Artificial Intelligence in Marketing

Artificial Intelligence in Marketing

How do e-commerce businesses know what I need before I know what I need?  

The answer is that marketers are beginning to use powerful, new AI marketing technology. Artificial intelligence (AI) use in marketing is beginning to make automated decisions - and then taking action - based on collected data, predictive analysis and machine learning. With this new technology, we are seeing AI being used today to successfully guide and influence buying behavior. 

Artificial intelligence is collecting consumer behavior data and using that data to improve marketing and communications activity and effectiveness over time. AI uses data to make decisions, and take action, based on what has or has not worked in the past. While email marketing has been around for many years, AI is improving how it can be used, especially in e-commerce shopping situations. 

Successful Businesses Rely on Repeat Customers 

Creating lasting relationships with customers can be vital to the success of a business. AI can now assist in sending personalized emails to the right person at the right time with the right messages. AI can also help identify and win back “at risk” customers, perhaps offering a special incentive to encourage a repeat purchase. 

Let’s put the importance of “happy customers” in perspective. Research shows:  

  • That 80% of future profits will come from 20% of existing customers 

  • We also know that 90% of consumers want to stick with familiar companies 

  • And it costs five times less to encourage them to buy again versus attracting a new customer 

We also know that: 

  • Improving customer retention by 5% boosts profits by an average of 75% 

  • And that's because loyal customers spend up to 300% more than first-time buyers 

Source: and RJMetrics 

New AI email marketing technology can personalize everything from subject lines, email content, delivery time, email frequency and promotional offers. AI can be a significant bridge between your business and additional sales since loyal customers spend up to 300% more than first-time buyers.   

In Addition to Existing Customers, AI Can Target Other Types of Customers 

Beyond existing customers, businesses are beginning to use AI in marketing to focus on additional types of customers, including:  

  • Type or category of product(s) purchased   

  • Repeat customers  

  • New customers  

  • Recent purchases  

  • Most engaged  

  • Least engaged 

Rather than sending out mass emails to large groups of customers and hoping we generate some interest, why not send emails to each individual customer based on their unique interests, activity and recent purchases? 

AI technology is now to the point where it is capable of managing this type of communications. Let’s instead send personalized messages when they are most likely to be seen and read. Let’s allow customers to follow their own personalized journey based on their behaviors providing them personalized recommendations. 

Wouldn’t that be better? Perhaps that model would look something like this below? 

How Would A System Acting on Personalized Recommendations Impact Your Business? 

With AI-based e-commerce, a business would be able to: 

  • Send messages that feature the most relevant products for each individual customer based on their unique shopping behavior. 

  • Use predicted preferences to personalize content. 

  • Increase average order value. 

This will help your business: 

  • Maximize email/on-site key performance indicators.  

  • Enhance discovery of the best products for various cohorts of your customer base. 

  • Engage customers by keeping emails interesting. 

Finally, AI can predict and take action on: 

  • Best email subject lines for each individual customer. 

  • Highest performing email messages for a particular goal/outcome. 

  • Offering an incentive or special offer at just the right moment.  

  • Identify best time to send emails. 

AI is very different from typical trigger automation, as the A.I. engine seeks to optimize each individual interaction. For example, if a user gets a price discount message, it would be based on predictive product recommendations, and not just simply something a customer has viewed before.  

Specific Situations Where AI Influences Behavior 

AI isn’t just responding to some particular action or trigger. AI is designed to react to each unique user when they exhibit a specific behavior within the context of all their past behavior. 

Here are some additional specific examples that AI can determine and act upon: 

  • Cart Abandon: Capture users who leave products in their shopping cart without purchasing. 

  • Follow up: An important engagement message sent at a specified time after a customer makes a purchase. This is a good opportunity to send additional product information, collect feedback, or entice a repeat purchase. 

  • Browse Abandon: Similar to cart abandon, but this captures when a user views a product on your site or mobile app and does not go through with a purchase. 

  • Search Abandon: This is when a user searches for something on website/app (via a search box) but doesn't find what they are looking for. AI can recommend items similar to what was searched for. 

  • Birthday: AI will automatically pass on your birthday greetings. 

  • Anniversary: A message is sent annually on your customers’ signup date. Another great opportunity to engage users and converts well like a birthday message. 

  • Price Drop: Based on predictive product affinity models, AI can identify when price drops will be interesting to your customers and send them email notifications. 

  • Back in Stock: Based on predictive product affinity models, AI looks for items that come back in stock that AI predicts your customers are interested in and will create and send them an email. 

  • Buy Again: AI can find items in inventory which are frequently repeat purchased and will trigger messages to purchasers to remind them to buy again. The trigger can send based on predicted re-purchase time for that user. 

  • New Arrivals: Based on predictive product affinity models, AI can look for items new to your inventory that customers are interested in and create and send emails. 

As you can see, Artificial Intelligence is now a reality and is today helping e-commerce businesses connect with customers and increase sales. 

We’d love to discuss e-commerce marketing and how Artificial Intelligence in e-commerce can play a role in your business. Just contact us or book a meeting online

Screen Shot 2021-07-02 at 12.20.03 PM.png


Additional Resources

Have Questions? Contact Endorphin® Digital