Balancing personalization with privacy
In 3radical’s recent Consumer Insights Report highlighted how a decade of covert data sharing and monetization has harmed business reputation. 84% of people want more transparency when brands collect data. Consumers are seeing the value of their data and are increasingly selective about which brands they share it with.
By Linda Vetter, SVP, Marketing, 3radical
Another key trend highlighted in the report was the increase in consumers looking for personalized brand experiences. For example, 92% of consumers stated they would share their data with a brand if they saw the benefit of doing so. Consumers know that brands can create a more convenient, better experience if they share their data – but they need to feel trust in the company.
To walk this fine line, forward-thinking companies are enacting transparent data policies that give control to the consumer. Here’s how all brands can do the same.
Building blocks for a transparent data policy
Stop using third-party data, embrace Earned Data
When it comes to data, we would always recommend quality over quantity. Low-quality, stagnant data sets from third-party brokers are renowned for being unreliable. In any case, Google will soon be consigning third-party cookies to the history books.
At 3radical, we recommend taking an Earned Data approach. Earned Data is first-party information knowingly shared by the consumer. This is fully consented, high-quality data that will provide actionable insights for brands. Not only that, it won’t be touched by the increasingly strict government regulations that are being introduced across the globe.
Explain the benefits and follow through
Brands need to set up – and define – a mutually beneficial ‘value exchange’. This means brands need to be open about the information they would like to collect, detail how they will utilize it, and show how it will benefit the customer. If customers can see how their data will provide value (and won’t be used in covert, manipulative ways), they will be more likely to share their personal information. The incentive doesn’t just have to stop at tailored discounts either. Consumers are increasingly looking for personalized experiences with the brands they trust and are willing to share data to get a better service.
The flip side to this rule is not to gather data just for the sake of it. Marketers should have a clear strategy for any data that they collect and follow through with any promises. Brands that implement a clear and honest value exchange will reap the rewards of customer loyalty.
Give consumers control over their privacy preferences
More efficient targeting leads to better ROI. So it follows that allowing customers to tell you how and what they want to be targeted with, will lead to greater revenue. Why would marketers want to waste time chasing people who aren’t interested in your product or don’t use the channel you are trying to reach them on?
Provide tools that allow customers to control their data settings. Give space for customers to understand and update their data choices. This way, when marketers do communicate with them using that data, there is no ‘creepy’ surprise element to your marketing, and they will pay more attention to it.
What does this look like in practice?
Apple: helping customers understand data privacy
After the media attention around the ATT privacy feature, Apple has heavily aligned its brand reputation with its privacy features. Rather than trying to hide or deny privacy concerns, the company has a dedicated portal to explain how a lack of privacy can be a danger. They then explain how Apple combats the risks but still brings personalization to the user experience.
The ‘A Day in the Life of your Data’ document is a great example of how Apple is aligning with consumers, with an open, honest and accessible account of its data privacy policies.
Adidas: proactive preference sharing
Putting your customers in control means that they can tell you what they want to see. Adidas actively asks customers to share their interests and preferences. This allows them to provide a more relevant and personalized experience with fully consented information straight from the customer.
Netflix: better user experience
With such a huge catalog, it would be easy for customers to be overwhelmed by the scope of choice that Netflix offers. The recommendation service is a fundamental part of the user experience. Customers can indicate whether they liked a title or not, which is matched with behavioral data to provide effective recommendations of what to watch next. And it’s clearly effective – more than 80% of the TV shows watched on Netflix are discovered through the recommendation system. This is overt data sharing used as a seamless part of the service.