“Simplicity is the ultimate sophistication”. This quote from Leonardo de Vinci describes the most exciting challenge I face in product management. Because when you achieve that goal of combining innovation with a rich user experience, things that used to be perceived complicated or unreachable become fluid and easy to process. A relief that requires patience.
But because I have a passion for simple and elegant product design, that patience has limits in one particularly annoying situation: when a product does everything well…except what it was designed to do. It seems obvious that a product should always complete the task it was designed to do. But there are numerous legendary accounts of products that ‘had one job’ and failed at performing it.
So, how does this happen?
Keeping first things first
As a kid, my parents used to tell me, “Always keep first things first”. That piece of sage advice was usually given within the context of “Do what you need to do first, so that you can do what you want to do later.” But I think it is largely applicable to product design as well. For example, I spend a good portion of my time defending my products’ roadmaps from ‘feature creep’, an ever-increasing list of required bells and whistles to include in the product. Obviously, I don’t defend against feature creep so that we can limit the overall functionality of the product; I do it so that we can give the product’s core purpose as much attention, consideration and resource as possible.
Similarly, Mobile Network Operators (MNOs) don’t intentionally ignore call quality to focus solely on data services. However, when MNOs use a set of digital voice monitoring tools that deliver data in the form of network performance KPIs, these KPIs alert their operation teams when and where a service issue may be occurring on the network. They spend time investigating that problem as well as surrounding factors to first bring some context to the event. When finally arriving at a root cause, the operator then assigns resources to remediate the issue. The goal from beginning to end is to fix the network, and herein lies the problem.
When MNOs use network performance as a proxy for customer experience, their remediation efforts often stop short of ensuring that customers are actually having a good experience. But “My network is running properly, so my customers must be having a good experience” is an assumption MNOs cannot afford to make – especially where it concerns digital voice experience. Nothing will tank an operator’s NPS (Net Promoter Score) more quickly than poor call quality. Most subscribers will have some patience with random degradation of data services. And even when they aren’t patient, they often don’t immediately know whether to blame the network operator or the content provider. But when their smartphones fail at being telephones – even if only for a minute – not only do they get upset, but they know exactly who to be upset with. And sooner rather than later they churn – and in the worst way: quickly and silently. Not to mention those customers who don’t leave silently, but vent their frustrations on social media platforms.
This isn’t to say that MNOs don’t already realize that they need to keep customer experience top of mind. They know this. As a matter of fact, many of them even evangelize throughout their organizations the need to keep customers first. However, while they evangelize customer-centricity, some are still figuring out exactly how to operationalize it.
Closing the loop on customer experience
Relying on network-centric KPIs as an indicator of customer experience leaves a gap in what needs to be a reconciliation between network performance and customer experience. In addition to changing its internal messaging and external branding to focus on customers, MNOs should also put tangible measures in place to operationalize customer centricity throughout their people, processes and technology.
Here are some key dos and don’ts for MNOs to close the loop on customer experience.
- Take advantage of artificial intelligence (AI) and machine learning (ML) to automate much of the investigation and analysis of customer experience degradation anomalies that occur on your network. This can accelerate your mean-time-to-repair (MTTR). The more AI & ML can tell a story about what’s happening on your network by bringing much-needed context, the less time your network operations teams must spend on retrieving data and running root cause analysis.
- Use tools that rely on customer-centric KPIs as an indicator of customer experience – here again ML is key for scoring the experience. Don’t get me wrong; network performance KPIs are crucial and should be monitored. Just don’t assume they are giving you a full report about what’s happening with your customer. For example, customer-centric KPIs can indicate:
- The severity of voice experience anomalies
- The number of impacted customers
- The number of potentially impacted customers (so that you still have a chance to fix the problem before they experience it)
- Are there any leading indicators of customer experience degradation, or does it occur abruptly?
- Where is the problem located? Is it on the network side – such as VoLTE or VoNR handoff interruptions, or on the customer side – like a device known for one-way audio issues?
- Don’t use network performance as a proxy for customer experience. Your network could be running well, and customers still could be having a bad experience while using it.
- Don’t rely solely on customer surveys and feedback. While they are good to have on hand, surveys can be limited by poor phrasing and question biases and feedback is often dependent on the customer’s mood at the time of response submission.
Customers will not abide poor call quality. No matter how sophisticated smartphone devices get, customers still place seminal importance on initiating, connecting and completing telephone calls flawlessly.
To ensure this happens consistently, network operations and service management teams need to shift thinking to prioritize the customer. Fixing the network shouldn’t be the goal. Remediating degradation anomalies on the network is a means to an end: and that end should be to fix the customer’s experience.
Read more on Mobile Voice Analytics:
- Ops-IQ Mobile Voice Analytics
- Intro video of Ops-IQ Mobile Voice Analytics
- New AI-driven Mobile Voice Analytics Product from Guavus Helps Operators Meet Customers’ Great Expectations for 5G
To learn more about Guavus’ Mobile Voice Analytics approach, schedule a meeting with Guavus today.
Image attribution: iStock