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Combining data sources to enrich customer experience management
CX management can evolve through the integration of new sources of data that build a bigger picture of how users interact with the network, how they express their views, and how devices perform complex tasks in enterprise slices. A new data architecture is required to leverage these new sources of information – and to enable automated responses to be delivered.
Slicing changes the dynamics of CX management – but there’s a lot more to consider
In our recent white paper on Customer Experience Management in 5G SA networks, we considered how technical aspects of CX will change with the advent of slicing. We also noted, though, that it’s not just factors that can be measured and observed in the network that will contribute to the overall CX enjoyed by customers.
While metrics from the network across all domains remain critical, operators also now recognize that CX is a combination of multiple factors – some of which lie outside their traditional domains. As an example, we suggested that trending topics on social media could influence customers and thus change their perception of the CX delivered – rightly or wrongly.
While this may remain some way off, let’s imagine that a network outage is reported in Stockholm, leading users to query their connection or wonder whether they were getting the service they paid for. These anxieties will undoubtedly have an impact on how they perceive CX. But what if the outage never happened? What if it was an incorrect report, or even a hoax?
If the operator concerned had access to trending topics on social media and could identify any negative (or positive) reports – and then correlate these with observed metrics from the network which proved that there was no such outage, they may be able to take action to forestall any negative impact by taking control of the social media narrative.
A clear case of “what if”. But it is a serious point. Narratives shift so quickly today, that operators need to proactively assure, not only their networks, but to manage their reputations in real time.
This – currently hypothetical – example illustrates the potential value that can be obtained from combining existing and new data. Put simply, operators will need to broaden their focus to include data from other sources – from outside their networks – so that they can integrate new information into their operational and analytics programs.
Another aspect of CX is the overall satisfaction a customer has for its service provider – not, that is, at a given moment but rather through time. A given customer might respond negatively to an auto-generated survey sent via SMS. The results of such surveys provide another data set – and negative survey results could trigger an automated review of observations about network performance for a set billing period – and, perhaps, trigger a new discount to be offered, or an extension of a data plan.
Delivering different kinds of CX – to devices in slices
Let’s consider a final, though currently largely hypothetical, example. An operator has delivered a slice to an enterprise, perhaps a factory. The enterprise uses the slice – which comes complete with specified QoS performance – and takes advantage of the wireless connectivity to run its processes, connect its devices and so on. In this case, there are no people connected to the slice, but many devices are deployed in the factory, each of which leverages the available performance.
From the perspective of the operator, metrics are available from the monitoring tools in place – from the RAN to the core to which the devices are, ultimately, connected. This means they can assure parameters such as latency, jitter, and so on, while checking that they are correctly accessing the slice.
But they can’t tell if the devices are actually doing what they should be – only the operational systems of the enterprise can determine that. The operator, meanwhile, has sold the service with an SLA – so needs to be able to ensure that it delivers.
To achieve that, they have their usual metrics, but they may also benefit from metrics provided by the enterprise. In this case, CX isn’t the same as for a person streaming a video but is something that relates to the tasks performed by the devices and the equipment to which they are connected.
So, to obtain the full picture and to enrich the data that it already has, the operator can benefit from obtaining additional data from the enterprise slice customer. Now, you could argue that this isn’t strictly necessary, because the SLA may be based solely on the assurance of cellular network operational parameters.
Sure – but then what if the MNO seeks to differentiate the service assurance it offers, across a growing diversity of slice models – and to achieve competitive advantage. This will be particularly relevant if it is targeting specific verticals. In that case, the benefits of supplementing existing sources of data with new information from the enterprise domain within slices delivered by MNOs could be a contributor to future competitive success – and drive the long-sought business growth promised by slicing.
Network data – necessary, but not sufficient. Go further!
In today’s landscape, we can already see that network data is necessary but may not be sufficient to deliver the new kinds of CX demanded by both customers and devices that use the network and the slices it supports.
And here’s the thing. We need to be able to combine any source of data and ensure that it is available for processing. As we noted in our paper “By ingesting any source of data, we can enhance CX by considering different touchpoints and interactions with your network – building a bigger picture that complements the techniques that unlock 5G SA and slicing assurance”.
This requires a new DataOps-based processing platform to harness the power of data analytics, at scale, taking any data sources we think might be relevant alongside standard metrics and measures from the mobile and other domains. This data architecture can then provide the fuel to make new connections, decisions and automated responses to manage CX more effectively – and with a great scope than has previously been possible.
Data integration and movement is integral to this vision. Bringing data together, in to a single, unified pool that makes it available for analytics, processing and more to deliver a truly comprehensive view of CX – and the tools to manage it. Talk to Elisa Polystar to find out how to truly leverage your data so you can drive competitive advantage and secure the benefits of an augmented approach to CX.
