In digital marketing, the continuous optimisation of email campaigns is crucial to achieve the best results. However, traditional A/B testing can be time-consuming and is not always accurate enough to fully understand customer needs. This is where artificial intelligence (AI) comes into play. AI-based testing methods enable automated and more precise analysis of email campaigns and help companies achieve their marketing goals faster and more effectively.
What is AI-based testing in email marketing?
AI-based testing can produce results and predictions that go far beyond what is possible with traditional testing methods. Instead of testing just a handful of variables, such as the subject line or CTA, AI can test & optimise many elements of an email simultaneously. For example, it not only analyses which subject lines are better received, but also how timing, imagery and targeting can be adjusted to achieve the best possible open and click-through rates.
Advantages of AI-based testing
- More precise target group analysis: AI helps to align email campaigns with a granular target group analysis. Using real-time data, AI can recognise which content, sending times and styles are particularly relevant for different segments.
- Optimisation of content components: Rather than just testing the subject line or layout, AI enables testing of numerous components such as CTA wording, images, videos and personalised offers that improve the user experience and increase conversion rates.
- Automated testing: While conventional testing often requires manual evaluations, AI automatically analyses large amounts of data and adjusts campaigns in real time. This means less effort for the marketing team and greater efficiency in campaign planning.
- Predicting results: AI can predict how certain email content will perform with specific customer segments based on historical data. This enables data-driven decision-making that works without long test phases.
Application examples for AI-based testing
- Subject line optimisation: AI can identify which formulations, word lengths and emojis achieve the highest open rates based on user behaviour and optimises the subject lines accordingly.
- Personalised content: Based on recipients’ previous behaviour, such as links clicked or products purchased, AI helps to integrate personalised recommendations and offers directly into the email.
- Send time optimisation: AI can be used to calculate the best send times for individual recipients based on their activity patterns. This increases the likelihood of emails being opened and read
Examples of variable & testable elements in emails
Challenges when using AI in email marketing
As with all technologies, there are challenges when using AI, especially when it comes to implementation and data integration. Companies must ensure that they have sufficient and high-quality data to achieve meaningful results. It is also important to regularly monitor and adapt the AI algorithms to ensure their effectiveness.
Conclusion: AI-based testing strategies as a game changer for email marketing
AI-based testing offers a wide range of opportunities to improve the efficiency and precision of email campaigns. It reduces manual effort, provides more comprehensive analyses and helps to increase the relevance of content for recipients. Companies that optimise their email marketing strategies with AI have the opportunity to better understand their target groups and offer campaigns that sustainably increase conversion and interaction rates.
Checklist: 11 best practices for interactive emails
In our checklist “11 best practices for interactive emails”, we and our partner Mayoris present eleven best practices for interactive emails in email marketing.
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