Know Your Audience
Learning Objectives
After completing this unit, you’ll be able to:
- Determine a strategy for data gathering.
- Explain the difference between implicit and explicit data.
- Validate existing data.
Data Gathering and Validation
It’s time to start using your brand-new preference center to gather more data through a data gathering or validation campaign. Let’s go through some examples.
Welcome Your Subscribers
In all relationships, it’s important to make a good first impression. This is also true for your new subscribers. You can put your best foot forward with a thoughtful welcome campaign that leads a subscriber through a series of emails. Hint: A welcome message is the best time to ask all those questions you have for them. And it’s when subscribers are most likely to respond. Win-win. Here’s what a welcome series could include.
| Email Description |
Example Message |
What to Include |
|---|---|---|
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Welcome Email One First email sent as soon as someone registers for your emails. |
Thanks. We like you too... |
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Welcome Email Two Email sent a few days later that reinforces your brand and asks for more information about the subscriber. |
We want to learn more about you... |
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Welcome Email Three The third email sent to the customer uses information the subscriber provided or asks for that info again. |
See? We get you... |
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Learn More About Subscribers
If you've been friends with someone for a while, you probably know lots about them—like where they live, the names of their pets, or what types of trivia they're good at. But, what if you don't? What if you realize that you don't know much about them at all? It can feel a little awkward to ask some of these basic questions. The same goes for brands that don't know much about their subscribers.
As a marketer, you need a way to gradually build knowledge about your customers. That's why using email to gather preferences over time is a great way to build stronger relationships and evolve your content strategy. Here are some sample campaigns that do just that.
| Email Description |
Example Message |
What to Include |
|---|---|---|
|
Birthday Request Email Email sent to request a subscriber’s birthday information. |
I want to send you a birthday treat, but I don’t know your birthday. |
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Survey Email Email sent to request specific feedback (regarding an event, an item, etc.) from a subscriber. |
How do you like your birthday gift on a scale from 1 to 5? |
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Progressive Profile Email or a series of emails sent to request specific information from a subscriber. |
I want to find out more information about you, so I’ll ask one additional question that links to our preference center. |
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Preference Call to Action (CTA) Email specifically asking for the subscriber to visit your preference center. |
Are you getting what you want? We have great content to share and we want to learn more about you. |
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So, what do these messages look like in the wild (or your inbox)? Here is an example of a progressive profile email for a recipe site. It offers a clear question that drives a consumer to their preference center, and it provides a clear benefit to the subscriber.
It is important that emails and surveys in a progressive profiling campaign be short, easy to complete, and reward customers for their time.
Confirm What You Know
American psychologist Abraham Maslow not only developed a hierarchy of needs, he also said, “I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.” Meaning it might be appealing to make assumptions based on what info you have already, but it’s not always wise.
For marketers, it is tempting to make certain assumptions based on the data you have collected on a subscriber. And you do have to make some assumptions about your subscribers in order to do your job. So how do you balance what you assume about your subscribers (implicit data) vs. what you know for sure (explicit data)? We’re here to help. First, let’s break down these two types of data.
Implicit data is data that you have about a subscriber that you have inferred, but it is not plainly or directly provided by your subscriber. Imagine you’re a retailer, for example. You have purchase data that shows your customer bought a baby stroller last month. You are about to send an email with a coupon for diapers. But should you? Do you really know they have a baby and need diapers? What if the stroller was a gift for someone else? These are good questions to ask when dealing with implicit data.
Explicit data is the data that your customer told you via a preference center and is clearly stated and spelled out. There is no room for confusion. Again, pretend you’re a retailer with purchase data from a customer who bought a baby stroller. This time, you also have preference data from that customer indicating that they have kids under the age of 2. They might need that diaper coupon after all. Go ahead and send away.
Directly requesting data in an email campaign can help create the best possible experience for a customer. These types of campaigns are called data validation campaigns. Here are two examples of when you might use them.
| Email Description |
Example Message |
What to Include |
|---|---|---|
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Gift Guidance You have purchase data about your customer, but don’t want to assume they made the purchase for themselves. |
We want to provide you correct content suggestions. Were you buying this item for yourself or someone else? |
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Life Change/Opt-Down You have a brand that a customer only needs at certain times in their life, so you want to acknowledge your brand and not send an insensitive email to your customer. |
Maybe something in your life has changed (animal passed away, you moved, and so forth) and you don’t want to hear from us right now. Update your preferences to show what messages you do want. |
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Use Your Data Responsibly
Marketing messages can walk a fine line between helpful and—dare we say—creepy. But don’t let that spook you. To create personalized content that feels spot on, marketers can use purchase history and behavioral data. Just stick to the guidelines we’ve talked about. Here’s a refresher.
- Clearly define your goals for data collection.
- Don’t ask for data if it doesn’t provide value to the subscriber.
- Explain why you’re asking for something. (Customers want to know, “What’s in it for me?”)
- Be open about how you use the data you’re given.
Overall, you can build trust with every interaction by keeping your customer’s data secure and honoring their preferences. Stay tuned—next we transform your data into really awesome content.