Technology and Trust: Two Vital Rules for Using Data Without Damaging Trust
January 13, 2020 by Leela Bozonelis
Data has made consumer targeting more precise than it has ever been before. This has opened the floodgates on how companies can reach consumers in more relevant—and, sometimes, creepy—ways than ever before. Don’t misunderstand using data to target consumers is a business imperative. Like most things, however, there’s a right and wrong way to proceed.
Done correctly, consumer targeting can bring welcome relevance to the types of content a person may see on a given day. Incorrectly applied, however, overly zealous targeting can feel intrusive or build a sense of distrust between consumers and industry.
Highly specific data targeting is still relatively new. Social and ethical norms are still being established, and many legislative bodies around the globe are working to catch up to protect consumers. This uncertainty leaves a sort of uncharted territory, where adventuring organisations are left to intuit boundaries by learning from others and listening to consumers.
To keep consumer loyalty and in turn to keep their business. Company leaders much make strategic choices when it comes to gathering and using consumer data. Thankfully, using data appropriately isn’t that different than building a relationship with a friend or colleague.
Data has become a currency unto itself. Give it the respect that reality demands. Don’t take without giving something in return, and don’t use it in a way that feels predatory. In short, be cool with it.
Being cool with data means understanding when things go a step too far and invade personal boundaries. Consider a real-life scenario. An observant colleague could notice certain behaviors that might make them suspect a coworker is pregnant: increased morning absence or tardiness, a change in diet or drinking habits, or shifts in wardrobe. Yet, it would be highly disrespectful and irresponsible to take those observations and tell others about the potential baby to come.
Despite this pretty clear social norm, some companies haven’t taken the hint. In a specific example, the retail giant Target used data to predict a teenager’s pregnancy and began sending marketing materials that were specific for a mom-to-be. Unfortunately, while the data was right the behavior wasn’t. The pregnancy-based marketing began before the news of the pregnancy was shared. In a second, a company’s use of data spilled over into the “real world,” and destroyed trust in the process.
A Target spokesperson commented saying after that incident, they started to hide targeted ads within other random products in their advertisements. This way the consumer would not feel watched and would believe that those targeted items were happenchance. Ultimately, the same ends were achieved with this shift in data-based marketing but done in a way that felt less intrusive
People trust and are loyal to people that make them feel good. People shop with that same sentiment. As author, speaker and consultant, Simon Sinek states “People don’t buy what you do; they buy why you do it.”
Similarly, people buy into brands that make them feel good, not brands that make them feel disrespected. If a friend made repeated intrusive comments every time you spoke to them, that relationship likely wouldn’t last long. Likewise, brands that deliver the same message over-and-over on multiple platforms for an extended period of time risk making consumers feel overwhelmed.
Manage expectations and feelings toward your brand and make smart decisions.If your company is giving a person anxiety about being watched, they are at the very least, subconsciously turned off by your product and will remember that when they go to shop.
In conclusion, when making decisions about using consumer data, it comes down to being strategic, ethical and creative. Like any relationship, make your partner feel valued and they will do the same in return.
1. Read more about big data and artificial intelligence on our blog.