Modern personalized marketing tools are incredible. With the right data about a user, you can tailor their brand experience to closely match their tastes, interests, and even elements of their lifestyle. You can market exactly the right pet products, outdoor gear, or even health advice based on what you can digitally learn about a customer, lead, or prospect.

But let’s face it: Personalization can also be creepy if not done correctly. The last thing you want is to give your customers or leads the heebie-jeebies. “Did it just say my name? How does it know I own a cat? Do I know you? Are you following me?”

There is an art to personalized marketing that is friendly and relevant to the user without creating the stalker vibe. That is exactly what we’re diving into today.

The Power of First-Party Data

First-party data is data that you collect directly from a user’s interaction with your website and brand assets. You can learn from their searches along with their browsing, shopping, and blog-reading history. Through this data, you can intuit a lot about a person, like whether they own a pet, have children, or do a lot of long-distance running.

First-party data is much more useful than third-party data, which is often generalized and bought from a broker, but it can be much more personal, as well. This can be good and bad. Personal data is more accurate and can provide a more tailored experience, but you don’t want to seem like you know too much, too fast, about a customer.

Like a good butler, the key is to make customer feel catered to, not creeped out.

Step 1: Introduce Yourself

One of the essential steps to friendly personalized marketing is to officially start the brand relationship. Introduce yourself. Use a floating chatbot greeting, a welcome email, or a special landing page for new visitors/account holders that welcomes them.

If through the chatbot or account creation, you have a chance to ask their name and a few important details. Otherwise, use language in your landing page that openly states that your goal is to personalize their experience.

This transforms the relationship from “You don’t know me, but I baked your favorite cake” to “I’ll be your personal chef, and I noticed you like chocolate”

Step 2: Ask, Don’t Tell

When personalizing the user experience, ask what the user likes and offer them options that your data suggests they will prefer. The conclusions that your personalization algorithm can derive from a few online behaviors are, admittedly, a little creepy when too-accurate. But asking again puts you in the role of an intuitive butler, rather than an unnerving mind-reader.

Drop little “this or that” surveys into the experience flow, or use language like “Do these interest you?” along with a personalized list of suggested products. Customers will feel the “getting to know you” stage of the relationship forming and have a chance to participate, rather than feeling like you “just know” what they might like.

Step 3: Show Your Work

When showing the result of first-data personalized suggestions, give the user a clue as to “how you know” that a suggestion might perfectly suit them. A little context can go a long way.

For example, the “People also bought” product section in Amazon suggests other products the customer might like while low-key hinting that it knows because the customer’s shopping behaviors match those of other people with similar tastes. It doesn’t say “You will want these things” but rather “Other people like you wanted these things”.

If you are offering items in their favorite color, open with a small graphic of items in that color they have bought in the past.

Step 4: Smooth Transition

After some time getting to know your customers and giving them a chance to tell you who they are voluntarily, you can smoothly transition to a brand relationship of personalized familiarity.

Greet customers by name in the UI when they log in or connect from a familiar device. Remind them of recent purchases with updates about orders on the way. From there, a fully personalized interface and product suggestions will make your customers feel like regulars at their favorite shop, where the digital shopkeepers have truly gotten to know their tastes.