Marketers know they need to use data to get better results for their email programs, whether that means keeping subscribers around longer, persuading more of them to open and act on messages or increasing the revenue earned from email.
Still, study after study shows marketers are still stuck on the ground floor of the data building. Maybe we’re too focused on implementing some world-changing email program, when all we really need is a smaller, more focused and long-term approach.
Data’s still a challenge for many marketers
Two studies point out that data continues to be a hurdle for marketers:
Data integration is the No. 1 challenge for email personalization. Econsultancy’s Email Marketing Industry Census 2017, published with Adestra (my employer), found 55 percent of marketers said this is one of their main challenges, along with “lack of resources” (41 percent) and “finding time to make it happen” (33 percent).
The Relevancy Group found that more than 50 percent of email marketers don’t use data to segment their email databases. That means their email success still rides on sending the same message to everybody in the database regardless of click or conversion data.
On the plus side, this last finding means that nearly half of all marketers DO use data successfully and likely see better email metrics and revenue results. How can we help everybody else get there?
The answer: Incremental innovation
Many marketers are eager to innovate but have too little time or money to support stepping away from the daily grind. It’s not that they don’t care; they’re just too busy trying to get the next campaign out the door.
It’s also hard to know where to start if you don’t know what to fix first. Here’s my solution: Instead of trying to launch a full-blown program, which could take more than a year, take it one step at a time. You’re innovating, but in increments instead of one big leap.
Start with just one change
This week, find something you could change in your next campaign — something you could test, a new call to action, or anything that doesn’t need a major upheaval. Make the change, and measure your results.
The next week, change another thing and add it to your list. The week after that, add another change to the two you’ve implemented already.
Build on your incremental innovations every week if you can. Before too long, you’ll look up and see how far you’ve come.
That’s the power of incremental innovation.
A place to start: ‘Next logical product’ trigger
Triggered and transactional emails can bring in a significant portion of your email revenue in a year. One of my favorites is the “next logical product” trigger, and it’s a good way to begin innovating in increments.
“Next logical product” emails tie customer intent to your data to generate another purchase. You can predict this behavior because your statistics show a significant majority of people buy that product next. That’s your “next logical product” trigger.
‘Next logical product’ data in action
Suppose you know that customers who buy washer-dryer combinations on your website often buy storage platforms — the things those big machines stand on with drawers to store detergent and other necessities — within two weeks after purchase. Naturally, you want them to buy that piece of equipment from you instead of the big box store across town. But how?
You say, “Hey! Let’s message everybody who doesn’t buy a storage platform from us 10 days later. Let’s show the exact washer/dryer they bought AND the storage platform that fits that model. And let’s make it easy to order it!”
How to identify ‘next logical product’ triggers
First, study your product and purchase data so you can understand purchasing patterns. What do people buy? What do they buy after that? What’s the time frame? Identify five products that you could investigate for possible next-logical-product triggers.
Next, give your data scientists or CRM analysts your product list. Ask, “For these products, what do people buy next shortly after the purchase, and what percentage of customers buy those products?”
Use your data to create a financial model, and then test it on a sample of consumers. If you can verify your hypothesis, create a simple email featuring the upsell for the product purchased.
Test several versions of the copy, going at it from different angles:
A transactional approach (“We noticed you didn’t buy this essential product to go with your recent purchase. Do you still need it?”)
A helpful/customer-relationship approach (“A lot of our customers found this product which helped them get more use out of their purchase.”)
Then, link directly to the product page in the email.
After you create and test your emails, isolate the customers who bought the original item in your time frame. Send the next-product trigger email manually, and assess the response. Try another date range, too. This will help you figure out the best time after the original purchase to send the follow-up email.
This trigger brings you two advantages:
You created a new revenue stream.
These consumers may have come back on their own to buy the next product, or they may have gone to a rival. Your “next logical product” email increases the chances that you’ll get that sale.
You created a new proof point you can take back to your data people.
Using the results you generated in your tests, you have a new proof point you can give to your systems people when it’s time to automate the process.
What are you going to try?
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