E-Commerce / Enterprise Bespoke crawlers & simulators

Our Bespoke Crawler & Simulators: How We Preempted Performance Failures at Scale

Simulated millions of shopper journeys across regions and devices to surface bottlenecks, optimize delivery, and increase purchases by 40%.

Disclaimer: Certain information in this case study have been anonymised to protect client's security. Specific references to brands and internal processes have been withheld to prevent disclosure of potential website vulnerabilities or strategic challenges to competitors. The issues addressed, solutions delivered, and outcomes achieved remain genuine and accurately represent the real project.

35% Reduction in Bounce Rate
After First 30 days
40% Increase in Conversions
Month on Month
2.9s Average Time-to-Interactive Achieved

The Problem They Faced

The client, a multinational electronics retailer with both a strong e-commerce presence and hundreds of physical stores across North America and Europe, serves millions of customers annually and manages an extensive catalog of over 50,000 consumer technology products. Despite significant investments in digital experience and infrastructure, analytics revealed growing friction in the online purchase journey. This included: high exit rates on key product pages, increasing cart abandonment, and a noticeable slowdown in conversion growth. Deeper performance diagnostics also showed that page load times and dynamic content rendering were negatively correlated with engagement, particularly during peak traffic periods and major promotional events.

Analysis revealed significant performance disparities across regions and devices. Mobile users in certain markets experienced time-to-interactive (TTI) delays exceeding six seconds, particularly on mid-tier devices and congested 4G networks. For a category where shoppers rapidly compare specs, prices, and reviews, even small latency gaps led to measurable drop-offs in engagement and conversion.

Existing testing solutions provided only generic insights and lacked the tailored simulation capabilities needed to replicate real-world conditions such as regional latency, network variability, and device performance. As a result, critical bottlenecks were often visible only once they affected live traffic.

Every bounce represented a lost sale. Collectively, those seconds of delay translated into millions in missed revenue and a weakened brand reputation.

Our Approach

We built a bespoke performance-intelligence framework tailored to the retailer’s architecture, traffic patterns, and business priorities. At its core were automated crawlers that simulated realistic shopper journeys at scale: across device classes, throttled network profiles, geographic regions, and peak-traffic loads. All done to reproduce the kinds of conditions that were degrading the user experience and identify problematic elements.

These simulations exposed high-impact, system-level bottlenecks under realistic, large-scale conditions: region-specific backend latency and cache-miss patterns, and render-blocking resources. Crucially, all issues were analyzed within high-intent conversion funnels (category → PDP → add-to-cart) and during peak traffic scenarios, not as isolated metrics.

Findings were translated into prioritized, business-mapped remediation items and integrated directly into the retailer’s delivery pipeline. We also deployed globally distributed synthetic monitoring and real-time alerting so regressions would be caught and triaged before impacting customers.

By combining large-scale, scenario-based simulation with continuous monitoring, the retailer moved from reactive firefighting to proactive performance governance, reducing latency and instability during peak events. In result: lowering cart abandonment, and sustaining measurable conversion and revenue improvements.

The Impact

With the new performance framework, the retailer could quickly identify and address bottlenecks across devices, networks, and regions. Average mobile time-to-interactive dropped from 6.2 to 2.9 seconds, while desktop performance improved similarly. Bounce rates on key pages fell by 35%, driving a 40% increase in conversions (product page session start to purchase).

The combination of pre-launch simulations and continuous monitoring enabled the teams to proactively resolve issues before they affected users.

The framework remains integral to the retailer’s optimization strategy, supporting pre-launch testing and ongoing performance governance across all new features and content updates. Rather than relying on generic platforms with limited flexibility, we delivered a fully tailored solution that the retailer can continually reuse and adapt as their needs evolve.

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