Enterprise AI

The personalization paradox

Personalization is often viewed as the Holy Grail of marketing. Virtually every company aspires to deliver experiences that are tailored to their individual prospects and customers. In doing so, they hope to build stronger connections with consumers and ultimately generate more sales. Make no mistake, personalization has the potential to be a real game changer. According to McKinsey estimates, giving prospects and customers personalized experiences has the potential to create between $1.7 trillion and $3.0 trillion in new value.

As a result, many marketers are turning to personalization tools to help them create custom digital experiences for consumers. A classic use case might look something like this: On a rainy day, a buyer decides to visit a retail site that sells outdoor clothing and equipment. Upon getting to the site, they’re pleasantly surprised to discover that rain gear is not only featured front and center, but that it’s also on sale. What they assume is a random coincidence is actually a case of the retailer using a personalization tool to match what it knows about them (in this case, their location and the current weather conditions there) with the products they’ll most likely to need at that particular moment.

While scenarios like this sound good, the problem is that they don’t always go according to plan. In many cases, rather than bringing businesses closer to their customers, personalization can actually raise red flags and drive a wedge between them.

What is personalization?

Personalization is about more than simply greeting a person by name in an email or showing them the same ad over and over again because they happened to search for a particular product in the past. Instead, it’s about understanding the characteristics and behaviors of your most important audience segments and then using that understanding to create relevant experiences for them.

In an ideal world, with personalization at scale, consumers who live in a city where it’s raining might be presented with rain gear to buy. Meanwhile customers who are environmentally conscious might get presented with information about how the company’s products are produced sustainably.

The idea is to align specific audiences with the products or messaging that’s most relevant and compelling to them. By doing so, the goal is to create a compelling experience that fosters a sense of connection between the consumer and the brand, and ultimately gets consumers to take the next step down the path to purchase. Of course, it doesn’t always work out that way.

Personalization pitfalls 

While giving customers a personalized experience sounds great in theory, in practice it can be highly problematic. At issue is the fact that today’s consumers are highly sensitive to data privacy issues. Walking the line between delivering a compelling experience and raising unnecessary data privacy concerns is fraught with challenges.

While most people know that data is being collected about them every time they go online, not everyone appreciates the extent to which that happens or the fact that their data is ultimately a commodity that marketers are more than happy to buy.

Unfortunately, marketers often run the risk of taking things too far. Using data, whether purchased or collected organically, they can create personalized experiences that leave people feeling creeped out. Target famously did this when it realized one of its teen customers was pregnant based on her online shopping habits and subsequently sent coupons for baby-related products to her home address. The problem was, she hadn’t told her family yet.

When things like this happen, instead of delivering the kind of personalized experience that was intended, consumers wind up getting turned off and losing any trust they may have had in your brand. Underscoring the point, according to research from Gartner, brands are at risk of losing 38 percent of their customers thanks to marketing personalization attempts gone wrong.

Delivering relevance while maintaining privacy

To get around these pitfalls and create long-term relationships with customers that are built on trust, we need to improve our data game. That means never collecting, using, or storing your customers’ personally identifiable information (PII). It also means putting a stop to that unreliable and potentially dangerous third-party data.

We get it, easier said than done. Thankfully, we have a solution: the Trusted Signals Exchange. Instead of relying on PII to deliver relevant experiences to customers, it pulls what we call signals from rich behavioral data to create accurate predictions or what a customer might want at a specific point in time. That way, when they show up on your channels, they get an experience that’s reliable, safe, and relevant.

The result? All the upside of personalization without any of the risks.

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