How to Make AI-Driven Emails Compelling Without Being Creepy

How to Make AI-Driven Emails Compelling Without Being Creepy

Hitting the right balance Prospects and customers are more than data points on a spreadsheet. Look at the audience critically to ensure you don’t flex an AI strategy that might cross the line for some readers. How would employees prefer their information to be used? These insights build and begin to inform future experiments, leading to better-informed strategies around which data to use as well as how and when to use it. Here are three steps you can take to use AI for your emails in a way that benefits your company and your customers alike. According to an Evergage study, 98 percent of marketers agree that when implemented correctly, personalization helps customer relationships grow stronger, and nearly 88 percent report that their customers expect this type of customized experience. Test and measure everything. Every aspect of a good email message should be tested and tracked. If all goes well, effective content patterns will emerge. Brands clearly have work to do, so listen to consumers when they give both positive and negative feedback.

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Most customers are wary about AI, so don’t make it extra weird by incorrectly using your data on them.

How to Make AI-Driven Emails Compelling Without Being Creepy

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AI is becoming more prevalent across digital aspects of business, but not every customer is thrilled with the new technology. In its fourth annual “Creepy or Cool” survey, RichRelevance found that only 32 percent of respondents felt OK about AI. The vast majority, 81 percent, believe organizations have an obligation to tell customers when and how AI is being put to use.

That means any company hoping to benefit from AI’s capabilities and retain customers needs to be transparent about the technology fueling its platforms. But companies shouldn’t fear AI. The biggest opportunity most organizations have is prioritizing their data to find the right balance of customization.

There’s a sweet spot between overgeneralization and overpersonalization: It’s somewhere between blasting out 10,000 copies of the same email to 100 different targets and attaching a picture of the prospect’s house in an email. Companies have loads of data on their customers, and that will only increase. However, when that customer information is used incorrectly, it can be off-putting or downright unnerving.

Hitting the right balance

Prospects and customers are more than data points on a spreadsheet. It’s exciting to have rows of helpful information that can help engage people, but like a first date when one person has clearly Facebook-stalked too much, it can be overwhelming. Look at the audience critically to ensure you don’t flex an AI strategy that might cross the line for some readers.

The whole team should discuss what level of detail will be comfortable for readers. How would employees prefer their information to be used? What’s impressive to see in a targeted email? And which data points, when used, feel like they cross the line?

Just as with any other process, form a hypothesis and test it; isolate variables and qualify the responses received. Which audience members responded favorably? Which buyer persona do they most resemble? Are there any patterns within those buyer personas? These insights build and begin to inform future experiments, leading to better-informed strategies around which data to use as well as how and when to use it.

It might sound complicated, but there are a few ways to ensure that the process achieves the right balance. Here are three steps you can take to use AI for your emails in a way that benefits your company and…

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