How To Successfully Use Data For Your Email Marketing

7 Min Read

Analyzing data gathered across multiple channels provides marketers with valuable insights into audience preferences and behavior. This can lead to more focused, effective campaigns, which is why US marketers have invested around $5 billion into data management in the past couple of years.

And email remains a crucial marketing channel, with almost 70 percent of businesses putting money into it as they aim to grow, retain, and engage their audience.

Combining data and email has the power to create a powerful marketing strategy, but marketers must use the information they gather properly to achieve the best results.

How can you do this?

Define the Most Important Data

First and foremost, marketers should determine which metrics they’re going to focus on to improve their email marketing campaign.

The best email marketing software offers marketing teams access to a wealth of data, but scouring it all for actionable insights can be daunting. Especially for smaller, less-experienced marketers.

For email campaigns, marketers should focus on open rates, click-through rates, unsubscribe rates, bounce rates (to see how many emails fail to reach their address), list growth rates, spam complaints, new subscribers, mobile open rate, and ROI (based on the number of sales generated by a campaign minus the money spent on it).

You need a reliable email marketing automation platform and other tools to make the most of your campaigns.

These metrics offer a practical insight into the level of engagement and impact marketing emails make. Comparing data over set periods reveals the effectiveness of any changes implemented into the campaign and identifies opportunities to improve.

Trying to focus on too many metrics can spread marketing teams too thin, though, which is why it’s so important to pick only those which provide actionable information.

Use Benchmarks for Accurate, Consistent Measurement

Once you’ve identified the most effective metrics, you need to establish benchmarks. These represent the averages achieved through email marketing to date, such as the average number of opens across a six-month period. It’s helpful to gather data on industry averages, too, for a deeper insight. Compare these to measure how well the business’s email marketing is competing with others so far.

Establishing benchmarks enables marketers to determine how email marketing performance improves or drops over time. For example, open rates may increase while more subscribers choose to sign off.

In this case, it’s clear that subject lines are doing their job, but the content of the emails could be the problem. This would lead the way for a more in-depth analysis, such as comparing low- and high-performing emails for differences in visuals, tone, offers, etc

Understand and Segment Your Audience

Sending prospective or existing customers’ emails which are of no interest to them is a surefire way to see your subscriber list shrink. And it’s a common issue, with more than half of consumers receiving too many emails of little or no relevance to them.

Recognizing the different demographics within an audience is key for boosting the relevance and increasing an email’s power to engage recipients. Analyzing data helps marketers break their audience down into important segments, based on:

Location

Using geographic data collected at the point of registration allows marketers to send emails with information on relevant deals or events within the recipient’s area.

For example, a retail company might run a weekend sale in specific stores only. Notifying subscribers who live outside of range is a waste of everyone’s time, so focus on locals instead.

Purchase habits

Importing data from an e-commerce platform enables marketers to explore subscribers’ purchase habits, such as buying frequency, amount spent, order value average, and products purchased.

Studying this data, marketers can see which customers are worth the most and least to a brand, what their buying interests are, and when they’re likely to be looking to buy a specific product again.

Behavior

Behavioral data examples include cart abandonment, pages browsed, products added to cart, email clicks or opens, and form abandonment.

Understanding which pages and products customers spend most of their session time exploring makes it easier to segment them by interest. Meanwhile, cart abandonment data allows marketers to set up automatic email responses to be sent whenever a customer takes this action.

These are designed to keep them engaged and incentivize them to complete the transaction, using a discount or free shipping. If the data shows a high number of abandoned carts, it indicates a problem with specific products, prices, or website functions.

Personalize Emails for Higher Engagement

Personalization can be as simple as including the recipient’s name in the subject line, which is proven to make an email 26 percent more likely to be opened. And 90 percent of American consumers find personalized marketing content “very” or “somewhat” appealing.

But personalization can run deeper. For example, personalization is well-suited to a welcome email. Greet the recipient by name in the subject line and tailor the content to their interests to make more of a positive first impression.

Beyond this, marketers can target customers they know to have children with family-focused visuals and information that’s more relevant to parents than non-parents.

You might use data to send personalized emails on customers’ birthdays, too, including exclusive deals based on their age, purchase habits, location, etc. Birthday emails actually generate up to 342 percent higher revenue per email than standard marketing messages.

Data-driven email marketing takes time and close analysis, but it puts marketers in a better position to target customers more effectively.

Gather data from across email, social media, and interactions to learn about different demographics. This will help to make each email count, boost their relevance to customers, and reduce their risk of going unnoticed in cluttered inboxes.

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