But while this is more true than ever in today’s environment, it’s not the whole story. After all, it doesn’t matter how many billions or even trillions of data points a firm possesses – if they can’t utilize it effectively, it’s doing nothing more than taking up server space.
Turning this raw data into something useful may be a particularly pressing challenge for telco providers. These firms collect some of the richest customer data sets of any industry. Yet while these businesses are well aware of the value they’re sitting on, they may often find it hard to turn this raw data into accessible information they can work with, let alone effectively ask questions of the data to gain actionable insight.
Many people often talk about ‘data insight’ as the goal of their analytics campaigns. But this is still only a small part of an effective strategy. Insight most often refers to just the results you get from analytics activities, whereas a true data activation strategy covers everything, from collecting and aggregating data, the analytics processes themselves, to how firms respond to it.
It’s a holistic approach to data analytics that uses more personal findings to drive marketing and customer experience efforts across an entire customer base, utilizing the most up-to-date sources of information to segment users and spot patterns that can be directly used in a wide range of activities.
For example, data activation can involve analysis of traits and interests to segment customers into behavioral tribes, who can then be targeted with truly personalized messaging that reflects what they’re most likely to respond to. This covers not only what you say, such as the type of offers you present, but also when and how you say it.
Managing huge volumes of data is always a challenge. But one of the best ways of turning the insight you gain from big data analytics into actionable results is to reduce the number of steps involved in your analytics process and democratize access to data.
At present, far too many businesses still limit these activities solely to their IT and data science teams, and often there are good reasons for this. The tools they have in place for accessing their data are complex and require deep knowledge of coding to function. As such, control over big data analytics remains solely the preserve of specialized data science professionals.
This can present a number of issues. These individuals – talented though they are – don’t have the same outlook as marketing or CX professionals and are often more detached from direct communication and messaging.
Marketing teams, on the other hand, have a much closer connection with their customers, so if they’re able to access the right data and make their own connections, they can much more quickly see trends and make their own decisions.
To do this, however, tools must be accessible. This means intuitive user interfaces that let users explore their customer data in depth and at scale, without any knowledge of skills like coding.
For example, the Intent Platform lets you select from a range of hundreds of variables about your customers – such as demographic information, data usage, what websites they visit and many more – and combine them in thousands of ways using a simple drag and drop system, across millions of customers.
This lets marketers drill down into the data to uncover truly personalized insights they can use to guide their activities, without having to wait for anyone else to run algorithms or interpret the results.
Some firms may worry that the more people who have access to this valuable customer data, the harder it will be to keep operations secure and meet the requirements of privacy legislation such as GDPR. But with the right tools, these concerns can be addressed.
We put the concept of the ‘digital twin’ at the heart of how we handle customer data, which ensures we’re able to provide a complete picture of what makes a person tick without compromising on their privacy.
This consists of a full virtual ‘copy’ of a customer, based on a complete history of their data, including sources such as CRM, billing and network information. Because these twins are separated from the physical customer, data privacy is upheld at all times.
Once you have these ‘twins’, you can create seamless personalized experiences that are tailored to them. But you can also look across your data to spot other users who match these profiles and create micro segments of customers with the same interests to deliver more powerful messaging.
Get in touch to find out more about how the SafeSignal Engine can help you turn insights into data activation.
Image credit: iStock/Farknot_Architect
Customer analytics is a vital part of setting the direction of any telco’s marketing activities. Without a clear picture of who your customers are, any campaign you run won’t be effectively targeted or personalized to the degree that today’s consumers now expect.
Getting customer segmentation right is easier said than done. In many cases, businesses’ efforts are hampered by complex data analysis processes that may require a large investment by the data science team or the use of third-party consultants to develop the right models. Because these efforts take so long and are so expensive to complete, […]
Customer expectations are now higher than ever as businesses strive to provide the perfect customer experience with a more personalised approach.
The telecoms industry holds some of the most extensive and detailed customer data of any sector. One major advantage for these firms is that the data they possess comes directly from their customers.