Profitable Location Data Monetization — 3 Lessons from a Telco Company

Zsolt Palmai
Starschema Blog
Published in
6 min readJun 19


Companies in many industries are hoarding piles of cash and don’t know it. Case in point: a telecommunications giant was sitting on massive amounts of anonymized location data that a variety of would-be customers were eager to pay handsomely for. How do we know? We helped them take that treasure trove of data and convert it into a sustainable, and highly profitable, revenue stream in just two years. Many lessons from this project extend well beyond the telco business and its technical implications to provide valuable insights for organizations from a variety of industries that have data and want to monetize it. Here are some key takeaways.

1. Know Your Data

If you’re reading this blog post, chances are you’re at least suspecting that your business is generating location data that might be valuable to others. Chances are, you’re right.

If your day-to-day operations involve electronic devices like smartphones, tablets and laptops, or anything that uses GPS, mobile cell towers, Wi-Fi access points, electronic transactions and PoS terminals, there’s likely geolocation data to be anonymized and aggregated. If you’re a telco company, you have access to a staggering amount of data of traffic and movement data — and the same goes for those involved in transportation, for example, only the nature and applicability of the data will be somewhat different.

Recognizing the availability of relevant assets and the opportunity that comes with it is half the battle. If you don’t immediately know what to do with it and to whom it might be valuable, that’s OK. Our client wasn’t sure either when they set out to create a new practice for data monetization.

2. Seek Out and Understand Demand — Starting at Home

Your internal teams might be your first customers for the location data you’re already producing as a byproduct of your everyday operations. How they’re using your data might tell you a lot about who else could use it and how. This was the case for our telco client, who relied on device-based location data for network and service optimization around the usage habits — specifically, the mobility patterns — of customers. Specifically, they were able to use their data to identify so-called “spatial bottlenecks” where improvements to their network would be the most worthwhile. The same core data, with its multitude of layers, could just as well be useful for a broad variety of other use cases to improve operations for organizations that don’t generate such data — or not in similar quality or quantities — as part of their business.

There’ll likely be more kinds of customers than you might assume off the top of your head. To get a clearer picture of your opportunities, it makes sense to brainstorm use cases with internal teams, share the types of data they have and find out how they think they — and others — could use it. Even internal PoCs might be worth exploring, as more successful ones can be turned into monetizable products later on.

Our telco client found recurring customers spanning the retail, tourism, consultancy and urban development industries. These customers used the data to fine-tune everything from advertising strategies to traffic planning. Meanwhile, specialized location intelligence companies constantly seek to procure data from various sources to build analyses that they can then sell to customers of their own, essentially acting as middlemen.

3. Put Nice Things in Nice Boxes

At this point, it might seem like you just open your vault and a multitude of customers will come rushing in — not so fast. Many other organizations have potentially valuable location data — so what, other than maybe the sheer amount or some unique content, will make yours more valuable than others’? The key is in the packaging. You need to ensure that the data is rewarding and easy to work with — that is, , clean, of high quality and accessible in an attractive the form most appropriate for your goals.

The business value of the monetized data is largely dependent on how clean and accurate it is, which means you’ll need appropriate data quality assurance practices. This will necessitate algorithms to clean, organize and aggregate data, as well as monitoring tools and processes. For our telco client, the introduction of “noise filtering” and new compression techniques for more efficient data storage and sharing made a big difference in how easy it was to provide customers with high-quality and easy-to-manage data. And, in addition to making it easier to satisfy customers, these innovations helped the company optimize operations and lower costs — which went a long way toward achieving profitability for their new data monetization practice relatively quickly.

The other key component besides data quality will be the form in which customers can attain your data. Common forms of monetized location data include packaged datasets, continuous data feeds, map-based visualizations, and PoCs that customers can adapt to their own use cases. And if you’re willing and able to build out additional capabilities, you can even go further — like our client did — and provide complete analyses based on your data, thereby cutting out the location intelligence middlemen.

Going back to the earlier point about understanding demand, how you will present your monetized data that’s up for sale will also largely depend on the preferences of your likely customers , so doing your homework about at least your core target verticals will help set the scope and direction for the strategic and technical elements of the eventual practice — and the investment necessary to make it happen.

Conclusion: Opportunities are Everywhere, But You Can’t Skip the Legwork

The modern data economy promises relatively quick and easy gains for a multitude of companies who’ve been collecting vast amounts of data as a result of their core business activities. In addition to the telco story that served as a basis for this post, we’ve worked with a range of very different organizations, including office equipment providers, to explore ways of packaging and selling data to satisfy sometimes highly specialized demand. But while the best practices we shared above apply in the vast majority of cases, there’s also highly individual strategic and technical needs that need to be properly explored and accommodated for each project.

In this story, we touched on some technical challenges like data cleansing, monitoring, compression, but they’re many potential challenges opportunities that were not discussed. The challenges will have very different implications based on your particular environment but will invariably involve tailoring your technologies and processes to facilitate your data monetization goals. The bright side is that such an undertaking is also a great opportunity to kill multiple birds with one stone and use the necessary developments to improve your data management practices and pipeline to also improve other business-critical processes.

If you’d like to explore ways to turn your data into a viable cash stream, we’re hered love to brainstorm and help you make the best decisions and get the most value out of them. Get in touch — we’d love to talk.

For the full story on how we helped a major telecommunications company set up a data monetization practice and make it profitable in two years, see the detailed case study:

And for location data monetization best practices for any organization, including how to successfully navigate the legal waters around the matter, dive into the white paper by one of our experts who also worked on the telco project:



Zsolt Palmai
Starschema Blog

Zsolt is Content Manager at data services firm Starschema, where he creates materials to help you learn about the company and enterprise-grade data solutions.