Why are Data Monetization projects failing?
Data monetization is becoming a hashtag and a buzz word across several industries. However, the success of the hashtag does not match the real success of data monetization initiatives, with only few companies managing to implement streamlined and profitable data monetization projects.
One can consider that a company starts doing Data Monetization when it starts treating its own business data as an asset and is able to extract the benefits of maximizing its value, either for internal use, or through selling the data to 3rd parties creating a revenue stream from it.
It looks simple and logical, so why, and where, are the data monetization projects failing?
#3 reasons for the failure of Data Monetization
#1 Data is not gold
Companies (e.g. telcos) assume their data is worth gold, but there is a huge gap between the value that customers are willing to pay for the data. For the end customers, the value must be proportional to the value that the data can add to support business decisions. Furthermore, those end customers are used to working with proxies – at no cost – that help them support those same business decisions without spending money and time acquiring tons of data. For instance, if we want to understand which city areas have a higher concentration of people during the day, we can use a data layer with telco antennas (public data, free of charge) instead of buying mobility datasets (aggregated and anonymized) from a telco for an astronomic value. The accuracy and details of a telco's mobility data are far superior to the antennas proxy, but are the companies willing to pay for that next level of accuracy? How much is the additional detail worth?
#2 The bumped path from raw data to data product
The process of gathering raw data and turning it into attractive datasets ready to be sold to 3rd parties can be hard, and most companies don´t have the right resources to do it. The Data and IT consulting companies themselves lack the experience in this type of projects and often make them too complex and expensive. Even after reaching the stage where datasets are ready to be sold, companies face the problem of structuring its offering. How to make the offer available? Annual subscription vs One Shot Sale? How many time periods? What periodicity of update? Which format?
#3 Missing friendly tools to bring data to life
It´s not enough to sell datasets and pray for the clients to take advantage of that data. Even the most religious believers end up discovering that customers are failing to take the final step – the actionable step – that consists of transforming the data they have purchased into valuable insights capable of influence and support critical business decisions. Tools such as Mapidea (learn more here), capable of bringing data to life in a simple and fast way, are changing the game and can be crucial for the success of data monetization projects.
Data Monetization is here to stay, but companies need to change their approach on this kind of projects and stop thinking their data is the holy grail. Data Monetization projects need to be focused on the end customers pains: How are they going to acquire the data? Can they extract effective value from the data and ensure a positive ROI?
