In defence of data monetisation: A dirty term that can improve CX
The idea of monetising data makes customer experience professionals feel uncomfortable - but it shouldn't.
My role involves working with businesses to use their data to create value for their customers, their partners and themselves. In discussions I have sometimes abbreviated this clunky description to ‘data monetisation’, frequently provoking uneasiness in those in the room.
For clarification, I should add that I am based in the UK, where we are still suffering from GDPR after-shock. And when I probe the reason for their discomfort, the implicit assumption is that data monetisation either violates the GDPR or other privacy-focused regulations (such as PECR in EU, CCPA in California and other state or country equivalents) or that it is ethically questionable – a fuel for the digital stalking that people fear will become more and more prevalent as new sources of data are added into the mix.
Time to reframe our understanding of data monetisation
In response I have tried adding ‘ethical’ as a prefix. But this just reinforces the idea that, without qualification, data monetisation is a bad thing to do – it equates to exploitation of the data subject – when that isn’t the case (or at least, it doesn’t have to be the case). So I think it’s time we reframe what data monetisation actually means:
- By pointing out that not all data is personal data so there is no risk of harm to individuals if it is shared.
- By drawing attention to the alternative ways of extracting monetary value from data that don’t involve selling it.
- By highlighting that personal data can be used to create value for multiple stakeholders – most notably the individual to whom the data pertains – from which the company will accrue value indirectly. (This is why personal data is such a huge value multiplier.)
- Because there are privacy-compliant ways of sharing data for either direct or indirect financial gain.
Direct monetisation – enablement of better decision-making and automation
Data does not have intrinsic value, it is not like gold or silver or any precious metal, its value is derived from what it enables – better decision-making. Decision-making can be made better on two primary dimensions – by increasing speed or enhancing quality.
In instances where there is a high volume of relatively unimportant decisions that need to be made, for example as part of an operational process, speed is of the essence. Making a good enough decision quickly is more important than making the best one slowly. Increasingly we are seeing these types of decision made automatically without human intervention, saving both time and resources, with data being the enabler of this efficiency uplift.
With decisions involving the allocation of scarce resources – where to spend the marketing budget, for example – getting the decision right is more important than making it quickly. When quality is the priority, data supports better decision-making by enlightening decision-makers about past experience and enabling predictions about likely outcomes under different scenarios. As such, it means resources can be allocated to where they will be most effective.
Whether these decisions in your organisation are made by humans or decisioning tools, ensuring that the required information is available at the right time in the right place with the right quality is a significant enhancer of organisational productivity and financial value.
Indirect monetisation – delivering a better customer experience
The same logic applies to customers’ decision-making – and this is where personal data has its greatest value potential.
As customers complete the journey to their desired outcomes, they also need to make decisions – some of which will be of high value and impact, with some being more procedural. (If your customer journey maps don’t flag the decisions made at each stage by each party and the data required to enable that decision-making, then adding that is an easy step towards delivering a better experience.)
The more you enable customers’ procedural decisions to be made quickly and effortlessly – for example, automatically completing a form for them using the data you have so they don’t have to decide whether to fill out the form or not – the smoother the customer’s journey will be and the greater the likelihood of their completing it with you.
When thoughtful consideration is more important to the customer than speed and ease, you can provide analyses – for example, product performance and reliability forecasts, what similar customers to them have done, customer reviews and ratings of the different services they are considering, etc. – to help them make a good decision. This will reduce stress and cognitive effort because you have made all the information required readily available.
In essence, data enables you to create a customer experience that is more personalised, is easier and quicker to complete, and delivers more confidence. All of which delivers value to your business in the form of higher conversion and retention rates, and lower costs to serve.
Indirect monetisation – creating value for other stakeholders
Similarly, there is a chance to deploy data to your benefit in your relationships with all your stakeholders – staff, suppliers, partners and regulators. With all stakeholders, there is a value exchange. Deploying data to help the other party to be more effective and efficient – make better decisions or save time or costs – the greater the value you can demand on the dimensions that are most important to you.
This might be better pricing and credit terms from suppliers, increased introductions or recommendations from partners, higher staff retention and, in the case of regulators, reduced risk of time-absorbing scrutiny.
Privacy compliant data sharing
The final way of monetising data does come from sharing it, either for direct financial reward or indirect gain, but not in the ways outlined at the top of this article.
Firstly there is selling a service based on aggregated data. There are a number of examples of this – banks aggregating customer spend in restaurants in different postcodes to provide restaurant chains with insights into the size of the local eating out market and intensity of local competition; telecoms businesses selling aggregated location data to retailers to help them choose where to site their next store; and smart car data being shared with traffic apps to show areas of congestion. (Aggregated data from other smart devices being the next area of opportunity.)
Secondly there is providing anonymised line item data, so that whoever receives it can perform pattern analysis and create predictive models without individual privacy or security being compromised. This relies on both individual consent and robust anonymisation protocols and there remains a risk that what appears robust now becomes less so in the future, for example with the arrival of quantum computing. But advances in privacy-preserving technologies, such as algorithms scanning encrypted data without ever storing an unencrypted set, should enable this type of safe data sharing to continue.
One example of this type of data sharing is patients agreeing to share medical data with researchers. Here the benefit is indirect – feeling good about helping those in the future who suffer from similar conditions. But sharing data can be of direct value to individuals. Joining up data from multiple services – banking transactions, retail purchases, media consumption, social media activity, internet browsing, etc. – provides an unparalleled insight into someone’s needs and what will create significant value for them.
The natural concern is that this insight could be used to manipulate and exploit people, and that clearly needs to be guarded against. But when used to benefit the individual concerned via proactive need recognition combined with the creation of highly personalised or customised services that are delivered at the right time and place, it is a powerful generator of value for customers, in which service providers will be able to share.
Data sharing is a relatively immature market at the moment and the challenges with joining up this data are not to be underestimated. But it is a key focus for governments, their first step being the introduction of PSD2 in the EU and its national manifestations such as Open Banking in the UK.
But the potential of data sharing to: enable innovation in the form of highly personalised or customised services, increase productivity (supercharge the efficiency and effectiveness benefits outlined above) and intensify competition (particularly in digital markets) together mean we are likely to see many more such initiatives. Indeed the UK Department of Business, Energy and Industrial Strategy is also looking to build on Open Banking via a number of new data sharing initiatives to cover communications, energy and digital services.
All of which will mean that the focus of data strategy needs to change from focusing on the data that your business has to focusing on the data that it needs. But that is for another post. In the meantime, happy (ethical) data monetisation.
Key takeaways for data teams
- Data monetisation is not something to shrink away from – there are multiple ways to increase the return on your data investments in a compliant and ethical way.
- Key to data monetisation is focusing on the decisions that all parties need to make – the business, your customers and your partners. Data is only valuable when it helps people make better – faster or higher quality – decisions.
- Monetisation strategies may also involve sharing or acquiring data from other sources. This is an area where there will be significant developments in the near future, so is one to keep an eye on.