Customer Data and Telcos
Telecom companies have a unique advantage in the modern marketplace in that they have more data than any other industry about their customers. They know where they are, how they interact, and how they transact business. And unlike most other segments, they create all this data that they can consume as well. But it is a totally different story when it comes to leveraging all this information and changing it into something that can meet today’s demand for real-time business and consumer insight.
What kind of data are we talking about?
Telcos have multiple terabytes of data in their networks – data that is humongous, varied and complex. LTE/4G mobile networks, GPS, location-based services, social media and IPv6 that creates as many IP addresses as there are grains of sand – together produce some unthinkable amounts of data. This data comes in myriad formats. Insights need to be got from unstructured data that comes from the Web, social media, and machine devices. All this calls for processing systems that can handle data volumes too large and complex for human intervention. The key is to minimize the cost of processing and managing all this data while maximizing the value they can derive from it.
The telecom industry has access to some of the largest amounts of personal data about its customers – data from demographics, usage history, communications preferences, location, presence (network monitoring), purchase behavior, direct interaction (via call center and web) and responses to campaigns.
Data and Understanding the Customer
All this data helps in understanding the customer – their needs, preferences and unique position in the lifecycle – and in getting a complete picture of each one. The customer’s touch points must be understood as well – why he chooses to engage with the Telco through this particular channel, and not something else. Understanding the customer and making a profile for him will tell the staff what would interest the customer – which is where cross-selling and up-selling comes in.
How will this help?
You will be able to tell what would work for each customer or for a group and what doesn’t. You will then be able to send the right message to the right customer at the time that is most right for him. This whole process of engaging with the customer can be automated – messages that are relevant and consistent across all channels can be sent out to each customer. In the automated process, an intelligent database will understand the background of each customer and recommend even a channel mix. All that is needed is an optimal multi-channel strategy with the right tools.
How do we do this?
- For customer engagement to be meaningful, customer data needs to be available at all touch points – in a form that can be understood and used readily. This will facilitate instant customer recognition by all customer service executives, power each interaction so that it is meaningful and ensure the utilization of cross-sell and up-sell opportunities.
- A single customer view – loaded with all the available information about him – that is integrated across product, channel and segment is essential. Data must include customer usage, associated history, lifestyle and transactional data. According to Gartner just having this information alone would result in a revenue increase of 48% 4!
- Great analytics – Most analytical tools will help you predict the best time for selling him something and also present you the next best offer. The best kind of campaigns are those that are multiple, concurrent and highly targeted which are based on real time triggers and retention campaigns based on current usage behavior and historic data.
Data puts an end to assumptions. With so much information, there is no need for guesses – it changes everything. Decisions can now be made based on facts. Not assumptions or clever guesswork. On the other hand it empowers the company with information and insights. We have reached a point where one can safely say that no longer should any business discipline operate without the power of data.
Data-driven marketing is not the future of marketing. It is here.: