Today, brands have a treasure trove of consumer data as well as the ML tools necessary to interpret it — allowing marketers to get very granular with their outreach. We are reaching a point where marketers can use predictive analytics to create perfect, personalized marketing campaigns to send a customer at the right time — but beware! Using personal info the wrong way won’t make your messaging seem helpful. It’ll make it seem creepy and turn customers off. Fortunately, there are ways to use data and AI without creeping out your audience.
First, let’s identify what creepy marketing looks like. Mark Smith of MultiChannelMerchant gives a great example:
Imagine you take an Uber to work every day at roughly the same time. A notification or a prompt at that time reminding you to request a ride would be welcomed. However looking out of your window around that time and seeing a driver already waiting for you, before you’ve even had a chance to open the app, that’s where personalization can cross from convenience to creepy.
The most infamous real-world example was Target’s targeted pregnancy outreach, first reported in 2012. Based on purchase history, Target was able to develop a “pregnancy prediction” score to accurately deduce not just if a woman was pregnant, but also correctly estimate the due date. As Forbes reported, “What Target discovered quickly is that it creeped people out that the company knew about their pregnancies in advance.” Keep in mind, this was in 2012, and predictive analysis has since gotten better by leaps and bounds — so much so that marketers can reveal information about their customers that they didn’t even know about themselves. The question is, how do you use this information in a way that helps your customer and not in a way that makes them feel creeped out?
Provide a Human Touch
The first thing marketers need to do to eliminate the creep-factor is to make sure there is human oversight in the process. Think about it — how can you provide true, personalized messaging when everything is automated? Yes, machine learning is necessary for targeted marketing, but relying solely on machines to develop outreach campaigns for you is a recipe for disaster. People naturally feel uncomfortable if they believe some machine is making decisions about them, so provide a human touch, and show that there are warm people behind marketing campaigns that have the customers’ best interests at heart.
Katrina Taylor, head of UX and product design for the fashion rental site Armoire, states that companies should find ways to seamlessly merge automated and human interactions. “Because we are using an automated approach, we don’t want to follow it up with more AI.” Let AI enhance but not replace human interactions, and be sure that reports from human interactions become a part of the data set. In short, use the data, but don’t forget to use your eyes, your ears, and, most of all, your brain and heart.
On that note, following the golden rule is probably the most important thing you can do to prevent the creep-factor from setting in. Treat others as you want to be treated. If something seems creepy to you, it will seem creepy to your customers. Always put yourself in the shoes of your audience. Treat your relationship with your customer like a relationship in real life. Most people don’t like to reveal everything about them to people they just met, so why would a customer feel good about revealing (or having been revealed) everything there is to know about them to a company they are just getting to know? Remember that AI can’t be taught to feel empathy — so the rollout of your campaigns should always be overseen by a human.
- Tip: start slow in collecting data, and only with information customers might naturally feel comfortable sharing. As Taylor reminds us, “It’s better to start off with a light touch and fill in the details as we go.”
If a consumer finds out through an ad that their privacy has been invaded, you have probably lost them forever. Building loyalty always comes down to two things — developing trust, and providing value. Be completely open with your customers on why you are collecting data, and be clear on how this data collection benefits them.
For instance, Ventura Foods has made it a point to share their data with their customers. They share how data leads to business decisions, and then solicits additional feedback. In this way, customers feel like they are a part of the process and even offer additional data that they were not likely to give otherwise. Essentially, make your audience want to give you information. “When they know how we’re using their data, it motivates them to give us more data,” said Taylor. Customers should never, ever wonder how you got information about them, which is why it’s important to rely on your own real-time, 1st party data.
Remember that most customers want a personalized experience. A CSA study reports that 55% of US shoppers say they often sign up for personalization programs. That said, let your customers be in the driver’s seat, and give them reasons why providing information is of value to them. Lineate can help create an ethical and effective strategy using predictive analysis and other ML tools. To see how our AI team can help build what you need, reach out today.