It’s no secret that Australian retailers have been able to capitalise on the rapid success of ecommerce and hone their omnichannel strategies to meet evolving customer demands. However, this digital evolution, as beneficial as it is, also creates new operational challenges for retailers.
Consumers today expect seamless shopping experiences, whether they are browsing a mobile app, checking in-store stock availability, or placing an order for home delivery. Operational disruptions, such as slow-loading web pages, payment failures, or security incidents such as the data breach at furniture retailer, Early Settler, last year, can cause a poor customer experience with the potential to irreparably damage customer loyalty, brand reputation and ultimately impact revenue.
Alongside customer expectations, retailers face increasing complications in supply chains which result in higher operating costs. E-commerce fraud also represents a significant ongoing threat. Australians reported $2 billion in scam losses to key organisations in 20241, according to the National Anti-Scam Centre’s latest Targeting Scams Report.
While Australians have a long-time love affair with online shopping – we collectively spent $61.2 billion on online retail in the 12 months to February 2025, according to the NAB Online Retail Sales Index2 – today’s shoppers are understandably fearful of falling victim to fraud. The necessity to provide them with robust protection adds an additional layer of complication for sellers.
While many retailers already use observability to manage system performance and understand the root cause of customer-impacting problems, observability data can provide greater opportunities for solving challenges beyond traditional application and infrastructure monitoring.
Real-time data enables actionable insights
Retailers generate vast amounts of data from digital interactions, but without clear visibility into how IT issues impact business outcomes, it can be difficult to identify areas for improvement. Retailers can bridge this gap by linking systems performance insights captured in observability data to their business analytics practices. This gives teams a deeper understanding of how IT performance influences key metrics such as conversions, revenue, and customer retention, so they can focus on the issues that have the greatest commercial impact. Retailers can therefore make smarter decisions about where to allocate engineering efforts.
For example, a one second slowdown at the beginning of the customer journey that has caused a 50% drop in conversions over the past 24 hours is far more urgent than a seemingly larger issue later in the process that only resulted in a 10% decline in conversions. By taking a more unified approach to observability and business analytics, retailers can empower their teams to make these distinctions in real time. As a result, they gain the deeper context needed to understand issues and ensure that high-priority fixes are addressed first.
Proactive measures to meet customer expectations
With customer expectations higher than ever before, retailers need to move to a proactive service model rather than being forced to react to problems. By anticipating and resolving problems before they arise, retailers can mitigate their impact on the customer experience. For example, observability-driven insights could identify that an API slowdown prevents inventory updates from displaying correctly when customers checking stock availability. This needs to be resolved quickly, as it could lead to missed revenue opportunities and disappointed customers.
The benefits extend beyond everyday transactions. During peak shopping events such as Black Friday, retailers can use observability to stress-test their systems in advance, identifying potential bottlenecks before high traffic volumes push them to breaking point. Retailers can take this one step further by using observability data to drive AIOps workflows that trigger an automated process to resolve issues without human involvement, so customers never feel any impact. This level of preparation can mean the difference between a record-breaking sales day and a costly system failure.
Combating fraudulent activity
Fraud remains a persistent and growing challenge in the wake of the Covid crisis which saw many Australian retailers shift their focus from bricks and mortar to online sales.
The cost of retail crime has soared by 40 per cent since 2022 and cost Australian retailers $7.79 billion in FY2024, according to the 2024 ANZ Retail Crime Study3.
As businesses expand their digital presence, fraudsters are becoming more sophisticated, using tactics such as account takeovers, payment fraud, and refund scams to exploit weaknesses in e-commerce platforms and processes. These threats are not always easy to detect, especially when they involve subtle patterns that unfold over time.
Observability data can help retailers to combat fraud by providing a holistic view of customer interactions across applications and transaction histories. By continuously analysing behaviour patterns, retailers can detect unusual activity that traditional security systems might overlook. For instance, retailers can use real-time visibility into the whole customer journey to identify suspicious users who are attempting to log into multiple accounts in succession. These insights can help retailers identify this unusual activity as a potential credential-stuffing attack and trigger an automatic response before any real damage occurs.
Likewise, if a sudden spike in refund requests is traced back to a specific region or IP address using observability data, it can help retailers to uncover potential fraud schemes. A proactive fraud prevention strategy, enhanced with observability-driven insights, can make a significant difference in securing business operations and improving customer trust.
Embracing observability data
Observability has long been used to find and fix digital issues, but now retailers are able to go beyond traditional monitoring capabilities to proactively tackle challenges impacting the customer experience. By utilising observability as a strategic business enabler, retailers such as Village Roadshow have been able to improve operational efficiency, proactively meet customer demand and expectations and deliver a seamless consumer experience.
Embracing observability data which providers deeper, real-time insights enables retailers to drive smarter decisions, build stronger customer relationships and stay ahead of the competition.
Andrew Foot is regional vice president of sales for Australia and New Zealand at Dynatrace.