Enabling Data Monetization: Defining Terminology
Many organizations don’t have clear definitions of what terms mean and how to use them. Everyone understands the implications of terms like “attrition rate,” “customer acquisition cost” and “customer lifetime value,” but how are they calculated? Which parameters are used and which are most important? What are the KPIs by which you operate, govern and grow your business? Without clear terminology backed by metrics that adds real meaning to it, you can’t answer business questions in part or entirely, or in a timely manner, or with any degree of confidence in the answers you get. For assistance with correctly defining your terminology, talk to Integress.
We see time and again how organizations will do a marketing campaign and say, “We got a thousand people.” How would they know if that’s good or bad without context? If you spend a million dollars to gain those 1,000 clients, and your cost of acquisition is $1,000, your customer lifetime value is $100. That’s horrible. But if your customer lifetime value is $20,000, that’s great. You want to understand who your customers are, how you segment them and which customers are best targets for a particular marketing campaign. You need to know what to measure and why you are measuring it and what you are looking to achieve.
- Back terminology with metrics to clearly define terms
- Quantify and prioritize KPIs by which you operate, govern and grow your business
Address additional tips to better prepare for successful projects by downloading our FREE whitepaper, Enabling Data Monetization: A Playbook for Handling Common Challenges.
The term “data monetization” was first associated almost exclusively with selling and trading data to attract and enrich partner relationships. Recent innovations like master data management, modern BI tools, and advanced analytics, provided organizations with new ways to monetize enterprise data to increase revenue and profit, improve operational efficiency, and realize new revenue streams.