8 min read
Published On: 2023-01-31
Email marketing has been a staple of digital marketing for years. With the rise of artificial intelligence, it has become even more powerful. AI email marketing for Ecommerce and DTC brands can help boost email marketing ROI in several ways such as personalizing email content, optimizing email sending times, identifying high-performing subject lines, and more.
Let’s deep dive into how AI in email marketing helps Ecommerce businesses perfect their email marketing strategies. With more successful email campaigns, your advertising cost would reduce, resulting in increased revenues.
Personalizing email content is an integral part of AI email marketing and can help boost email marketing ROI by making the recipient feel more valued. As per Salesforce, 52% of consumers were more likely to open an email if it was personalized to their interests and preferences.
A best practice of using AI-based email marketing for personalizing content is to segment your email list based on customer behavior, demographics, or other relevant information.
The most common example of AI in email marketing is Amazon leveraging AI to collect customer data such as purchase history, browsing behavior, and search history to create personalized product recommendations for each customer. These recommendations are then included in the customer's regular email updates, as well as on their account page.
By using personalized product recommendations, Amazon is able to increase the relevance and effectiveness of its email marketing efforts, leading to higher engagement and conversion rates.
Moda guide: How to increase your Ecommerce email open rates?
Predictive lead scoring is about leveraging machine learning algorithms to analyze customer data and predict which leads are most likely to convert into customers. This can help boost email marketing ROI by allowing businesses to focus their efforts on the most promising leads and tailor their email campaigns accordingly. As per Marketingsherpa, organizations that leverage lead scoring mechanisms get a lift of 77% in ROI over organizations that do not use predictive lead scoring.
Best practices for using predictive lead scoring in AI email marketing:
DTC brand Bombas showcases a great example of predictive lead scoring. They start by collecting data from various sources such as customer demographics, browsing behavior, purchase history, and engagement with marketing campaigns. This data is then fed into machine learning algorithms that analyze the information and predict which leads are most likely to convert into paying customers.
Based on this analysis, Bombas can then prioritize and target its marketing efforts to the leads that are most likely to convert. If the predictive model indicates that a certain group of leads is more likely to convert, the company can choose to allocate more resources toward targeting that group with personalized AI email marketing campaigns. This allows Bombas to be more efficient and effective with its sales process and help the company to increase its conversion rate.
Automated segmentation comprises machine learning algorithms to analyze customer data and automatically segment your email list into different groups based on specific criteria such as demographics, purchase history, browsing behavior, and more. It can help increase the relevance and effectiveness of email campaigns, leading to higher engagement and conversion rates. A study shows that targeted email campaigns have a 34.7% higher open rate and generate 26.5% more orders than no-targeted and generic ones.
Online men’s grooming brand Dollar Shave Club leverages data from its customer's purchase history and browsing behavior to segment its customer base.
One instance of how Dollar Shave Club uses automated segmentation is by dividing its customers into different groups based on their purchase history. For instance, customers who frequently purchase razor blades may be placed in one segment, while customers who frequently purchase skincare products may be placed in another segment.
Once these segments are created, Dollar Shave Club can then use this information to personalize its marketing efforts. For example, the company can send targeted promotions and discounts to customers in the razor blade subscribers segment for products related to razor blades. Or send skincare tips and tutorials to the skincare enthusiasts segment.
Moda guide: 7 Ways automation improves customer experience
Ecommerce businesses are using AI in optimizing subject lines to improve the open rates and click-through rates of their email campaigns. As an initiative of AI email marketing campaigns, they are leveraging machine learning algorithms to analyze customer data and using this information to create more effective and personalized subject lines.
Here are a few best practices for crafting optimized subject lines:
Online eyewear brand Warby Parker is recognized for their intriguing and innovative subject lines. They utilize different types of customer data to personalize the subject lines of their emails.
For example, if a customer has shown interest in a specific product, using AI email automation, the customer receives an offer (in this case a free home trial) for the product.
This not only makes the emails more relevant to the individual customer, but also increases the likelihood that they will open and engage with the email.
Dynamic content entails using customer data to tailor the content of an email in real-time. A study by the Direct Marketing Association (DMA) found that dynamic content can lead to a 760% increase in email revenue.
An integral part of AI email marketing, dynamic content increases the relevance and effectiveness of your Ecommerce email marketing campaigns, leading to higher engagement, conversion rate, engagement, and increased email marketing ROI.
Here are a few best practices for using dynamic content in your DTC AI email marketing:
Online grooming company Birchbox sets a great example of utilizing dynamic content in AI email automation. The brand uses dynamic content to create targeted campaigns for specific segments of customers, like sending an email with a special offer to customers who have not made a purchase in a while.
Send-time optimization determines the best time to send an email to a specific recipient, based on their engagement history and behavior, aiming for higher engagement and conversion rates.
Using AI in email marketing, you can find the best time that gives your emails the highest open rate.
Here are a few best practices for using send-time optimization in email marketing:
Expedia uses data and analytics to determine the best time to send an email to each recipient, based on their engagement history and behavior. For example, they might send an email with a special offer to a customer who frequently travels on Fridays at 3 PM when they have a higher chance of being available and browsing for travel options.
Email triggers and automation can help boost email marketing ROI by increasing the relevance and timeliness of the messages that are sent to subscribers.
A study by Epsilon found that automated emails have a click rate of 119% higher than broadcast emails.
Best practices for implementing email triggers and automation include:
Zalando, an online fashion retailer, implements an abandoned cart email trigger system that sends automated emails to customers who have added items to their cart but have not completed the purchase. The email reminds the customer of the items left in their cart and offers a personalized discount code to encourage them to complete the purchase. This helps to increase conversion rates and overall revenue from email marketing efforts.
Moda Guide: 5 Unmissable automated emails for DTC brands
Predictive personalization uses data and machine learning algorithms to predict the interests and behavior of individual recipients and tailor email content and offers accordingly.
Netflix leverages AI email marketing campaigns like no other. They extensively leverage data on customers' viewing history, ratings, and behavior on the Netflix platform to recommend shows and movies to each individual subscriber. The platform also uses this data to create customized email campaigns promoting content that the subscriber is likely to be interested in.
Moda guide: 6 Ways to boost your email conversion rates
Dynamic email testing, also known as A/B testing, involves sending different versions of an email to a small subset of recipients and comparing the performance of each version. This allows marketers to determine which elements of an email, such as subject line, sender name, or call-to-action, are most effective in driving engagement and conversions.
According to a study by Campaign Monitor, A/B testing can lead to an average increase of 18% in open rates and 25% in click-through rates.
Have a deep understanding of customer cohorts and their respective affinity segments so you can create multiple versions of emails backed by relevant context for better results.
Teleflora, an online flower retailer uses A/B testing to optimize the performance of its promotional emails. They test different subject lines, headlines, images, and calls to action to see which versions drive the highest open and click-through rates. By using dynamic testing, they were able to improve the performance of their email campaigns, resulting in increased conversions and revenue.
Spam filtering refers to the process of identifying and blocking unwanted emails, such as spam, phishing, and fraud. It can boost email marketing ROI by increasing the deliverability of your emails and ensuring that they reach the intended recipients.
According to a study by Return Path, on average, 20% of business emails are blocked or sent to the spam folder. By improving the deliverability of your emails, you can increase the chances of your recipients seeing and engaging with your content, which can ultimately boost your ROI.
Avoid using certain words or phrases that are commonly associated with spam, such as "free," "guaranteed," or "click here."
Add a plain text version of your email in addition to the HTML version to avoid spam filters.
One of the biggest hurdles in AI email marketing is the proliferation of spam messages filling up inboxes. Fortunately, you can get hands-on experience with spam filtering tools such as SpamTitan (TitanHQ) and Hornet Security.
Email summarization is a technique for AI in email marketing where the main points of an email are condensed into a shorter, more concise summary. This can boost email marketing ROI by making it easier for recipients to quickly understand and engage with the content, and can also help reduce the amount of time recipients spend reading and responding to emails.
Best practice to consider while using email writing AI apps:
Tone and language analysis is one of the most crucial parts of AI-based email marketing. AI email automation tools leverage NLP and machine learning algorithms to understand the tone and language of an email and tailor the response accordingly. Several studies indicate that emails with personalized subject lines are more likely to be opened.
Best practices for implementing tone and language analysis include:
Grammarly is one of the best AI email marketing tools for tone and language analysis. It uses AI and NLP technology to analyze the tone and language of an email and the user’s sentiments, and suggest improvements in grammar, spelling, punctuation, and tailors language accordingly.
Real-time analytics and reporting comprise collecting, analyzing, and interpreting data on email marketing campaigns in real-time. It provides marketers with insights into the performance of their campaigns and allows them to make data-driven decisions to boost engagement and conversions.
When you are considering using AI email marketing, implement a scalable and performant data infrastructure, such as a data lake or a data warehouse. Also use real-time data processing technologies, such as stream processing or in-memory databases for the best possible results.
Online grooming DTC brand Glossier uses real-time analytics to track the performance of its email campaigns and make adjustments as needed. Data such as open and click-through rates, conversion rates, and revenue generated from email help optimize campaigns and improve the overall ROI.
AI email marketing becomes more holistic in approach when it can have access to data from multiple platforms. You can enhance the capability of your AI-based email marketing campaigns by integrating with other platforms such as CRM, email tracking tools, and analytics to personalize your email campaigns further.
An important point to remember is that when adding integrations, take into consideration the recipient’s experience.
Online mattresses and bedding products company Casper, in addition to their own DTC website, integrates with other platforms such as Amazon, Walmart, and Target for selling, allowing customers to purchase Casper products through those retailers as well.
Additionally, the company has an API for integration with other sites, like sleep-tracking apps. Having data fetched and tracked through multiple sources, Casper can send AI-based email marketing to customer cohorts and provide them with multiple shopping options to choose from.
AI has been transforming industries with its sheer power and Ecommerce and DTC industry is no exception. By leveraging AI in email marketing campaigns, Ecommerce businesses can greatly enhance their ROI by allowing for more targeted and personalized campaigns, automating repetitive tasks, and optimizing their overall marketing efforts. With the ability to analyze large amounts of data and make predictions, AI email marketing tools and AI email automation platforms can provide DTC brands with valuable insights and data points to improve the effectiveness of their email marketing strategies and drive business growth.