Your customers expect you to be proactive and serve them with inspiration and product suggestions. Eliminate all obstacles and inspire them to their next purchase. The newsletter must be aligned with customer preferences, and you must do your utmost to catch their attention.
Use A/B testing for optimized results. Before entering the world of test strategies, let’s have a look at what a good newsletter structure and content is. It’s not just what's on the outside—but it's the inside that counts.
Here's how to avoid that, with a newsletter your contacts will want to receive:
- Start with a strong subject line. The newsletter should be opened by as many recipients as possible. Customers that haven't opened your messages for a while are more likely to churn.
- Add an interesting pre-header. After reading the subject line, your customers should be even more compelled to open the email when they read the pre-header, so it should not be left as "View this email in browser..."
- Filter your email and be relevant for every contact. Strive towards a one-on-one dialogue rather than using the same modules for everyone. Use available data such as demography, online and offline behavior, purchases and interests to decide what each segment of your audience should see.
- Use distinct call-to-actions. What will make the customer click-through from your email to your website?
- Test, test, test! Use A/B or multitests and and turn insights to actions.
What is the ultimate email like?
Unfortunately, there's no one formula that'll work for everyone. Since your offering and target audiences aren't fully comparable to other lines of businesses, there aren't any generic benchmarks:
- What is a good/acceptable open rate?
- How can we use content to optimize open rates and/or click-through rates?
- What kind of promotions work?
- What time of day should we send emails?
- Which channel shall we use for different messages?
- What impact does a reminder have?
You need to carry out tests for understanding your marketing potential. Being data driven and understanding customer preferences must not only include AI, machine learning and smart algorithms. You can make a big difference by just being curious, structured and by testing your hypotheses.