AI will be able to generate $14 trillion more revenue and 38% more profit by 2035. Businesses have been able to enhance customer service by using AI email marketing to provide relevant, data-driven insights. Small businesses should take advantage of the AI revolution.
With the help of three Ds, AI can automatically solve problems.
- Detect – This step is where AI finds the most predictive attributes. It then helps you to identify the elements that you should pay attention to and those you can get rid of.
- AI is deliberate – AI compares predictive attributes to each other to provide personalized recommendations and answer questions.
- Develop – Machine Learning, a subfield within Artificial Intelligence, allows it to program and reprogram itself. It can then modify or evaluate the data based on the results of experiments. AI’s beauty is its ability to mature with each iteration.
AI can be integrated into every stage of email marketing. Let’s find out how.
AI-powered A/B testing
Email marketing content creation can be difficult at times. A/B testing is necessary to determine which type of content performs best. When optimizing emails that convert and deliver results, A/B testing can be very helpful.
However, it can be time-consuming and leave you open to errors if done manually. AI developers have created an easy way for marketers to create email marketing content that is highly effective and result-providing.
According to custom papers, this task has been automated entirely with this integration, and it’s among the most impactful revolutions of email marketing.
This system is used by many marketing professionals to make sure they send relevant content that is likely to be opened. This system tests CTAs, themes, and copies. It also checks for other important aspects of an email.
Select the Right Days to Send Your Mails
Email campaigns are often a series of emails that build on each other. It is important to start your campaign on a day that will generate higher response rates than other days. Your first email should not be sent on the weekend or when nobody’s looking. Follow-up emails won’t strike a chord.
AI has the sweet benefit of being able to analyze a lot of data and identify trends. AI can help you determine the best days to launch your campaigns.
According to Exceed, an AI marketing platform, the best days to send an email with a greater likelihood of response are Tuesday and Wednesday. This day is 7% more likely for an email to be answered.
Weekends, particularly Sundays, have the lowest response rates. Sunday response rates can drop to as low as 4.9%. Mondays are in the middle with a 5.9% response ratio due to inboxes overflowing over the weekend.
Fridays also have an astonishingly high response rate, at 6.2%
Thursdays have the lowest response rate of any weekday, at 5.2%. These lessons are obvious: Email your messages on Tuesday or Wednesday after the weekend backlog is cleared. This will allow people to read your emails.
Follow up at the right time
Follow-up is something that every email marketer fears. How do you know when to follow up so that your prospect responds positively? You don’t give your prospect time to read your email if you follow up too quickly.
If you don’t follow up, you could be forgotten. AI can help you find the sweet spot between being able to accommodate your prospect’s hectic schedule and being forgotten. According to the study, the best time to send the first follow-up email is between 3 and 4 days.
It all depends on the type of prospects you are pursuing. Some industries prefer to wait longer, while others prefer faster follow-ups. Your AI will ultimately help you determine the optimal time by crunching your data.
Exceed’s research has shown that after the first follow-up, your chances of getting a reply drop dramatically after 8 days. Response rates fall below 2%. You can expect a “good-enough” 2.1% response rate if you follow up within one week. A 5-day follow-up period will yield rates of 2.5%.
It’s vital to remember that when you follow up, it also affects the likelihood of receiving a reply. These numbers are valid even for a second follow-up email. Curiously, these emails have a drop in response rates between 6 and 17 days. However, the response rates increase to 1.7% after this time.
You don’t have to wait for two weeks to follow up. Follow up within 2 to 4-days of the last email.
Make sure you have the perfect number of follow-ups
The majority of marketing teams feel panic about increasing their unsubscribe numbers by delivering emails more than normal. They give up after only 1 or 2 follow-ups. Exceed data shows that 10 follow-ups are the correct number.
Although it seems absurdly high, it is actually true. It’s possible for someone who has been ignored 9 times to reply to your emails if you combine this with the previous points about email spacing and sending them on the right days of the week.
It all depends on the individual data you have collected over time. AI-powered analytics can also help you determine the right number of follow-ups.
AI in email personalization
AI can be used for multiple purposes. Your email marketing strategy will determine which AI personalization technique is most effective.
Email marketers can utilize the 3 P’s key AI techniques, which are:
- Profile-based personalization
- Product-based personalization
- Predictive Analytics
Personalization of emails using AI based on your profile
This is a great way to send newsletters or other campaigns to large audiences.
Online recommendation systems are becoming more detailed and in-depth. Spotify and Netflix have refined their recommendation engines to create more meaningful engagement with their customers through hyper-personalization.
Spotify, for example, provides personalized and tailored recommendations to each listener. While automated recommendations are not new, Spotify’s complex algorithm doesn’t just use a user’s saved tracks; it creates a profile of each user’s musical preferences.
Consumer expectations have been raised by these entertainment brands. Retailers must now provide curated content to each customer – not just based upon a user’s previous clicks or purchases but also based on their shopping preferences.
Personalization via email newsletter is especially well-suited for profiling
- The results are often highly relevant. Profile-based AI is based on each consumer’s taste profile. This means that they will be highly relevant to the consumer’s interests. Profil-based AI email address
is especially useful for organizations with many products and many consumers (think retailers and e-commerce)
- Encourage product discovery. This technique has another advantage: email marketers can use shoppers’ taste profiles to encourage shopping and browsing – even if the shopper does not have a clear need. Email marketers can maximize product discovery and revenue by constantly displaying relevant and fresh content.
- Marketers can get started quickly. Profile-based personalization avoids the cold start problem that plagues product-to-product recommendations technologies.
Although the technology requires initial data in order to make recommendations, it is more likely that the quality of these early recommendations will be better than a platform that becomes statistically valid only after millions of data points are correlated.
Recommender systems have the impact of guiding shoppers in a personalized way to interesting products in a large space of potential product recommendations.
Profil-based AI systems suggest products based upon the attributes of products that a given shopper likes in the past. To recommend new and exciting items, a profile-based recommender combines the attributes of each shopper with those of the products.
Profile-based personalization is often the best option for email newsletters. This creates a detailed picture of each customer’s preferences so that the marketer can tailor email content to each subscriber’s needs.
AI to personalize emails based on products
This is a great way to send purchase confirmations or other behavioral messages.
Product-based AI emails rely on the relationship between products and consumers. All that is required to create a correlation among all your products.
Product-based AI email assistants can be used in marketing to cross-sell products and trigger behavioral campaigns, such as purchase confirmation triggers. Users can be shown matching products or additional products. This type of AI personalization is a market leader for Amazon.
Amazon realized early on that customers will buy more stuff if they are given the right product recommendations.
Amazon allows you to see up to five types of product-based AI personalization during the Amazon purchase process
- “Frequently purchased together.”
- “Your featured recommendations and most recently viewed items.”
- What do customers purchase after seeing this item?
- “Customers who viewed the item also viewed.”
- “Customers who purchased this item also bought it.”
This is great for motivating people to take action. Preventing churn
Predictive analytics is a combination of historical data, statistical models, and AI. It helps to determine which marketing strategies are most likely to succeed. Predictive analytics can include automatic winner selection and the next best action.
It sounds great! But how can predictive analytics improve your marketing strategy?
Predictive analytics helps you to understand your data better and make informed decisions. AI-aided predictive techniques help predict customer behavior by identifying patterns in your data.
Regression analysis, for example, identifies any relationship between previous shopping behaviors and future buying behavior to determine the likelihood of future purchases.
Predictive analytics can be used to identify unhappy customers who are more likely to churn and to recognize buyers with the most chances to buy. Predictive analysis of customer data can help you to plan your marketing strategy and predict behavior.
It is easy to begin integrating AI in email marketing
It’s easy to implement AI in your email marketing system. There’s no requirement for any data science knowledge. There are new AI-based software platforms that can be used by businesses, even if they lack machine learning maturity.
It is a good idea to start with a Proof of Concept (POC) because AI is still a relatively new field. A Proof of Concept (POC) is used to show that AI can deliver on your marketing goals.
POC is a pilot program that allows vendors to test their technology in an operational environment. This takes place for a set time period. This is a pilot program to test the AI Email Assistant using your data and then use it on an operational basis.
You should start by creating a list of potential POCs that are in line with your marketing KPIs.
Whenever you find yourself rich with numerous options, rank them according to business impact, weighted if compulsory, for ease of implementation. Next, pick the best POC and save the rest for future implementation. To build confidence and momentum, it is important to have early successes.
Make sure you choose an AI vendor, not just a rules-based platform. This is difficult to scale for the amount of data and interactions marketers manage today. You should also ensure that the vendor you choose understands your industry and can integrate with existing technology partners.