Personalization – the science of creating highly relevant emails that are as close to one-to-one messages as you can get at scale – is an email marketer’s goal and the toughest challenge.
Personalization is the most effective email tactic for 62% of email marketers who participated in a recent survey by Ascend2. But, 47% of them also said it was the most difficult one to pull off, thanks in part to the trend toward hyper-personalization from higher-order data integrations like artificial intelligence.
I’ve seen this in my work with clients as well. Many struggle with personalization and segmentation, and it’s not just lack of data or the capability to integrate it in their email platforms.
They just don’t know where to start.
They have an abundance of data everywhere and no clear starting point either for upgrading a personalization program or starting a new one.
Here’s my best advice: Begin this by inventorying the data you have, identifying what you need to proceed, building partnerships with your IT or database teams, testing your assumptions and then using what you have learned to make a case for greater investment in your email program.
I’ll take you through these steps one by one below.
1. Start with an inventory
You can’t work with data if you don’t know what you have or what quality it is. So, that’s the best place to begin.
Take inventory of what’s already working in personalization. Then, inventory the data you have available, whether it’s onsite, held in a different database within your company, housed at your email service provider (ESP) or available from another source.
This is an important first step because you need to understand the barriers that are keeping you from having access to that data regularly. If you don’t have a robust pool of first-party data – the data you collect yourself based on your customers’ behavior – you can always see what data you have available through your ESP. This data will show you what your customers are doing with your email.
That’s one of the great benefits of email. We have more insight into the channel than we get with social media, search or SMS.
Finally, inventory your baseline emails (your broadcast emails) and trigger emails to learn how many attributes you’re using per message. The numbers will be different because your triggered emails are based on user actions, and they will reflect more data than your baseline campaigns.
2. Identify the data you need and opportunities to use it
Identifying your available data and what you need can help you discover opportunities to use it for better results. Once you identify your opportunities, rank them on the expected impact each one will have on your email and how much effort you’ll need to make it happen. That gives you a prioritized list with the rhymes and reasons you need to build your case.
Look for areas where you can add more data to your baseline campaigns. Let’s say you manage email campaigns for a pet-care company. Consider how you could use geographic region. Dogs in urban environments will have different needs compared with suburban or country dogs.
If you can identify your customers by ZIP code, you can use that one data point to create three pieces of dynamic content that you can add to your baseline email.
3. Build partnerships and prioritize your requests
It can be harder to understand how to use your data if you can’t integrate it. Also, other departments in your company might have first-party data on your customers, but you might not be able to tap into it for your emails.
Instead of just asking your business intelligence team for access, explain how you want to use it. Better yet, partner with your BI group on a data project.
When you’re in your inventory stage, you might find data points imported into your program that you’re not using. They use up your resource space but give you no value. Approach your IT or database team and offer to exchange the data you’re not using for something that would be more valuable for your email marketing program.
Another issue to get a handle on is how to prioritize which of your available data is more important.
New automations will require developer time. So, you need to make a strong case that your request will be worth the time it takes to set up your automation. People will be more likely to listen if you can say it will lead to incremental revenue increase than if you try it to sell it as a new and cool thing.
4. Test your assumptions
Your next step is testing your assumptions. Mock up emails with the data as they would look in real time and test with active subscribers to see if your automations resonate.
If you see a measurable lift in results, you have ammunition to go to your executive team to say “We have this data point.”
You will have to show the value of your automations immediately. If the value doesn’t show up in 2 seconds, it’s a loss. It’s how you make sure you’re continually auditing your data sources to make sure they’re working.
5. Use what you learn
Once you have the results from your tests, you can use them to make a case for added investment, whether to add or expand automations, acquire more data or whatever you need to drive better results for your email program.
Use this information to prioritize your requests. They should be in line with what you are trying to accomplish with your email program.
Data is the fuel that drives your personalization efforts and helps send more relevant emails to your customers. These emails show how well you understand customers as individuals, with content that reflects their preferences and behavior.
Your investment now will pay dividends all through your email program.