The 3 Rs of Data Fusion

Data is not just the language of IT and business, it is increasingly the language of everyday life. It’s the fuel for the connections for the engines that allow us to talk with friends online, order food, or stream TV or movies. It’s also what fuels relevant and timely suggestions such as a baggage advertisement just in time for an upcoming trip and the fuel that keeps the services and websites that provide us with such valuable and entertaining content, available. and free for all.

But there is a problem. Shocking headlines about data breaches coupled with fear-based click-bait campaigns and “all data is bad data” have created confusion, fear and mistrust among people. For the fearful, the only answer is a data lock, more restricted use cases, and limited players. This could mean that the flourishing data environment that has been the basis of exciting new innovations online could become a relic of the past while another problem is that data becomes more centralized for a few big players, limiting competition and actually working against those who hope to limit the amount of data organizations hold.

The reality of how data serves people is lost in the confusion. There is a general misconception that data is dangerous, which is why all companies that use it are dangerous. The result is that the good actors have been mistaken for the bad, and good use of data with bad use – it all comes together.

So what’s next?

First, it is important to clarify the wide range of data that exists today. Data can range from non-sensitive data, like the type of car you drive, to more sensitive data – called special category data such as ethnicity, political leanings, and religious data. When the distinction is not clear between the two, they merge together, increasing the risk that people will think that all companies have access to all data, which is nonsense. The vast majority of the time when advertisers and marketers talk about data, it is non-sensitive data.

Above all, it must be recognized that there are bad actors whose aim is to ignore or break the law, steal data, commit identity theft and abuse data for their benefit. Of course, this activity must be stopped, prevented and punished. The actions of these criminals cause disproportionate worry and harm to people, but most other organizations use data not to harm people, but to serve them, it gets lost in confusion.

To reduce confusion, it is clear that some of the misinterpretations and fear need to be explained to help people understand databases and their use. A logical start is to help people understand that not all businesses are in the same position. These three simple classifications should help people better understand how businesses work with data, reducing confusion and fear, while increasing choice and confidence:

The Manager: These brands know the rules for the proper use of data and undertake to apply them. They use data to understand both current and potential customers, make better connections between information, and deliver better experiences. This includes making loyalty programs work, providing special offers based on past purchases, making marketing and user experiences more meaningful to improve people’s daily lives. Most of the brands that the public knows fall into this category.

Data is not inherently bad, nor is it equal

The Revolutionary: These are the technological innovators. They usually seek to resolve customer issues, some of which were previously unknown, and when they are successful they grow quickly. They don’t have bad intentions, but they represent the vanguard. Many of the benefits that people rush to take advantage of are actually made possible by data. The public should be reminded that new services – such as digital maps – in the palms of their hands are free because the data is used to show us more relevant advertisements. And here you have to be careful, as rapid innovation risks overtaking regulation, potentially creating an imbalance between customer and business advantage.

The Repentant: These are brands that have encountered a problem. They might be big brands, but they made a mistake that left their proverbial data door open to an incident such as a breach. The brands that are found here have a choice. Acknowledge the mistake, be responsible and take urgent corrective action or fail, burning customer trust. Respected brands that have slipped surely have no intention and can recover, but only through swift and transparent action.

Bottom Line: Data isn’t inherently bad, and it’s not all created equal. If the public does not understand this, a lot of things are in danger. Brands serve people, and people reward them with their attention and expense. It’s a fair exchange, and the use of data by responsible organizations is part of what makes the modern world go round.

Confusion by default demonizes data and masks the many benefits people derive from it, such as the largely free Internet. Despite the sensational claims that every person is watched, manipulated and monetized, data fuels our economy and fuels meaningful connections between people and brands. The data alone is neutral. But when put in the hands of trusted brands and smart innovators, it has the potential to improve the lives of all of us.

It’s time to start simple and break it down, to encourage people to understand the basics of drawing attention not to the data as one, but to the data that matters most.

Jed Mole, Marketing Director, Acxioma

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