Every single day, quintillions of bytes of data are generated. Businesses are collecting more data than ever before about their customers. Every click, every purchase, every action – all recorded in an ever growing data warehouse. The challenge in this new world is making sense of this data with customer analytics.
Or so we are constantly told. But perhaps the new challenge on the horizon is that customers are going to start selectively withholding their data. Not just the ultra-privacy conscious, but consumers en masse.
The end of free customer data
Data is often touted as the new currency for digitally-minded businesses of the future. But if consumers also realise the value of this new currency, then businesses will need a new strategy for engaging with their customers, and providing a compelling quid pro quo.
A new report by SAS Institute, the enterprise analytics software developer, finds that consumers aged 16 to 34 increasingly understand the power of their data, and view it as bargaining chips. This generation is willing to give up their data to an organisation only in return for hyper-personalised services. You may find very different customer attitudes depending on your industry. If you are a healthcare company, 67% of this generation will be comfortable sharing data with you. But if you are a retail company, that figure is only 32%.
A new business approach
In response to this new challenge, I believe that data-driven businesses must adopt a new thinking.
- Data should no longer be considered a free abundant resource only waiting to be collected and studied. Rather, it should be seen as an asset which can only be obtained through courtship of the data owners, with businesses having to demonstrate added value and trustworthiness.
- With the increased costs involved in obtaining data, a cost-benefit approach must be adopted. Whereas businesses may previously have been lured by the promise of big data into collecting as much data as possible, they will now need to be more selective about what they are willing to give up and for what type of data. This means a more focused customer analytics programme.
- Lastly, businesses need to think carefully about how they meaningfully engage their two groups of customers – those willing and unwilling to share their data. Any data collected will also need to be treated appropriately to account for selection bias (i.e. data collected from one group cannot be considered representative of all customers).