It could be argued that consumer broadband networks have historically been poor neighbours of business networks, with CSPs investing more funds in providing better SLAs to their higher paying business customers. But like it did for many of our pre-set ideas, the pandemic turned the tables around for broadband priority. Forced work from home policies, remote learning, and quarantines have effectively turned consumer broadband into business/educational/health broadband services for many. 

Home broadband is now a critical business service as well as a critical life service, with the majority of streaming, TV and voice services provided over a households consumer broadband subscription. Even as vaccines are starting to provide a new glimmer of normalcy, work patterns brought on by COVID-19 are expected to be long term. Broadband providers are realising that they need to provide consumer broadband users similar SLAs compared to their business networks. 


Be the first to know / Downdetector is not the answer 

According to a recent Capgemini research, fewer than half (48%) of consumers feel that the connectivity services that they have today adequately meet their remote work and education needs. Still, many CSPs openly admit that they often hear about consumer broadband service issues via social media and sites like Downdetector. Outages now result in immediate social media brand damage, which plays a direct role in customer churn and related revenue losses. 

This presents an even greater risk in saturated Western markets, where impacted consumers have plenty of choice. And with the fixed/mobile convergence, a negative home broadband experience now has the potential to cause churn for CSPs’ mobile customers too. Customer experience is a critical factor in building and maintaining a competitive advantage. No one likes to wait for videos to buffer or experience network issues during a Zoom meeting. Customer experience and network infrastructure teams need to know immediately if customer experience starts to degrade and why it’s happening.

To solve this, CSPs are constantly upgrading their infrastructure: building up their core, pulling more fiber, upgrading IT infrastructure, and introducing new technologies like Fixed Wireless Access (FWA) as back-up when their fixed network is down. But this is just part of the solution. Maintaining good quality of service requires CSPs to have full visibility into what is happening across their network, monitor critical network and customer experience KPIs in real time. Only by autonomously monitoring the network at scale can CSPs achieve early visibility of potential issues before they result in service failure and escalate into brand-damaging incidents. 


Detect and resolve faster with minimal disruption 

Fortunately for both consumers and CSPs, new Autonomous Monitoring Solutions, based on Machine Learning and AI, are now readily available, and can be deployed as an intelligent brain on top of existing architectures. These tools provide early visibility of network issues that could lead to service failure, before customers actually experience degradation in the service. They also provide correlation across many siloed domains and KPIs to reduce the time to detection and resolution, extending the life of the legacy infrastructures, and enabling the operators to enhance the customer experience, without major expenditure and disruption. 

CSPs that make early investments in these next generation tools, that are easily implemented with short time to value, benefit by retaining their customers and protecting their brand. Those that don’t will lose customers and revenue. 

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Written by Bryn Teasdale

Bryn is VP Western Europe, Telecom at Anodot, and is focussed on helping our European customers optimize their network and business monitoring, to provide better customer experience and greater operational efficiencies. Bryn has worked with Telecoms Operators for the last 20 years, holding EMEA, APAC and global leadership roles at industry stalwarts such as Cisco and Nortel, and a number of advanced technology start-ups, including P-Cube, Alteon and Qwilt.

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