For most of us, it’s not quite that easy. As with big data and content marketing, there is a lot of thought and planning required before you are ready to add AI to your email marketing.
Here are four steps to help you get ready:
1. Make sure your infrastructure is ready. Before thinking about AI, make sure your brand is set up with the foundational technology to support automation. Is your content served from a content management system (CMS)? Are images stored logically in the CMS, and can they be accessed easily? Are results easily accessible by the analytics team and automatically inserted into analytics software?
Chances are, your brand has been pulling these systems together for your Web site. You’ll need to make sure that the systems are also accessible by your email service provider and your marketing partners.
2. Ask for investment budget dollars. Most email marketers have small budgets already allocated to “keep-the-trains running” tactics. AI should be viewed as an investment, and marketers can and should ask their brands for extra investment budget dollars to pursue this technology.
This most likely means putting together some numbers that show potential return on marketing investment (ROMI), and then tracking results of the tests. The good news is, many brands look for investment opportunities like AI, so they’re likely to have interest in investing in AI for email marketing.
3. Start with machine-learning tools. There are a number of machine-learning tools out there (similar to AI but not nearly as complex or autonomous). It’s a great idea to start with these existing and proven tools before moving on to bigger and more expensive AI tests. Send-time optimization, and next-logical-product emails that rely on business logic and rules, are great examples of machine learning tools that can guide your next steps. Once your team has experience with these tools, it is easier to make the leap to bigger AI opportunities.
4. Run small tests first. Set the stage for larger tests by picking smaller ones to start with. Once you have success with a smaller test, it will be easier to build the case to get investment dollars for the larger ones.
Make sure you pick small tests that will give you the greatest possible lift over your control. For example, if you already have a lot of experience with a machine learning tool running your cart abandonment program, you may want to pick a different area to test first. Your goal is to compare AI to business as usual, not to compare AI to already augmented processes. A good small test might be subject line optimization.
Once you’ve demonstrated success adding AI to your email marketing in small areas, it’s time to broaden the scope. By starting small and growing from there, you’ll have a solid foundation of results on which to base your marketing and your investment budget requests. Before you know it, you’ll be ready to add AI to your email marketing everywhere.