How AIOps is Keeping Retail Lights on Behind the Scenes

When shopping online, customers expect everything to work seamlessly. There’s no room for friction like a pricing error, payment failure, or out-of-stock item masquerading as “in stock.” If anything goes wrong, online shoppers take their business elsewhere.

That’s why e-commerce continuity is table stakes for retailers today, especially when high-profile events such as Cyber Monday and the holiday season are huge revenue drivers for retailers. However, most of the risks to that continuity aren’t on the websites and apps that customers interact with directly. They’re hidden in the digital backbone of every modern e-commerce organization: technology systems.

Complex systems powering order management, inventory management, pricing, and payments will always have occasional bugs, outages, and process failures. It’s the job of the IT Operations (ITOps) teams to make sure those failures don’t interrupt the seamless customer experience.

One tool empowering ITOps teams to do just that is artificial intelligence for IT Operations, better known as AIOps. Through automation and machine learning, AIOps platforms can surface and remediate errors and inefficiencies buried deep within your technical stack.

But how can retailers, specifically, benefit from AIOps? Let’s dig into some examples.

Streamlining Order Processing

Order processing touches multiple systems from front to back. From the customer adding items to their shopping cart all the way to payment processing, inventory sourcing and, ultimately, fulfillment, delays can occur at any point along the way. A business observability platform can track orders seamlessly across system in three dimensions:

• anomalies that relate to order flow issues;
• data inconsistency and reconciliation issues; and
• IT system-related issues.

The platform can automatically alert someone or trigger auto-remediation if something looks amiss. This also ensures IT remediates the problem and key revenue-generating issues are resolved before business or end consumers report about it.

Remediating Pricing Errors

Perhaps no error is more confusing to the modern customer than pricing errors. Whether it’s the pricing engine showing one price on a search result but another at checkout or a promotion failing to apply at checkout, pricing errors frustrate customers and erode trust. Oftentimes, these problems are caused by promotional pricing failing to sync from a retailer’s promotional pricing engine to its pricing engine (where dollars are calculated) and/or to the front-end user experience layer. AIOps platforms can monitor all of these systems and automatically reconcile them with one another to ensure accuracy.

Automatically Detecting Downtime and Technical Failures

Part of making the order process seamless is ensuring there aren’t any technological dead ends for customers to run into. Whether it’s a timeout from a resource-heavy database, an unexpected API failure, or some other types of technical failure, traditional monitoring will alert teams after the fact. AIOps platforms can use machine learning algorithms to watch for anomalies across an organization’s technical stack, taking action to prevent downtime before it’s detected by traditional monitoring.

Automating Data Reconciliation Between Systems

A retailer’s order management system, ERP, warehouse management system, customer data platform and marketing technology stack all generate and consume data. More often than not, data can fall out of sync across these systems. AIOps platforms help automate data reconciliation processes to ensure data is consistent across systems and applications. Alerts can be configured to notify teams when data falls out of sync.

Success Story: Preventing Failures With Tapestry Inc.

Here’s a real-world example of how AIOps can help prevent failures for retailers.

Tapestry Inc., a “global house of iconic brands” such as Coach, Kate Spade, and Stuart Weitzman, has high customer expectations, and understandably so. The company integrated tools across its e-commerce websites, order management system, and physical stores to enable closed loop automation with AIOps. This has helped automate order processing remediation if something goes wrong, detect pricing mismatches before they reach the customer, and ensure data is synchronized across applications.

For retailers competing in an environment where customer loyalty is increasingly fragile, the technical infrastructure behind the shopping experience matters as much as the products themselves. AIOps isn't just about preventing fires. It's about building systems resilient enough that fires never start. And in e-commerce, that difference translates directly to revenue, customer satisfaction, and competitive advantage.

Rajiv Nayan is general manager and vice president of Digitate, an enterprise AI and automation software solutions provider.