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From app errors to user adoption: The missing analytics layer in Salesforce Lightning

BrandPost By Jeff Miller
Aug 13, 20254 mins

Organizations have invested heavily in Salesforce Lightning, and to ensure they’re seeing value, providing effective support, and increasing adoption, they need better analytics to identify errors in apps and track usage patterns. to provide effective support and increase adoption.

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Credit: NicoElNino

Salesforce has become the backbone of enterprise operations, with 90% of Fortune 500 companies relying on its platform to drive business processes.[1] What’s more, the company’s various cloud offerings generate over $20 billion annually,[2] cementing its position as the dominant force in customer relationship management and business automation.

To maximize their Salesforce investments, organizations are dedicating significant resources to Salesforce Lightning, spending an average of $500,000 on Lightning implementations. This substantial investment reflects Lightning’s appealing promise: empowering both developers and business users to build custom applications through intuitive drag-and-drop interfaces, democratizing app development across the organization.

However, building applications represents only half the equation. Even the most sophisticated Lightning apps deliver zero value if employees don’t adopt them or abandon them due to poor user experiences. Even worse, when errors occur within these mission-critical applications, IT support teams often struggle to replicate issues, leading to prolonged resolution times and frustrated users.

The core challenge facing enterprise IT teams centers on visibility. While Salesforce Lightning excels at enabling app creation, it provides limited insight into how these applications perform in real-world usage scenarios. IT leaders find themselves operating without crucial metrics that could illuminate user behavior patterns, identify performance bottlenecks, and prioritize which application errors demand immediate attention.

This visibility gap creates cascading problems throughout the organization. Without understanding feature utilization rates, IT teams cannot determine whether customizations truly improve productivity. When applications underperform, support teams lack the session replay capabilities needed to witness exactly what users experienced during error scenarios. The result is decreased employee efficiency, lower satisfaction rates, and ultimately, unnecessary friction that can degrade end customer experience.

Analytics platforms for Salesforce Lightning can address these challenges by providing the deep visibility that native Salesforce reporting cannot deliver. The capabilities extend beyond basic monitoring. Organizations can optimize employee onboarding processes by analyzing how top performers navigate Lightning applications, creating data-driven training programs that replicate successful usage patterns. This intelligence is also invaluable for demonstrating return on investment with concrete evidence of whether employees can accomplish intended tasks within the applications.

Perhaps most importantly, comprehensive analytics enable efficient IT support case resolution by replaying sessions to recreate issues. Support teams can observe the exact sequence of events that led to errors, dramatically reducing troubleshooting time.

“One of the most valuable features of a comprehensive analytics platform for Lightning is support’s ability to replay sessions to recreate issues,” said Kartik Chandrayana, Chief Product Officer at Quantum Metric. “Support teams no longer need to operate in the dark, because they can observe the exact sequence of events that led to errors, which dramatically reduces troubleshooting time.”

The value of Lightning Analytics becomes clear through practical implementation. A major telecommunications company deployed Quantum Metric Lightning Analytics to ensure efficient internal IT support case resolution. IT was able to provide hard usage metrics and recreate issues across its Salesforce Service Cloud environment, and, as a result, uncovered critical issues that were silently undermining business performance.

Within six months of implementation, the analytics platform identified 289 missed orders caused by agents encountering perpetual loading spinners in the purchase flow, resulting in conversion drops of up to 26%. The system also detected a 286% increase in frustration errors on the Select Offer button preceding the buy flow, correlating with a 36% decrease in conversion.

These insights enabled the telecommunications company to prioritize fixes for the most business-impactful issues, shining a bright light on previously invisible problems.

For CIOs evaluating their Salesforce Lightning investments, the message is clear: building applications represents just the beginning. True success requires comprehensive visibility into user experiences, application performance, and business impact—capabilities that extend far beyond native Salesforce reporting to deliver the insights necessary for maximizing enterprise software investments.

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[1] Salesforce FY 25 Annual Report: Leading the AI Agent Revolution.

[2] Ibid.