A compelling data monetization plan articulates clearly how your corporate data will generate bottom line results for you. Your strategy should address four key questions:

  1. How should you approach monetization?
  2. What are the risks?
  3. What are the benefits?
  4. What are the costs to build capability and execute the strategy successfully?
This is the essence of data alchemy – converting something of lesser value into something of greater value. In the case of data monetization, it means using the data collected in your various business systems to achieve reduced costs, increased customer satisfaction, an expanded partner ecosystem, and an increased bottom line.



1. How should you approach monetization?

Building a monetization strategy begins with asking business questions. Here are some to consider:

  • How can we identify new revenue opportunities (new products/markets/customers)?
  • How can we improve marketing impact by enhancing personalization?
  • How can we identify and respond proactively to increase customer satisfaction?
  • How can we minimize customer churn and increase retention?
  • How can we optimize our supply chain by sharing data with our partners?
These are all specific instances of just one question:

  • How can we use our data to address our pain points more effectively?
Sometimes a monetization strategy will mean literally selling your data to third parties – but a simpler approach that often pays off more rapidly begins with using your data to improve your business decisions and optimize processes to reduce costs.

2. What are the risks?

There’s a reason I listed risk as the second question to consider when building your strategy. Many companies fail in their initial data monetization efforts. According to Gartner, nearly 90% of organizations claim low business intelligence and low analytics maturity are major obstacles to making use of their data1. And we all know that when new approaches don’t realize projected returns (for whatever the reason) most companies are inclined to wait a while before trying again – and in today’s rapidly evolving business climate, that decision can cost you. At the same time, data scientists and analysts are (still) a scarce commodity. According to LinkedIn, in 2018 there was a shortage of more than 150,000 of these specialists in the United States alone. All successful data monetization solutions are as good as gold – but often cost just as much, too. The good news is, you don’t need to hire expensive data scientists and/or buy sophisticated tools and systems to get quick wins and scalable insights from your data. You can leverage experienced partners like Luxoft, whose data scientists and software engineers have already worked on multiple successful monetization projects, to manage that risk and realize returns.

3. What are the benefits?

Investing in a data monetization strategy pays off. Check out two of our customer success stories:

  • A tier one telecommunications company partnered with Luxoft to monetize their data to improve sales, increase revenue by $1 million, lower OPEX, and reduce churn by $25 million. The company leveraged an online, real-time, big data-driven solution designed to deliver highly-individualized content aligned to customer behavior patterns. The patterns were arrived at by integrating multiple data lakes that fed a recommendation system that dynamically delivered content to 130 million consumers in real time.
  • A leading bank wanted to carry out advanced modeling of financial products and realized they had 35 years’ worth of data spread across 150 different systems. They partnered with Luxoft’s Excelian team of banking consultants and specialist data scientists/engineers. The Excelian team handled all the work to identify, clean, and integrate the data – and then set up the data pipelines – to help the bank execute on a successful strategy for monetizing its newly-prepared data assets.
4. What are the costs?

Deploying the right solution, with the right data science and data engineering to realize projected savings or revenue results, requires far more than engaging a data scientist to build models for you. Giving a data scientist a file with example data will often produce what looks like a win. But that’s just one piece of the project puzzle. As you can see from the examples above, most of the work (often more than 80% of it) in a data monetization project is data engineering: (1) identifying where data is stored, (2) integrating it into a system at scale, (3) creating the processing pipelines to put data models into production, (4) getting the results to the right decision makers fast so they can realize the business wins, and (5) implementing the necessary DevOps so the models can be refreshed or extended easily by the customers once the initial project is complete.




Data engineering needs specialized expertise that is often outside the knowledge of most IT consulting firms or data science firms. It’s the years of know-how accumulated by partners like Luxoft where we have delivered scalable data monetization systems across multiple verticals on-prem, in the cloud, or in hybrid combinations – with teams of experienced software engineers and data scientists who know how to work with one another and focus on one goal: getting you to success as quickly as possible. We can work with almost any big data / data science tools you have, whether it be commercial or open source. If you don’t know what you need, we can recommend systems to you that we know will work.

Data Alchemy: Getting you from data ingestion to actionable insights…fast

Data engineering needs specialized expertise that is often outside the knowledge of most IT consulting firms or data science firms. It’s the years of know-how accumulated by partners like Luxoft where we have delivered scalable data monetization systems across multiple verticals on-prem, in the cloud, or in hybrid combinations – with teams of experienced software engineers and data scientists who know how to work with one another and focus on one goal: getting you to success as quickly as possible. We can work with almost any big data / data science tools you have, whether it be commercial or open source. If you don’t know what you need, we can recommend systems to you that we know will work.

At Luxoft, we help our customers get to the data monetization payoff by doing that critical 80% of each job – the data engineering that delivers the workflow from start to finish, no matter where the data is, how fast it is coming in, or how fast you need results – so you can focus on using the insights delivered by the system to drive your business forward.

If you are interested in how to make the most of the data you’ve got, be sure to sign up for our webinar “The Alchemy of Data Monetization: Turning your data into gold” on May 29th at 9AM PST / 12PM EST, where you can:

  • Formulate a data monetization strategy through a 1-day or 2-day onsite workshop
  • Review successful data monetization projects from other companies
  • Learn about typical workflows and technologies used for data monetization 
  • Realize the importance of using data visualization to drive intelligent business actions
  • Find out why cloud-based data monetization solutions are the fast path to return on investment
1 https://www.gartner.com/en/newsroom/press-releases/2018-12-06-gartner-data-shows-87-percent-of-organizations-have-low-bi-and-analytics-maturity


Dr. Ken Urquhart
Dr. Ken Urquhart works with Luxoft global clients to identify and implement data monetization strategies to increase bottom lines. Previously he has enjoyed successful executive careers at Sun Microsystems, IBM and Microsoft. Since 2015, Ken has been advising startups on artificial intelligence/machine learning/blockchain and has delivered business strategies and new technology prototypes to global corporations. He holds three degrees in physics.