It’s a tough time to be a marketer in this era of Big Data. Massive breaches of data privacy such as the Facebook / Cambridge Analytica scandal, the frequent hacks of credit cards, health records or other sensitive information and the prevalence of identity theft are weighing on people’s minds. In a recent survey conducted across several countries, consumers expressed concerns about how companies collect data, how they protect an individual’s privacy, and how they use the information that they hold.
Governments around the world are responding with new data protection laws that impose tough penalties for violations – in January 2019 France charged Google €50million, and in July the UK fined British Airways £183million and Marriott £99million respectively, all under the EU’s GDPR framework.
That’s a chunk of money for getting it wrong – and yet, that data can be incredibly valuable, giving us the ability to understand our customers more deeply than ever before. With the massive amount of information available we can anticipate their needs, we can learn how best to persuade them to buy our products and services, and we can even predict how much each one might be willing to pay and dynamically adjust pricing and other details that they see at an individual level.
Most people are willing to give us their data, but ONLY in return for trusting that we’ll use it to provide them with added value and personal attention. Consumers expect brands to get to know them, to stop sending them generic email blasts, and to make specific offers and recommendations based on their previous purchases, preferences and interests. Getting this right generates much more positive response and brand sentiment – and of course, higher revenue.
On the flip side, fully three quarters of consumers get frustrated when web content isn’t personalised to them. . . But they don’t want it too personalised – no one enjoys that weird feeling of being “stalked” when adverts for a tropical destination that we looked up on a whim suddenly seem to be popping up everywhere that we go online!
So how do marketers and advertisers navigate between making productive use of data to create meaningful, personalised interactions with customers and prospects, while avoiding the pitfalls of losing trust, losing respect, and losing money?
The answer lies in developing a clear strategy around what data you need, how you’ll collect it, how you’ll store it, and how you’ll use it, in ways that comply with relevant laws and that enhance your relationships with your customers.
One big piece of this is understanding the difference between “first party” data that you directly own and are responsible for, and “second or third party” information that you share with partners, or rent or buy from external vendors.
First party data is most effective for targeted marketing because it’s information that’s gained through direct interaction with your own customers. And within this category is “zero party” data – things that the customer has proactively told you, such as their fashion preferences, or their attitudes towards the environment (as opposed to things that you know but that the customer didn’t actually tell you, such as items that they viewed in their shopping cart but didn’t buy).
Using zero party knowledge to create personalised messaging shows the customer directly that you’re listening and responding to their expressed needs. It’s a great way to sustain trust and goodwill, which in turn leads to long-term relationships and revenue.
Our new course on data & targeting tells you about these various types of data and their uses, talks about some of the technology involved, and gives you lots of ideas for different ways of personalising and making your marketing more relevant both to current customers and to prospects. There’s a lot of great data out there – watch this course to help you make sense of it!
Data and Insights
Ch-ch-ch-ch-changes! The Impact of the Digital Revolution on the European Media Landscape
In the early 1970’s Gordon Moore, co-founder of Intel, suggested the power of computing chips would …Read more