Exploring value exchange: Can we put a price on data?

9th Dec 2011

Are your customers aware of the value of their data and their role in a value exchange model? And if not, should they be? 

In the first article of this series we discussed the existence of a value exchange, and the ambition of brand marketers to elevate their relationship with consumers from a commercial to an emotional one. What is clear is that wherever a particular brand is on this journey; information and data are critical elements in helping them understand customers. Without these elements, any form of interaction will simply not work.

But are consumers conscious of their role in a value exchange model, or indeed of the inherent value of their data? And if not, should they be? 
On paper, the value exchange model itself creates a fair balance between what is entered into the exchange – customer insight – and the resulting outcome for the customer, whether that’s a commercial reward or an emotional experience. It’s also safe to assume that it’s not just those of us working in the marketing industry that realise brands are ‘taking note’ when they interact with us. We recognise that supermarkets – blazing a trail through their collection and use of customer data – hand over personalised vouchers to the customer at the till, offering discounts based on their recorded purchasing habits. 
It doesn’t take much of a leap to make the connection between a penchant for double chocolate ice cream and a discount off every other purchase. Yet this monetary reward is relatively small considering the value of the data that the consumer is providing. Currently, the consumer probably fails to comprehend that their true value within this exchange is really ‘worth’ more to the brand than a 50 pence coupon.   
In practice, the consumer is not consciously attaching a price to their personal data. This unawareness allows us to use their data to generate true customer intelligence and deliver an emotionally charged experience to an individual. But will this be possible in a world where consumers are rapidly becoming more aware of the role that data plays?
The best of both worlds: buying and observing data
Customer intelligence is achieved as a result of two main insight approaches. The first is the ‘bought’ data/benefit exchange we’ve already discussed, where the brand indirectly purchases information from a consumer. The second is an observational exchange. Here the brand observes the consumer, notes their behaviour and infers insight based on their actions. In many ways this could also be described as an ‘unwitting’ value exchange, where the consumer is making information of value available – without realising it. This information might be gleaned from looking at items purchased and returned, what brands they’ve bought, and time of purchase. 
A further example is insight generated from ‘nudging’. This is where we observe whether the consumer opens and reads an email, clicks on a link, or responds in some way that indicates some thing about them. Gathering a combination of both these ‘types’ of data powers customer intelligence and deepens customer engagement. 
Amazon is the classic example of a brand using both forms of data to good effect. As customers, we readily hand over a set of basic but vital data: our name, address and other contact details. If we’re in the mood, then we’ll offer information on a ‘wish list’ – indicating items we’re interested in, or would one day like to purchase. Transactional data on the products we actually buy augments this. Amazon also observes our site browsing habits, responses to emails and banner click-throughs. They then combine this knowledge to improve our experience by suggesting products and services it thinks will appeal to us. 
This method of delivery isn’t perfect. Buy a present for someone, and you’ll forevermore be recommended similar products that aren’t appropriate to you. You may buy an item elsewhere with no way of letting Amazon know that you don’t need another one. But even with these shortcomings, we can see the potential of bringing different sources of data together. And if Amazon could convince its customers to share more about the products they already own? Imagine the positive way its recommendation model would change.
Observational opportunities
The opportunities for ‘observational’ data are rapidly expanding in correlation with the development of online touch points and specific social media interactions. This is increasing the volume of insight that can be gleaned by observing the consumer’s behaviour, while potentially decreasing brand reliance on the ‘bought’ data /monetary exchange model. This shift can pose significant problems.
IBM’s 2011 global CMO study found that almost 90% of UK marketers feel ill-equipped to deal with the overwhelming “volume, velocity and variety” of data. The cost of tooling up to meet this wave of ‘big data’, and the pressure to prove the ROI of any response, were cited as the biggest barriers. It’s clear that far from being an instantly viable stream of free insight, observational data presents marketers with a significant challenge. 
Let’s also not forget the legacy of investment in CRM systems, and the ongoing quest by many to create a workable single customer view. Countless organisations had their fingers burnt in the rush to invest in large and unyielding technological ‘solutions’ that rarely delivered their promise.
So getting the balance right between these two methods of data generation is vital – as is creating an efficient means of managing this. It not only provides an accurate and insightful view of an individual consumer, it makes the entire process cost effective. Otherwise a serious marketing misconception remains – that all data has value. It doesn’t.
Putting a price on the consumer’s head
Data is not valuable on its own. The value only exists if the data is correctly interpreted and profitably applied, regardless of its point of origin. The term ‘customer intelligence’ is a deliberate one – it describes the creation of intelligence from what we know about an individual. It’s about converting information into insight; insight that has the potential to create a value exchange that ultimately delivers the desired commercial or emotional outcome to the consumer. And whether we buy data from the consumer or invest in observing their behaviour, we can only create a valuable return if we do something with it. 
Amazon would love to get its hands on a list of my music and film collection – this data about my tastes would drive tailored recommendations, leading ultimately to more sales. They want relevant data to recommend and sell me products. But would it care so much about knowing my favoured holiday destinations? Or my food and drink tastes?   
There’s a real risk in collecting any and all data available and storing it on a database, without having clear objectives for practical applications. How often are we told something by, or ask something of, a consumer, only to not use it? Collecting anything and everything ‘just in case’ doesn’t lead to customer intelligence.
When it comes to how the customer perceives the value of their data, we know that observed data has little value in their eyes because they don’t know observation is taking place. Yet in the value exchange model, the very act of asking a consumer for information could prompt the question of why we want it; and what will they get in return.
Consumer comprehension of data value
Currently most consumers don’t consciously associate a price with the data they are providing brands in the value exchange. However, as consumers we are becoming rapidly more aware of the role data plays in our interactions with brands. Consider the role of aggregator brands in the financial services sector. In a short space of time we have come to trust these sites with a wealth of valuable information on our financial situations and insurance needs. We understand that by providing enough information we will receive a better price in return; centred on the best deals available to us. The end goal remains a commercial one, but the deals we seek are delivered through the provision of a service that can only work as a result of us knowingly and purposefully handing over our data.
How brands are using our data is also becoming a big, widespread conversation. Debates include the very public discussions over what Facebook knows (or is trying to know) about us. The application of the edited ER. High-profile brands publicly discussing the use of insight, and increasing infringement of Data Protection regulation. All these well-publicised debates flag up the importance our data now commands. As marketers, our immediate concern is that consumers will start to consciously place a price on their data.
It’s really only a matter of time before this consumer awareness grows to such a level that it will impact the marketers’ ability to collect data, or use it to deliver campaigns based on powerful insight. In this scenario we would be left in the position of having to revert to creating campaigns based on data gleaned from lifestyle surveys and derived data sets – hardly the promise of the information-age. Marketers need to prove to consumers, and quickly, that unlocking the value of their data is about more than a commercial outcome so that consumers do not increasingly chose to opt out of providing any ‘bought’ data. With the value exchange we’re offering, it becomes about an emotional benefit. We then need to invest appropriately to build our sources of ‘observational’ data.
Commercial and emotional outcomes: making data value about more than a price
Some marketers will see raising the awareness of the value of ‘bought’ data as a bad thing, because it risks setting up the expectation in the eyes of the consumer that they will receive a monetary reward in return for them sharing their information. If this happens, consumers savvy to the value of their data could hold off on the value exchange in hope of a better ‘return’. The result is a competition between brands based on the ‘best offer’. This manifestation would quickly damage the very foundation of the value exchange model. If brands all sell the same product and are forced to reward consumers with discounts, then price becomes the only differentiator. Anything else is unprofitable. The stark truth is that this approach is already doing considerable damage to the retail landscape.
This scenario supports the need to raise the outcome of the value exchange of ‘bought’ data from a commercial to an emotional level, with the offer of an enhanced consumer experience. If the consumer expects something else – namely that we will make the right decisions and choices based on our view of them to vastly improve their experience of the brand – the dynamic instantly changes and ‘value’ becomes a misnomer for the real return that is being presented. By engaging with consumers on an emotional level, the relationship with the brand becomes deeper and longer.
The Royal Bank of Scotland Group (RBS) has just announced an expansion of its ‘helpful banking’ proposition, which will trail a ‘Helpful Live’ forum. Here, its customers can converse with the brand’s representatives to offer feedback and suggestions on the service and services they receive. RBS hopes that by soliciting this kind of feedback it can improve its service offering and develop its helpful persona. But how else could this data be used? 
While RBS’s goal is to “actively seek out customers’ suggestions on how we can become more helpful”, they can still use this information to improve the experience for individual customers, as well as across the board. A particularly enthusiastic individual choosing to engage with the brand to offer their thoughts on good service is doing so on the promise of something in return. But this return isn’t based on a price or commercial value. It’s based on an improved emotional experience.
This hints at the huge potential within the value exchange. Think how much more informed marketing decisions could be when we have access to a rich vein of relevant insight. Let alone the depth of the consumer’s response to an emotionally charged interface.
The interface is all that matters
Our marketing solutions need to come from a combination of ‘bought’, observed and inferred consumer insight, along with an awareness of why this data is being sought and how it will be used. But what does the consumer then experience? It’s the interface between the brand and the customer that ultimately delivers the proof that customer intelligence is able to create a brand experience that is a positive and welcome encounter, and not just one about selling.
Mike Fisher is chief futurist at Indicia.
The next feature in this series will illustrate how the creative interface can be used to help the value exchange take place – connecting customers with brands at a deeper and more intimate level. In the final piece, we will explore some of the challenges facing organisations as they remodel their businesses in an effort to place the customer at the heart of all their operations.

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By bmonger
12th Dec 2011 21:45

Re: "In practice, the consumer is not consciously attaching a price to their personal data."

I disagree with this statement.  The consumer has a concept of value about supplying personal data - it is what they need to do to get something in exchange.  They may not have a fully developed value concept because they haven't studied it.  They are unlikely to have the meads to do so.  Nor will their concept of the value be the same as the "buyer" of the data input.  But like in any exchange, the consumer will have a concept of value,  Especially in respect to the possible risk I think

-- Dr Brian Monger

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By Mike Riddell
13th Dec 2011 13:28

What this article describes is VRM.

Innocent people are unaware of the value of their data. Our business is designed to inform the public of this value and act as a third party on their behalf to leverage its value and redistribute it in proportion to the amount of it they volunteer.

I'm sure we aren't the only business in the world working to such an agenda.


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