According to Forrester Research, marketers will blast out a record number of 258 billion emails this year – a 63% jump from just the year before. While many may pound their chests about those rapidly growing email lists, just as many are likely overlooking big opportunities to improve their targeting, relevance, and performance.
Indeed, a recent survey by CEB of over 800 marketers at Fortune 1000 firms showed that over half of those companies are still relying on past experience and gut decision making to create and optimize their campaigns. Only 11 %, meanwhile, are using data to support those decisions. Data, in fact, ranked dead last on their list of available resources.
Stats like those aren’t hugely surprising: After all, email marketing has sustained itself very profitably for a long time on a “batch and blast” mentality. But at 258 billion emails per year and growing, too many consumers are simply feeling blasted – and harder to engage without more targeted, relevant content and messaging.
Little wonder, then, why savvier marketers today are diving deeper into customer data to give their email-marketing campaigns more relevance, more precision in reaching the right people, and better predictability around buying decisions. What kind of impact can data actually bring to bear? Data-driven “triggered” email campaigns, according to Responsys client, Ascena Retail Group, have been shown to achieve the following:
- + 70% increase in unique open rates
- + 55% increase in unique click-through rates
- + 300% increase in dollars per email delivered
- + 225% increase in conversion rate
So what do you do with using customer data to yield numbers like those? As I sketched out in a recent webinar, Give Your Email Programs a Dynamic Boost With Customer Data, tapping customer data in powerful new ways doesn’t require a Ph.D in Big Data – it means identifying the most relevant types of customer data you should be working with, and then creating more personalized campaigns that have a good chance of boosting results.
4 Key Types of Customer Data
In order of importance, here are the four primary data types every email marketer needs to get acquainted with.
- Email Interaction. Basic email interaction data shows where the customer has clicked within the email, open rates, opened links, clicks, customer conversions, and related metrics.
- Web Interaction — Access to a recipients’ web interaction data can help marketers gain an in-depth understanding of how the customer is browsing a website. Abandoned shopping carts and completed applications, for instance, will show what the consumer is in the market for, thus filling the blanks for what kinds of email campaigns will prove most compelling.
- Purchase Data — Past purchase data can be a valuable predictor of a consumer’s next move. By looking at what the subscriber has purchased in the past and what they are using now, email campaigns can be customized to suggest a personalized next step. For example, if the customer just bought a new mobile phone, knowing specific specials for phone cases and screen protectors can help direct the next purchase.
- Profile Preferences — Data from user profiles, such as location, age and gender, may not be as reliable as the users most recent email or web interactions, but is still valuable in baseline targeting.
After identifying what customer data will be the most relevant to your campaign, the next step is to define segments based on the data collected. Consumers in each segment should exhibit similar types of behavior as shown by the data, ensuring that they can be marketed to in similar ways. Triggered emails, for instance – where a specific consumer behavior triggers a corresponding email — can come in a variety of formats, including welcome emails, birthday wishes, and reminders to repurchase favorite products.
A couple words of caution as marketers take a deeper look at data:
First, refreshing and re-evaluating data is a must — it has a limited shelf life. Make sure you’re constantly refreshing (and, if necessary replacing) your customer data, same as you would keep replacing vegetables and produce at the market.
Second, work to set up a simple but comprehensive test platform for email content, to ensure that it’s still resonating with each particular segment and driving revenue.
Are you among the 89% who are still not using data to create and optimize your email marketing campaigns?
If so, why?
What is holding you back from using all the data that has shown to improve targeting, relevance, and performance?