Marketers strive to personalize emails in the quest for relevance. This is not new to seasoned marketers who have been using marketing automation platforms to create customer journeys or leveraging segmentation and/or personas. This is a good usage of data and tools, but it simply can’t scale beyond a certain point. In our experience, most clients have around 20-25 data segments.
For relatively large user bases, too many journeys and segmentation could potentially ruin the user experience and complex rules make it hard to maintain. The genius of ML and AI can save the day! AI power, combined with human intellect (IQ), is going to create a hyper-personalized experience to the user which will compel them to remain engaged with the brand.
The marketing side of the email industry was relatively slow to embrace machine learning and AI. Even today, a lot of companies want to leverage the hype of AI and ML, but a marketer needs to understand “How is this new technique improving my customer experience and ROI?” If the answer is not conclusive or results are not visibly different, then the solution is just hype with no value addition.
Implement Data Segmentation in your Email Marketing
Understanding their user base is a fundamental need for a marketer. Each marketer should know as much as they can about their customers. To that end, usually, marketers segment the users based on demographics (age, location, etc.), marketing segments that they may have created in the past based on purchase behavior, or email behavior like email activity (opens, clicks, etc.).
Traditional approaches are usually based on experience and limited data points. This is why marketers need to upgrade their data segmentation techniques based on newer and more AI-friendly methods.
Once marketers have a good understanding of these segmentation techniques, they will be equipped to leverage the power of AI to get the right content to the right user, at the right time and on the right channel.
Send time optimization is not new to email marketers. Many of them are doing it in at least one way - based on the time zone of the user, or the best time to generate responses. There is no point delivering email at midnight for users in Cleveland and the same message sent to users at 8:00 am in Dubai, in a single send with the same message.
If a brand has users from multiple time zones, the delivery times must be optimized per time zone, allowing the marketer to adjust their content accordingly. Not only send-time optimization but email delivery optimization is as important for boosting your email engagement rates.
Delivery optimization is usually invisible to the marketer, but if the email service provider (ESP) is using some advanced machine learning and AI techniques to optimize delivery for better inboxing and reputation building, this should provide significant stability in overall reputation and a jump in ROI of email campaigns.
Email Delivery Optimization for better engagement
Optimization of Campaigns using Real-Time Analytics
Traditional reporting of campaigns was limited to opens, clicks and a few other basic stats. While basic metrics are still needed, tracking metrics have evolved from numbers on charts to data that can be used to get insights and make recommendations to achieve the intended goal.
Real-time analytics in your email campaign can help you not only monitor the performance of your emails but are also a very effective tool for drawing insights for your future campaigns. They help collect actionable insights that are very specific to your company and your brand.
Power up these insights with AI, and you will be well on your way to get superb campaign performance.
Key takeaways
A Summarized view
The industry has been using words like “Right time, right message, right channel” for many years. Before the Internet, with fewer options, data and predictive analytics could do a fairly good job of finding the right targets to market to, and then the message convinced that user they needed something. Fast forward to now, when users have so many options and new behaviors that were never a consideration before.
Research that used to happen at the dinner table or water cooler at work is now a major step in the journey process. Consideration with review sites, comparison sites, all getting closer to decisions. Search and digital advertising’s role in all of this and the signals that occur each step in the process that users take.
The customer journey is complex. The good news is that AI and ML can help marketers move to the next level of marketing. They will still be the brains behind the plan; this is the technology that is fed by inputs from marketers. But they will have the tools that will give us the ability to transform their marketing by providing truly one-to-one experiences, in a new Segment of ONE world.
Download the whitepaper to amplify your view of email marketing above and beyond the usual tactics used by marketers.
About the author
This whitepaper on artificial intelligence in email marketing was written by our experts Chaitanya Chinta, Head of Deliverability at Pepipost, he has a 10-year experience in email deliverability and having written a few spam filters himself, he has an in-depth knowledge of working os Spam filters and email deliverability and Jeannette Kocsis, SVP of Marketing and Business Development, Pepipost US. She has extensive working knowledge of the working of businesses and their requirements. Along with great knowledge and experience in getting the best possible ROI from emails.
Being experts in their respective fields, they have explained how and where AI works best in Email Marketing and how you can best benefit from implementing these in your Email Marketing campaigns. This whitepaper explores in-depth, the working of these algorithms and their best use cases.
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