Using Customer Data to Create Relevant E-mail

Let’s face it, the average e-mail inbox is a busy place.

People do not even open scores of commercial e-mails. And even if they do open one, they’re just as likely to erase it or hit the unsubscribe button.

Then there are those precious few that they open and read. What is it that makes these messages stand out from the rest?

One thing. They address the person’s interests in a timely way. They get opened because there is value inside.

Even old-time DMers know that e-mail is the best channel for sending the right offer to the right person at the right time. But it won’t work for you if you blast irrelevant messages.

For example, many e-mail marketers treat their best customers the same way they do a one-time purchaser. But good data will help them differentiate between customers.

You don’t have to know a customer’s blood type. Often, it’s enough to know whether they’re male or female, a first-time buyer or repeat buyer.

The bottom line is that you have to tailor your messages for specific segments.

Segmentation models can range from simple to complex, but it’s better to start with a basic approach and build on it. For example, a follow-up e-mail regarding a sale can be customized for two audiences: those who opened the offer and those who didn’t.

You can remind those who opened the first e-mail that the offer is ending soon. And you can entice non-openers with a “not-to-be-missed!” subject line.

And as you get more savvy, you can use RFM metrics and online behavior to better target your audience. Even the simplest exercises can increase the relevance of your campaigns and lead to additional revenue for your business.

“Dear Valued Customer: the content you are about to read is generic and unlikely to resonate with your specific needs or interests.” Obviously, that’s not the message you want to send, but it is the one your customer receives when an e-mail fails to address them personally.

Using what you know about your customer to personalize content is a simple yet dramatic step towards more relevant e-mail. After all, if you want your customer to be on a first-name basis with your brand, shouldn’t he expect your e-mail program to do the same with him?

From there you should explore the use of profile information and preference center data as a means to target the customer’s needs. For example, you can reference the customer’s last transaction and offer a discount on a complimentary product. If you have a loyalty program you can remind a customer of their current points balance and what her points are worth. Either way, presenting customers with offers that are created “just for them” will enhance the relationship.

Timing is everything in business. When an offer is made at the right time it further drives relevance and increases the likelihood that the customer will take the desired action. But how do you ensure that your timing is on target?

The best way is to implement automated triggers. You can spit out an e-mail to be sent based on a customer’s behavior, from registering for a newsletter to an online purchase to transferring to the next level of a loyalty program. Triggers can also help you awaken customers who have been inactive for an extended period of time.

Another benefit is that the message will reach your customers when they are most receptive.

Above all, you have to understand the lifecycles—of both customers and products. Let’s say your product marketing strategy involves a tryout, you can implement triggers that move customers through the trial period and offer an incentive to buy at the end.

Even something as simple as a transactional e-mail should be considered a valuable contact point in the lifecycle. Take advantage of transactional e-mails as an opportunity to cross-sell and up-sell, or create goodwill around your brand by highlighting valuable customer service.

And remember is this: Relevance is an evolution, not a revolution. It’s best to always start simple and built in a manageable timeframe. Work with your team to prioritize your available relevance tactics: which ones are the most feasible? What will have the most significant impact? What types of data will help us take the next step?

A data audit will help you make some of these decisions and identify what other data types you may want to collect in order to continue segmentation. You should also commit to testing and measuring your results in order to understand what relevance tactics are generating the best return, and where you should focus your next relevance-related program.

Sophisticated Web behavior and click stream data are great. But for building relevant e-mail, the only data you need is right under your nose. Start with the data your e-mail programs generate every day – you’ll be surprised by what you can achieve today.

Millie Park is account director at e-Dialog, an e-mail services provider based in Lexington, MA.