In part one of our two part series, Heavy Reading analysts Ari Banerjee and Sarah Wallace discussed contextual intelligence for telecoms (CIQ4T) and how this type of approach, which provides advanced analytical insights for a holistic customer view, can improve engagement and elevate the customer experience.
Now, in the second and final installment, Ari and Sarah delve a bit deeper into what this actually means for service providers and explore some real-life examples of putting CIQ4T to work, such as monetisation, network resource optimisation and dynamic profiling with advanced analytics.
As I mentioned in one of my earlier blog posts, the telecommunications industry needs to increasingly predict what is important to customers rather than simply being reactive – and analytics plays a key role in helping to achieve this. Ultimately, turning all of this data into actionable information helps to bring people close together and furthers our goal of making data beautiful.
Like last week, you can listen to the full podcast of the conversation here or read the highlights below.
Ari Banerjee: Can you talk a little bit about the use cases that Comptel is addressing today that are more customer-facing?
Sarah Wallace: One of the first use cases is obvious but also very important, and that’s monetisation. This includes upselling to the customer, offering them something that might be triggered through some type of complaint, or offering them a new service. Another aspect of this is cross-selling – identifying subscribers and offering something they don’t necessarily need but that fits their usage pattern. So, for instance, service providers could offer a device with its own hot spot to a customer who may travel a lot.
Then, of course, there’s the aspect of new customer acquisition when it comes to monetisation. This entails identifying influencers in the network that might have a lot of off net relationships and making them an offer that will compel them to spread it virally – subsequently acquiring new subscribers.
Ari Banerjee: Beyond that, there’s the whole element of network resource optimisation. As we all know, when it comes to wireless, bandwidth management and resource management become extremely critical. Looking at the evolving wireless industry and all of its networks, 4G rollout is happening almost everywhere across the globe with LTE as the preferred route that most operators have taken.
With this comes another element of how to use spectrum, bandwidth and network resources better – especially when we look at services that are becoming more popular to enterprises or to consumers. These are really services that are low latency – those that revolve around video content and media. How do you provide expected quality of experience? All of that, again, needs advanced analytics or use of CIQ4T in a much broader way. Therefore, an OSS/BSS vendor already in the network can provide a lot more value additions for service providers.
One of the things that we are seeing operators challenged in is around cell-site optimisations. As we know, 4G networks are challenging because of things like traffic load balancing, handing over traffic between cells, determining where to put small cells – all of these need much more contextual information. So if OSS information is joined with contextual information, such as user experience, location and so forth, there’s a typical pattern of user-behaviour that can be mapped out.
Analytics can show that reducing power of one cell in favor of another cell might improve the overall network. Also, it can provide intelligent analysis around experience of a small set of high value customers who are typically using demanding services at a set time during the day, and how this can be handled in a better way based on load balancing across different parts of the network.
Subscriber-centric wireless offload – this becomes very important – and any operators who are providing 4G services are talking about wireless offload. This is because you cannot keep a subscriber on 4G continuously, it must instead be offloaded. Can this be done more intelligently using analytics? Can decisions be made based on the profitability of the customer lifetime value? Is there an SLA attached to the customer? Are they part of an enterprise contract? All of these different dimensions come through and are brought together via OSS/BSS systems and then intelligent decisions can be made based on which subscriber to offload. Again, use of CIQ4T and advanced analytics plays a major role here.
Service control based on subscriber profiles is another area that we think CIQ4T makes a lot of sense. By augmenting network data with subscriber data, utilising behavioural patterns, matching subscriber preferences and so forth, services can be tailored according to different users on the same subscriber account. So, for example, giving a company’s directors priority service compared to other employees, or managing a parent’s business applications in a different way than the entertainment applications used by their children.
So again, advanced analytics can also drive policies, which can drive service elements in the network and these can be programmed into things like policy servers for enforcement throughout the network in a much more soft-ticketed fashion.
Sarah Wallace: Some other use cases in addition to that include real-time churn prevention. This means being able to examine behaviours in subscribers who are obviously going to churn. Various elements to observe are multi-SIM prediction, rotational churn, and even churn location (do they reside in an area that has a propensity for high churn?)
Another use case is the concept of dynamic profiling with advanced analytics. This entails examining characteristics such as their usage, interests, location, socio-economic class, influence in their network (SNA), overall propensity to churn and their relationship to off net users.
Then, of course, there’s SNA which is a sub-set of advanced analytics. It’s really just looking at social networks in the sense of relationships – looking at family, friends and co-workers – and seeing what kind of influence the subscriber has in their sphere.
The last use case is advanced offer management – enabling service providers to confirm which promotions and service bundles are successful to offer including loyalty points, event and rule-based promotions, traffic-based promotions and management capability based on data subscriber network usage.
Personally, it makes me happy to think that Comptel’s software can be – and is – a part of the lives of so many people. And as consumers have different expectations for quality of experience, one of my personal favourite use cases is defining how to provide the experience that is right for each customer. Which use case do you find most appealing for CIQ4T?