As public fury rages around Facebook, Cambridge Analytica and the intrusion of privacy, we as marketers need to recognise the paradox between this consumer anger and the proven value of personalised customer experience. We need to resolve this paradox, in order to move forward positively and meet the requirements of both our shareholders and our customers.
The use of data in marketing suffers from a fundamental conflict between two customer needs:
- Data effectiveness: Customers expect us to deal with them intelligently, communicating with them according to a complex set of preferences in order to give an optimal experience, usually at low cost, facilitated by digital communication.
- Data responsibility: Customers often perceive the collection of data about them to be irresponsible and intrusive, imagining us tracking and storing their every move. In addition, they often worry about the use and security of personal information, lowering trust in our brands.
This conflict will remain as long as brands continue to rely on data that is poorly focused on the specific consumer insight they need to generate value – data that it is often purchased from third parties. Such an approach means that brands either intrude across a wide arc of their customer’s lives to poorly calculate their preferences, or they simply frustrate customers with an utterly impersonal and unintelligent experience.
There is an alternative approach that resolves this paradox using small quantities of psychologically-focused first-party data. This gives a detailed understanding of how customers think, feel and choose in the specific context that a brand needs to deliver value to the customer. This specificity increases the power of the data while preventing the brand from intruding on the customer’s privacy.
People are surprisingly diverse
As humans, we accept that we are all individuals and so it is unsurprising to be told that we behave in unique ways. What we miss is that the diversity is not just between us but within us. What we truly love about the people we are closest to is their idiosyncrasies, the unique way they blend diverse ways of dealing with the world. I might like extreme sports but shy away from financial risk. I might be outgoing with friends but be extremely anxious when I make a presentation.
In psychology this is called context-specific behaviour. We vary so much in different contexts that it is scientifically proven our behaviour is only 10% predictable, using even the most accurate measurement of our general psychology. Conversely, psychological information that is context-specific can predict our behaviour with 90% certainty.
This fact tells us as marketers that our data must be highly specific to our brand and product type if it is to inform our marketing endeavours. For this reason, third-party data is highly unlikely to help us deliver personalised value to our customers. This fact also ultimately leads to the idea that past behaviour is the best predictor of future behaviour. Given this, why isn’t context-specific behavioural data transforming the power of marketing?
The right data is about the right question
What data do we marketers require to know how to change a customer’s perceptions of value, so we can change their behaviour in the specific context of our brand or product? When we ask this question, it’s immediately apparent that data that describes historic behaviour might help us predict, but not change their future behaviour. The difference between knowing how to predict behaviour and knowing how to change it is both large and critical.
Imagine you know that a consumer buys Coca-Cola most weeks, in preference to Pepsi. You as a Pepsi marketer might naturally assume they are a good fit for Pepsi advertising, and that it is easier to change their brand loyalty than to persuade them to switch from a less related non-cola beverage. For this reason, the behavioural insight feels helpful in that it tells you that this customer should be preferentially targeted.
Psychological information that is context-specific can predict our behaviour with 90% certainty.
What the insight doesn’t tell you is why the consumer buys Coca-Cola preferentially to Pepsi or, even more importantly, what kind of messaging could change that preference and overcome the power of Coca-Cola advertising.
The data tells you who drinks Coke, not how to influence them. Once you understand what is needed to influence these consumers (as well as those in other behavioural categories), it’s often the case that these customers are in fact not the easiest to influence.
The data that is truly needed in this case is contextually specific and psychologically focused rather than general or behavioural. As the Pepsi marketer, you need to understand the mental processes of a consumer to a greater level of detail than your competitors, so you select your audiences more effectively and ensure your messaging has a unique advantage.
Collecting the data you really need
Until recently, data that could be collected at any scale has been behavioural and demographic. This data is easy to acquire, and a whole industry is dedicated to convincing marketers that collecting and storing this kind of data is the key to delivering game-changing results.
The reality is, however, that most brands build up vast and disparate databases of customer data, at considerable cost, yet remain unable to create much tangible benefit from it.
Scaleable psychology and digital psychometrics have now made it possible to map out how individual customers think, feel, choose and perceive value, at the scale of your brand’s whole audience. This data tells you about your customer’s preferences – what they value and how they like to be communicated with.
To balance the increase in marketing performance with the practicalities of increased marketing collateral, each customer is placed in no more than one of 60 preference categories. This means that, over time, this data has a very different quality; instead of it simply growing in volume while often decreasing in usability, it simply becomes more accurate in terms of placing the right customers in the right categories.
You can resolve the paradox
Initially it may seem the use of scaleable psychology is more intrusive to the customer, but in fact the opposite is true. Committing to only using context-specific, psychologically and value-focused data has huge perceived benefit to the consumer:
Customer-focused: You are only holding and storing the customer’s relevant preferences to your brand or product and using that information uniquely deliver value to your customer.
Transparent: The data you hold, what it is used for and the way it is processed are all clearly defined and easy to understand.
Non-intrusive: You are not intruding into other areas of the customer’s life, and the information is used responsibly to understand your customers and deliver value.
Secure: Databases of demographic and behavioural data can be used for malicious purposes. In contrast, someone’s specific preferences about how they understand or value car insurance, for example, does not pose this issue.
Being ahead of best practice
GDPR is not the end of the legislative road, as the conversation will soon switch to e-privacy regulation, expected to come into effect in early 2019. The direction of legal travel is clear. Storing lots of general data on consumers and not being transparent as to its purpose and usage is going to become ever more legally perilous. The freedoms enjoyed by media owners trading third-party data are also going to become severely curtailed.
Being ahead of the curve is going to be about first-party data strategies. You will be pushed for ever more transparency and responsibility over your data usage. Brands that stay with the current data methodology will experience a painful reduction of their marketing capabilities.
Embracing context-specific and psychologically-focused data, and committing to only gathering data that actionably delivers customer value, is a positive way forward. It is better for the customer and more effective for the brand. This data is both secure and not personally identifying (as preference categories tend to contain tens of thousands of consumers), keeping brands outside of the costly world of GDPR non-compliance. It also allows transparent and understandable consumer messaging around data, avoiding the necessity of endless legal jargon and improving consumer trust.
Richard Summers is chief scientist at neuroscience research company CrowdCat