David Van Camp

Technical writing for user success

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Troubleshooting

Faster issue resolution thanks to mobile replay

See it here

Read the story behind it…

Show me where it hurts. This is a story about feeling a customer’s pain.

Here, I created a story that describes how to use Experience Analytics as a diagnostic tool in a high-pressure customer support situation – an experience that many support technicians and app developers can relate to. Part use case and part instruction, the story outlines specific steps that an app developer can follow to diagnose an application crash.

Experience Analytics (Tealeaf) is a locally installed customer analytics application that monitors the actions of visitors to commercial websites. It can also be deployed to monitor customer interactions with a mobile app. Experience Analytics can record and replay the exact movements of a customer interacting with the app and provide details of each HTTP POST request.

Audience: Application developers and customer support technicians.

Noteworthy: This story is based on the actual behavior of an application simulator developed by an Experience Analytics professional services consultant. The simulator was developed based on experiences with real customers. I worked closely with the consultant to understand the scenario and the simulation. The final article includes screen shots from the simulation, including a stack trace that shows a developer exactly what to look for in case of an application crash.

Tools:

  • Markdown in Zendesk for authoring
  • MS Word and Adobe Acrobat, for reviews
  • Techsmith Snagit for screen capture, editing, and annotation

What is Experience Analytics (Tealeaf) On Premises?

The on-premises version of Tealeaf is a suite of data analytic and traffic monitoring applications that customers install in their networks, behind their security firewall. Tealeaf applications monitor the content of web traffic that enters a company’s commercial website. Data analysts and system administrators configure the system to watch for specific patterns of customer behavior. The analytics can provide early warning of customer struggles, help detect fraud, troubleshoot problems, and monitor website performance.

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