Improving Customer Experience in Telecoms with Geospatial


A guide to using geospatial to improve the Telecom customer experience, including network optimization, service personalization & targeted support.

This post may describe functionality for an old version of CARTO. Find out about the latest and cloud-native version here.
Improving Customer Experience in Telecoms with Geospatial

Key to the success of any business is customer satisfaction, and this is especially true for Telecoms. Customer expectations of telecom providers are constantly rising. Subscribers are no longer satisfied with just a satisfactory experience, wanting more than competitive pricing and high quality coverage. Telecoms customers now expect highly personalized services that cater to and anticipate their voice and digital needs.

In such a competitive industry,  service providers must meet and exceed these expectations to grow market share and increase ARPU... but how? Enter geospatial data.

Location Intelligence provides Telecoms companies with a much clearer understanding of their customers and service provision. In turn, this can help them to improve their services, new product offerings and ultimately increase customer satisfaction - both from a B2C and B2B perspective.

In this post, we’ll explore three ways geospatial data and analysis can help improve customer experience in Telecoms.

Exploring market potential for Telecoms in New York City.

#1 Network optimization

It is undeniable that providing consistently satisfactory network coverage is the foundation of customer satisfaction for Telecoms. 

Geospatial data can be used to identify areas with poor network coverage or weak signal strength, which can then be leveraged to:

  • Inform a network optimization strategy, such as helping teams know the optimal locations to deploy additional towers or upgrade existing ones. Learn more about this approach in this article covering how to use spatial analysis for 5G Rollout.
  • Predict changes in network coverage and quality, based on projected demographics, usage, and even weather data, to help companies preempt downtime and respond rapidly.

Curious about spatial patterns in network coverage? Explore the map below (or in full screen here) to understand residential internet coverage patterns across Washington state. 

If you’d like to replicate this map, sign up for a free 14-day CARTO trial, and explore the source data from the Federal Communications Commission here.

Leveraging spatial data science for Telecom network optimization has enormous potential that we couldn’t possibly cover in just one post. If you’d like to find out more about this, request a demo from our team of experts.

#2 Personalizing services & location-based promotions

As mentioned earlier, Telecom customers now expect personalized services tailored to their specific requirements. This enables marketing teams in the industry to be more targeted and, as a result, more cost-efficient with their service roll-out and promotions, instead of trying to offer everything to all customers.

One way to offer personalized services is by providing discounts on data usage or roaming charges to customers in specific locations, for instance:

  • Companies could offer free data packages around event spaces where Wi-Fi typically struggles to handle the high number of concurrent users.
  • Another approach could involve sending targeted alerts to customers when they travel within a certain distance of an airport, detailing international roaming charges and offering promotions for international data plans.

In addition to adapting services and promotions based on the facilities in an area, organizations could also adapt them based on the people in that area. 

Geosegmentation combines data points such as demographics, spend and online activity to score residents against particular profiles or market groups. A particularly relevant dataset is the Internet User Classification from the Consumer Data Research Centre. Machine learning has been used to classify users into one of 10 internet user types, such as e-Cultural Creators and e-Withdrawn - learn more about this classification here.

You can see this illustrated in the map above (explore in full screen here), which uses category widgets in CARTO Builder to illustrate the number of people in each user group, as well as their likelihood of using the internet in public spaces. 

You can find out how to replicate this type of data visualization - known as a dot density map - in our recent post “5 maps you didn't know you could create with SQL.”

Areas with a high number of "e-Cultural Creators" could benefit from higher levels of mobile data coverage so that users can seamlessly create content wherever they travel. Conversely, in areas where the "e-Withdrawn" are more prevalent, Telecoms could distribute educational materials to help residents get the most out of their Telecom service to avoid churn - or even assist them with external services such as online banking and travel planning.

#3 Location-based support

The final use case we’ll be exploring is targeted customer support. Location Intelligence can be leveraged to make support activities more efficient, with more resources being allocated to areas where they can have the most benefit. Examples of this include:

  • Pinpointing hotspots of reported network problems to prioritize network improvements in those locations. These improvements could be shared back with customers in those locations, so they can feel confident that services will be improved soon. 
  • Manage customer expectations in areas which are experiencing - or predicted to experience - lower service levels.
  • Provide location-based alerts to customers when they are moving to areas of lower coverage. This can help customers avoid frustration and ensure that they have a smoother network experience.
  • Provision of location-based customer support, such as guiding customers to the nearest store or service center.

You can explore an example of this below (or in full screen here) which shows the distance from every property in Washington, D.C. to their closest phone stores. This can be calculated in CARTO Workflows using the ST_DISTANCE component. Our example leverages Safegraph’s Places dataset - which you can access via our Spatial Data Catalog here - along with OpenStreetMap building outlines. You can check out our guide to accessing OpenStreetMap here.

An increasingly important focus for Telecoms is support for vulnerable customers, such those who are visually impaired or elderly. With the global population aged over 60 set to rise to 22% by 2022, meeting the needs of this demographic will increasingly factor into the success of all businesses, Telecoms included. 

Analysts can use demographic data - such as CARTO’s Spatial Features - to understand the distribution of these vulnerable customers to allow them to roll out more targeted customer support.


Interested in learning more about how spatial data and analytics can benefit your Telecom operations? Check out more examples here, or if you’re ready to start your Location Intelligence journey, sign up for a 14-day free trial here!