Turning raw data into a new revenue channel

You must have heard the saying that ‘data is the new oil’, but companies are finding that this oil is difficult to sell and monetise. It’s like having all the raw materials to bake a cake but not knowing how to mix them together to prepare it. The analogy is especially true where companies have built lots of data over the years but just don’t know how to monetise or even come close to taking commercial advantage of it. There are of course many ways it can be monetised, if you have the right principles in place.

Different ways of monetising data  

·     Revenue model – Facebook did not have a proper commercial model until 10 or so years ago. But then came the personalised ads based on the data Facebook holds of us and the data we give Facebook free of charge. It was only through this data that Facebook developed its paid advertising model on its platform. The beauty of Facebook ads is that they can be highly personalised as they contains geographic, demographic and attitudinal information from us (where we have given permissions). This makes the ads highly personalised. Facebook has earned $114b from its advertising revenue. Most of this revenue can be attributed to the level of data and personalisation sophistication it has in its platform.

·      Data partnership - partnership with companies that hold relevant data is another way to monetise data. A good example of this is mindfulness apps. Until recently, they were facing an identity crisis, as people were not signing up for, or thinking they didn’t need one. But then came Fitbit, a company that collects health-related data such as ‘stress levels’. Some of these apps partnered with them. Only when customers found that their stress score was too high (through Fitbit data), did they realise the importance of mindfulness apps and started subscribing to their services. It was the Fitbit data point that led to the huge monetisation through subscription for mindfulness apps. And through the process, Fitbit also earned commission from these apps.  

·      Money from open source data – there are various ways you can make use of free open source data to monetise your proposition. Take the example of companies like Mintel or Data Monitor, who extract freely open source available market data from data repositories like data.gov.uk, add qualitative data from surveys to these, create insights reports on various business sectors and sell those insights.  

·      Collaborative data sharing – data monetisation is not limited to bigger corporates. There are various ways in which small companies can come into data sharing agreements and drive revenue. For example, tourism companies sharing trends and data with hotels, restaurants, local entertainment businesses, can be in a win-win situation. One example is a small real estate agency providing local property market trends, helping other businesses and individuals make informed decisions.

·      Data consortium - another option is to build a consortium of data to share anonymised data for benchmarking purposes. By collaborating on data analysis, SMEs can collectively gain insights that benefit everyone involved while maintaining data privacy and security.

Speed Read - checklist of ways to monetise your data

·      There is no one way of monetising your data assets and you can monetise your data asset in many ways

·      You can monetise it by directly selling, partnering and sharing data, setting up adata consortium, monetising insights from data or using insights to set up advertising platforms

·      You don’t have to be a big corporate to monetise data

·      Non-personalised data can also be monetised for market insights and benchmarking

In a nutshell, data in not the new oil until you monetise this oil, datais just a raw material and unless you have a model to monetise it, it will remain an unused, underutilised entity with little business value.