6 Ways to Use AI Now to Improve Your Marketing Results

I don’t know about you but I’m overwhelmed by all of the talk about Artificial Intelligence (AI) and what it could or will do in the future. Much of the conversation seems focused on whether AI will be good or bad for humanity and how it needs regulation to not take over the world. Fear not, we don’t see AI replacing us humans as marketers but rather, it should help us do our jobs better. Think of the saying, “Work smarter, not harder.” AI is a competitive advantage for marketers already using it and a great skill to have on the old resume.

We want to help you cut through the AI clutter and learn 6 specific ways you can use AI now to improve your marketing results:

1. Save time doing creative tasks like creating imagery and videos and writing copy for blog posts, emails, texts, social posts, etc.
2. Automate sending an email or SMS at the best time for it to be opened by the recipient based on their past email and SMS interaction history aka send time optimization
3. Automate selection of the next best content to resonate with a customer (i.e. content in an email, landing page, your website). We recently wrote a blog post about this
4. Automate the selection of the next best marketing channel to reach a customer
5. Automate selection of the next best offer to get a customer to purchase a product or service (or sign up for a demo, request a quote, etc.)
6. Automate selection of the next best product recommendation to get a customer to purchase another product or service (think cross-sell and up-sells)

There are many other ways you can use AI now to improve your marketing but we chose these 6 because they move the needle the most in saving your team time, improving the customer experience, and increasing marketing conversions and sales.

TIP: You will need more than one technology to do most of this cool stuff such as a Customer Data Platform (CDP) to do the AI-powered recommendation and a platform to execute the recommendation such as a Marketing Automation Platform (MAP), Content Management System (CMS), and/or Commerce Platform (CP). As AI functionality advances, it will likely/hopefully become more embedded in MarTech and involve less need for multiple platforms with integrations between them. 

That said, there are MarTech platforms a step ahead that have AI features embedded in them for a few years now such as Salesforce Marketing Cloud with its Einstein AI features, Adobe Marketo Engage with its Predictive features, and Oracle Eloqua with its Advanced Intelligence features. But, even these fancy MAPs can’t handle all of the marketing use cases above alone. For use cases 4, 5, and 6 above, most MAPs require another platform such as a CDP to power the data science models used to drive the AI features. Let’s go through a few of the use cases above and see how you can use AI now to improve your marketing.

Expedite your creative tasks like creating imagery and videos and writing copy for blog posts, emails, texts, social posts, etc.:

• Content creation AI tools like Google Bard, OpenAI ChatGPT, Jasper AI, and Pictory are popular because they are easy to understand what they do and even easier to use. And, they save us marketers a lot of time…like 80% time savings on writing first drafts according to Jasper AI. For example, you can ask Bard or ChatGPT to “draft a blog post that’s at least 1500 words about the history of AI” and within seconds, it will do so. Jasper AI will also translate it for you into up to 30 different languages. Pictory will create a video for you such as from one of your blog posts, webinars, or a script you provide, add captions and subtitles, and allow you to edit the video.

Automate selection of the next best marketing channel to reach a customer:

• Customer Data Platform (CDP): Your CDP would ingest your customer data from various sources such as marketing-tracked activities from your Marketing Automation Platform and Web/Mobile Analytics Platform, and purchases from your CRM or whatever platform stores your customer purchases. The CDP would use a data science model to analyze data about the customer including the channels they responded to most and the channels that resulted in the most purchases from the customer. Then, it would provide its recommendation by updating a customer field (or as some call it, an “attribute”) called, “Next Best Marketing Channel” with a value such as Email, Web, SMS, or Push.
• Marketing Automation Platform (MAP): Your CDP would be integrated with your MAP so it could write a value to your MAP’s corresponding field, “Next Best Marketing Channel.” In a campaign in the MAP, you would have the decision to check the “Next Best Marketing Channel” field and if the field value is “Email,” the next campaign step would be to send an email. If the field value is “SMS,” the next campaign step would be to send an SMS. And so on.

Automate the selection of the next best offer to get a customer to purchase a product or service (or sign up for a demo, request a quote, etc.)

• Customer Data Platform (CDP): Your CDP would ingest your customer data from various sources such as marketing-tracked activities from your Marketing Automation Platform and Web/Mobile Analytics Platform, and purchases from your CRM, Commerce platform, or whatever platform stores your customer purchases. The CDP would use a data science model to analyze data about the customer including the CTAs in campaigns that they responded to most and the CTAs that resulted in the most purchases from the customer. Then, it would provide its recommendation by updating a customer field called, “Next Best Offer” with a value such as Request a Demo, Request a Quote, or 30% Off Promo Code.
• Marketing Automation Platform (MAP): Your CDP would be integrated with your MAP so it can write a value to your MAP’s corresponding field, “Next Best Offer.” In a campaign in the MAP, you would have the decision to check the “Next Best Offer” field and if the field value is “Offer A,” the next campaign step would be to perhaps send an email or SMS with Offer A. If the field value is “Offer B,” a different campaign step would be to send an email or SMS with Offer B. And so on.
• Advertising Platform (AP): Your CDP would also be integrated with your AP so it can send specific offer segments (lists of contacts) to the corresponding AP audiences. The AP would be configured to display “Offer A” when a new contact enters the “Offer A Audience.” For example, the CDP would send a specific segment of contacts for “Offer A” to the corresponding Google audience called, “Offer A.” Most CDPs can send segments of contacts to various APs such as Amazon Ads, Facebooks Ads, Pinterest Ads, etc.

Automate selection of the next best product recommendation to get a customer to purchase another product or service (think cross-sell and up-sells)

• Customer Data Platform (CDP): Your CDP would ingest your customer data from various sources such as marketing-tracked activities from your Marketing Automation Platform (like product-specific messages the customer responded to) and Web/Mobile Analytics Platform (like product pages the customer visited) and purchases from your CRM, Commerce platform, or whatever platform stores your customer purchases. The CDP would use a data science model to analyze this data about the customer’s purchase history, products not purchased but relevant, and products the customer has shown interest in. Then, it would provide its recommendation by updating a customer field called, “Next Best Product Recommendation” with the corresponding product name.
• Marketing Automation Platform (MAP): Your CDP would be integrated with your MAP so it can write a value to your MAP’s corresponding field, “Next Best Product Recommendation.” In a campaign in the MAP, you would have the decision to check the “Next Best Offer Recommendation” field and if the field value is “Product XYZ,” the next campaign step would be to perhaps send an email or SMS with content about Product XYZ. If the field value is “Product 123,” a different campaign step would be to send an email or SMS with content about Product 123. And so on.
• Content Management System (CMS) or Commerce Platform (CP): Your CMS or CP should be able to do this alone, without a CDP, if it has a product recommendation AI feature. For example, Adobe Commerce and Oracle Content Management both have a product recommendation AI feature. They both use machine learning to analyze a customer’s purchase history and then provide a list of recommended products on the website or online store. You have to supply a product inventory for the feature to reference so it knows which products make sense for cross-selling and up-selling when another product is purchased. But then it does the magic from there.

As you can see, there is A LOT you can do to use AI to improve your marketing. Just like anything, we recommend you start by executing 2-3 of these AI marketing use cases and evaluate the results. You should see positive results like time savings and/or increased conversions which will help you justify the budget needed to execute more AI marketing use cases.

Conclusion

AI is a powerful tool that can be used to improve marketing results. By personalizing content and offers, automating tasks, improving decision-making, creating engaging experiences, and gaining insights into customer behavior, AI can help you reach your target audience, increase conversions, and improve customer loyalty.

If you are not already using AI in marketing, I encourage you to start exploring the possibilities. AI has the potential to revolutionize the way you market your business, and it is only going to become more powerful in the years to come.

Need help determining where to start or how to use AI now to improve your marketing? Contact Us and one of our Marketing AI Experts will be happy to help.

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