WiFi Analytics Needed to Improve Endpoint Connectivity and Satisfy Users | Wyebot

WiFi Analytics Needed to Improve Endpoint Connectivity and Satisfy Users

December 12, 2022

Your business runs on your WiFi network, and for many companies, these networks consist of hundreds or thousands of endpoints. These endpoints need to work reliably for all users so that business productivity proceeds uninterrupted.

What are endpoints?

Physical devices that connect to your network are endpoints or end devices. This includes desktops, laptops, tablets, smartphones, and IoT devices.

What are not endpoints?

Infrastructure devices are not considered endpoints. These are devices like routers, gateways, switches, and load balancers.

How do WiFi analytics improve endpoint connectivity and the end user experience?

Analytics tell your IT professionals how end devices are performing at any given time. With the right analytics, teams know exactly what needs to be done to keep these devices connecting reliably and optimally. This is key because it’s through these end devices that your users interact with your WiFi network. Without the devices, users cannot access the network and cannot perform.

Which WiFi analytics are the best ones for connectivity?

End devices exist to improve the user experience and productivity. Determining the right analytics come from focusing on the end user and asking what they need. Endpoint analytics should be:

  • Continuous: For a complete picture of end device performance, analytics need to be gathered 24/7. WiFi networks are dynamic, and therefore an issue can arise at any moment and impact device connectivity. Addressing issues quickly and improving the UX requires there to be no gaps in device analytics.
  • Real-time: IT must be able to respond to issues as soon as they occur. This requires real-time analytics from all end devices.
  • Historical: The best way to comprehensively understand and improve the end user experience is to combine real-time insights with long-term performance trends. This requires historical analytics. 
  • Proactive: Proactive analytical platforms identify issues either before they occur or as soon as they occur. This allows IT to resolve issues quickly, often before end users are impacted. Companies who choose to use reactive analytics instead usually aren’t alerted to issues until users report a problem. 
  • Automatic: With hundreds or thousands of end devices connected to the network, IT professionals don’t have enough time to manually, continuously analyze real-time data, identify issues proactively, and map long-term trends. Companies must provide a way for these tasks to be performed automatically.

With these points in mind, companies will want the ability to analyze:

End user quality metrics

End user quality metrics are analytics from the user’s perspective. They tell IT professionals how users are experiencing connectivity at any given time. They can be gathered by working with a tool that connects to the network as an end device before running analytics; or, by using a telemetry solution. Telemetry is the automatic collection and transmission of data from remote sources, such as end devices. Not all telemetry solutions automatically analyze all data. Some partner with a second platform that performs the analysis.

Wireless connectivity and internet connectivity

After running these tests, IT will know if the WiFi signal is reliably available everywhere that users work. With most employees using mobile devices like laptops and tablets, it’s critical that there are no dead zones in the office.

Network security

No one wants end devices to connect to an unsecure network. Consistently running a security audit allows IT professionals to automatically be alerted to any vulnerabilities or weak spots. These can then be resolved quickly, avoiding possible attacks.

The entire network ecosystem

There are many factors that can affect endpoint connectivity. This includes an issue with the device itself, the network, the service provider, hardware, software, infrastructure, interference from nearby WiFi networks or Bluetooth devices, or a combination of any of these. To best ensure reliable connectivity, IT professionals therefore need analytics from this entire network ecosystem.

Bonus tip: Companies can use analytics tools that provide automatic root cause identification to greatly reduce the time it takes IT to identify the root cause of issues. Whether companies are facing coverage issues, congestion, interference, or another problem, no resolution can be implemented without root cause identification. With so many possible factors at play, this can take IT professionals hours or even days. The process is streamlined and simplified by working with a tool that automatically delivers the root cause with any issue alert.

Which WiFi analytics tools should be adopted?

AI-based WiFi automation platforms are the way to go since they deliver the key capabilities listed above:

  • Continuous, proactive analytics
  • Real-time and historical insights
  • Proactive alerts

These platforms use a combination of hardware and software and can easily analyze and troubleshoot networks with hundreds to thousands of devices. They are a scalable, cost-effective solution perfect for companies of any size.

Wyebot’s AI-powered solution, the Wireless Intelligence Platform™ (WIP), is vendor agnostic. It seamlessly integrates with existing network infrastructure, providing critical analytics regardless of changing technology. Organizations that use WIP report:

  • 90% faster resolution times
  • 70% fewer WiFi problem tickets 
  • 80% fewer remote site visits

Schedule a demo or trial today and give your end users the connectivity they expect and deserve.