistent experience is to store a single representation of a product in a product information management (PIM) system and use it for all channels — with appropriate adjustments for screen real estate. The information can be syndicated out to each sales channel based on downstream system and end user requirements, rather than using multiple systems to deliver product information through each channel and device. 

Lessons From Amazon

As Amazon and other e-Tailers have shown, information is the new gold, so retailers looking to survive the 50-year inflection point that reflects establishment of e-Commerce need to respond. Enabling omnichannel retailing through a well-planned view of enterprise information architecture is a requirement, not an option.

New approaches and ideas need to be explored, adapted and operationalized in order for companies to stay relevant and serve customers as their buying patterns and habits change. Not doing so threatens the survival of the enterprise. Enterprise Information architecture combines both the art and science of organizing information across processes, systems and applications.

Amazon has clearly validated the power of this approach, which now threatens not only retailers but also wholesale and industrial product distributors. Brick and mortar retailers serious about competing in the new technology ecosystem need to use enterprise information architecture effectively in order to not just survive, but to differentiate themselves, better serve customers and thrive in the 21st century.

Meet the Author
Seth Earley

Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.