With six of the seven billion people across the world in possession of a mobile phone, it is fair to say that this decade is the age of mobility. With so many people now connected, there are huge opportunities on offer for telecom companies. The data that is created by the six billion mobile phones in-use can be utilised to gain greater insight into customer behaviour and ensure that services are consistently of high quality and free from disruption.
The goal of real-time analytics is in reach, but data correlation is still proving a barrier.
Precision in intelligence delivery is key, a wrong offer or mistaken fault prediction could lead to poor customer experience, revenue loss and decreased brand loyalty. In the telco industry, real time analytics technology is offering valuable insight to help drive accurate and timely decision making.
Armed with this, service providers, especially telecom companies, can offer personalised products and services to their customers, enhancing customer experience at a number of touch points. However, there are challenges that make the implementation of a real time analytics solution difficult and hence need to be addressed.
Data correlation – the bottleneck
A telecom network has a huge number of interfaces and protocol stacks and the equipment used is often sourced from multiple vendors, making the task of collecting information in real-time a challenge. For example, if a customer is having trouble watching a YouTube video due to buffering problems, the communication service provider (CSP) may not be able to detect and resolve the issue in time due to a lack of data correlation.
There are so many different forms of structured, semi-structured and unstructured data now available that CSPs often struggle to correlate that data in a way that brings useful insights. In order to improve data correlation, data capture and data integration must be improved first. Data needs to be captured at the switch level and then integrated into a single data store location. This further needs to be accessible by analytics tools to evaluate and garner insights that aid the business decision makers.
Today, advanced data integration tools are available and CSPs and telecom organisations are leveraging them to conduct near-real-time analytics to improve their customer service. The goal of real-time analytics is in reach, but data correlation is still proving a barrier at the moment.
Data collection and security – The privacy concern
Maintaining data security and customer privacy is yet another challenge the telecom companies face. Real time analytics provides an opportunity to the telecom operators to monetise the huge amount of customer data they collect. It can be used to offer personalised services to that customer through event based marketing; but it can also be used by urban planners, law enforcement, retail outlets, and so on. The issue lies in treading the fine line between leveraging customer data to offer timely and useful services that customers appreciate and inadvertently annoying customers.
Too many restrictions on storing and using customer data risks strangling the analytical possibilities for that data.
The biggest annoyance for customers when it comes to event based marketing is caused by lack of customer understanding. Lack of understanding the customer well can cause the additional services and offers to be inaccurate. The answer sounds simple – gather as much data as possible – however, the actual gathering of that data can be difficult. Data collection needs to be opt-in and its utilization must be made clear to the customer.
There is a wealth of negative publicity around identity data collection and this leads to people being less willing to share their data with telecom providers or third parties. Restoring the customers’ faith in the data utilization is crucial. However, as more data is collected it can offer better insights into customer behaviour thereby enabling improved segmentation of customer groups which in turn leads to more accurate marketing campaigns.
As event based marketing improves, confidence will grow and more customers may choose to opt in for data collection and avail the benefits provided by those services. This suggests that individual customer data collection will increase exponentially so long as the consumer is clear on how their data is being used and that it is secure.
Data privacy – what lies in the future?
Weaving throughout this, irrespective of whether data is being collected or used by telecom companies themselves or by a third party, is the role privacy laws and regulations play. Privacy regulations in the EU and elsewhere restrict operators from storing customer reference information.
Operators can anonymize any customer references at the data collection layer itself, however too many restrictions on storing and using customer data risks strangling the analytical possibilities for that data. The solution to this conundrum will require significant work to be undertaken with regulatory bodies to ensure data remains private but analysis can still happen.
Did this article help you understand the issues of real-time analytics? Let us know in the comments.