AI improving Marketing Automation

As brands continue to prioritize the customer experience and customers’ attention spans become more selective, AI is increasingly helpful for analyzing huge amounts of impactful marketing data and improving marketing automation capabilities. 

For revenue-focused marketers, AI can process huge amounts of data along the customer journey to find areas of improvement. This data can also help marketers understand how to create attention-worthy omnichannel content. In fact, a recent survey of 600 executives across 18 countries found that nine out of ten companies use AI-enabled solutions specifically to improve the customer journey. 

AI and Marketing Automation

If you’re not already familiar with marketing automation, you will be soon! 67% of marketing leaders currently use an automation platform, and 21% say they plan to in the next two years. 

Marketing automation, just like it sounds, enables you to automate redundant marketing and marketing engagement/activities. At a basic level, it helps generate more leads, nurture leads and existing clients, close more deals more efficiently, and effectively measure marketing success. A marketing automation platform, like Pardot or Marketing Cloud, compiles all your marketing data in one place and helps connect the dots between all your intersecting marketing campaigns. 

Only recently has AI been added as a feature of powerful marketing automation platforms. The fact that AI runs on data makes it a perfect add on for marketing automation platforms – most marketers’ ultimate source of truth for customer data. By using AI-enabled marketing automation tools, marketers are able to identify qualified leads sooner, build smarter email nurture programs, and create more relevant content.

Here are 3 key ways that AI is improving marketing automation:

  1. Identify Qualified Leads Sooner:
    AI-powered predictive lead scoring significantly enhances the efficiency of lead generation by intuitively identifying leads that are the most engaged and qualified. Predictive leads scoring uses data such as demographics, social information, and behavioral data to analyze how qualified a potential lead is. This helps marketers and sales teams quickly focus efforts on leads that are more likely to turn into revenue.Einstein Behavior Score is Pardot’s predictive lead scoring tool powered by AI. It predicts buying intent by analyzing sales activity data found in Sales Cloud, and evaluating marketing engagement and positive trends in behavior.
  2. Build Better Email Nurture Programs:
    Marketers can leverage AI with marketing automation to analyze data and automatically deliver predictive, intelligent lead nurture and customer engagement experiences at scale.AI-powered Marketing Cloud Einstein Content Selection allows marketers to send unique, personalized email content for each customer. You simply give Einstein access to your content assets, then when you begin sending, Einstein selects the best asset for each customer, based on the customer data available. Next, Einstein begins analyzing the performance of the sent content to find out which assets have the most engagement and prompt customers to click a link on the email. As Einstein discovers the content that contributes to increasing click rates, Einstein selects that asset more frequently as it continues to send emails.
  3. Create More Relevant Content:
    By processing and depicting your customer data, AI can help you predict the type of content your audience is most interested in and would resonate best with. This helps marketers work smarter by easily curating online experiences to individual customers. By tailoring content to each individual’s needs and interests, marketers can provide the relevant answers to potential buyers’ questions as they move closer to a purchasing decision. Smart content personalization contributes to more successful SEO, helps nurture leads better, and creates more enjoyable customer experiences. Einstein segmentation enables marketers to build the best audience for each marketing campaign. By using machine learning and pattern analysis, Einstein segmentation analyzes billions of customer signals from within the Salesforce data management platform (DMP) and helps marketers discover buyer personas that exist within their audiences so that they can craft unique content for each buyer persona instead of sending a one-size fit all message.

As AI continues to improve the world of marketing automation, marketers will be able to easily consolidate the marketing tools that they use to create and analyze customer experiences. Marketers using AI-enabled marketing automation can create customer experiences that are highly targeted, relevant, and effective. We’re excited!

About the author

Alicia is a Digital Marketing Manager and Pardot Consultant at Kadence Digital. She is passionate about creating meaningful marketing campaigns, creative strategies, and technology that makes life easier. You can find her exploring Austin, Tx with her puppy, Rory.