There was a time when marketing campaigns were manual.
Analytics were primitive. Emails weren’t dripped automatically to a list. Customer behavior tracking was clunky and limited.
Marketing automation changed all of that.
From personalized email marketing to lead scoring to analytics, marketing automation connects it all. And it works—80% of companies that use marketing automation see an increase in leads, and 77% see an increase in conversions.
Now, AI is revolutionizing marketing automation.
By personalizing your campaign at scale and getting the right messages to the right customers, AI improves the customer experience. Artificial intelligence is also making marketers’ jobs easier by offering deep customer insights, predictive analytics, and real-time optimization.
Read on for a look at AI’s impact on marketing automation, examples of AI marketing automation in action, and a run-down of how to design an AI marketing automation campaign.
Introduction to Marketing Automation
Marketing automation means designing a marketing system with rules and workflows.
For example, if a customer downloads a lead magnet on your website, you probably need to do a few things right away:
- Send them the right lead magnet
- Create an entry for them in your CRM software
- Tag them for future reference based on where they signed up
- Start dripping an email welcome sequence over time to “warm them up”
- Send periodic SMS messages to inform the customer of special offers
- Use basic personalization (“Hi [first name], thanks for downloading [lead magnet]”)
Once you set up the workflow you need, marketing automation software does all of this for you.
Think of traditional marketing automation as a “marketing factory.” Although there isn’t any adaptive intelligence involved, you get huge efficiency gains by streamlining the grunt work of marketing.
By automating repetitive tasks, your time is freed up to focus on more strategic questions—like what’s working, what’s not working, and what your customers need.
AI takes all of this to the next level.
When AI Meets Marketing Automation
The limitation of traditional marketing automation is that it relies on your knowledge to create rules and workflows.
There’s no way you can know everything about customer behavior and trends across hundreds or thousands of customers.
That’s where AI comes in.
If marketing automation is like a marketing factory, adding AI to the mix is like hiring a 24/7 data scientist, content writer, sales assistant, and optimization engineer.
You’ll still have to make strategic decisions. But with AI, decision-making is easier because you’ve got a team to help you analyze data, provide recommendations, and adapt.
A few ways AI improves marketing automation:
- Personalization at Scale: AI helps personalize your marketing efforts at scale by automatically tailoring messages, content, and offers to each customer.
- Deeper Customer Insights: AI can analyze vast amounts of customer data, including social media interactions, purchase history, and cross-channel behavior. This gives you insights that lead to more relevant messaging and improved retention.
- Predictive Analytics: Predictive analytics allows you to anticipate customer needs, helping you create unique campaigns that resonate with each segment of your audience. Predictive analytics also helps you segment your customers in new ways—like each customer’s churn risk—unlocking a fresh perspective on where to devote your attention.
- Real-time Optimization: AI can analyze customer data and adjust marketing campaigns in real time, so you can reach customers with the most relevant messages and offers.
- More Efficiency: AI can automate repetitive and time-consuming tasks, like email campaigns and lead scoring, freeing up marketing teams to focus on more strategic and creative actions.
From your customers’ perspective, meaningful personalization is the key benefit of adding AI to your marketing automation system.
No one wants a generic marketing message for a product that’s irrelevant to them. AI marketing automation allows real personalization based on each customer’s behavior and preferences.
Examples of AI in Marketing Automation
Let’s take a look at some of the ways that AI is being used in marketing automation today.
With 63% of consumers getting annoyed with generic marketing messages, personalization is the way forward. Fortunately, AI makes it easier to create a relevant experience for each customer.
Take email marketing, for example.
Send time optimization adapts email delivery times based on each subscriber’s open and click behavior. Even more value comes from the personalization of email content. AI-powered systems can analyze customer data like purchase history, website behavior, and demographic information to create engaging email campaigns that are unique to each customer.
Here’s what a typical email AI recommendation integration looks like with GetResponse, a marketing automation tool:
(Image Source: GetResponse)
But personalization doesn’t end with email. Personalized messaging is now happening throughout the buyer journey, from ads to email to websites. AI marketing automation tools can improve engagement by serving different website messaging to different audiences, and are replacing traditional A/B testing techniques in favor of AI-driven continuous optimization.
Predictive Lead Scoring
Lead scoring is a method to sort prospective customers by those who are most likely to buy, so you can focus your energy on the most promising leads. Traditionally, this is done by scoring each customer based on factors like demographic data, job title, and company size, as well as their behavior. (For example, how often they open your emails).
The problem is, traditional lead scoring can be subjective, and assigning a weight to each variable can be a guessing game. Predictive lead scoring software is an AI-driven tool that integrates with your CRM and sales data.
Based on the data your software analyzes, it understands what makes a lead successful—and it can use that information not only to guide your lead scoring, but to guide your sales team’s next steps on each lead.
You can also use AI in a more proactive way—to hold dynamic questions with leads, cross-reference the answers with your lead scoring system, and determine whether they are qualified before passing them on to a salesperson. The below conversation, driven by the conversational AI platform Conversica, shows how this process works.
(Image Source: Conversica)
AI-powered customer segmentation systems can analyze vast amounts of customer data in real time, allowing businesses to create more accurate and effective customer segments. In a Persado survey, 35% of executives say customer segmentation is one of the most significant ways they are experimenting with AI.
Traditional customer segmentation happens either manually, by tagging a customer, or with a rules-based system that segments customers based on data in your CRM. By doing this, you can create messaging and offers that appeal to each group of customers.
But customer segmentation suffers from the same issue as lead scoring:
Because AI has access to the full scope of your analytics and customer behavioral data, it can uncover hidden patterns of behavior and segment customers in ways you might never have thought of.
For example, the customer segmentation tool Peak.ai creates a “single source of truth” for all customer data, then uses predictive analytics to group customers by factors like estimated likelihood to churn, propensity to purchase, and lifetime value.
At a glance, you can see where your most profitable customers are:
(Image Source: Peak.ai)
Designing an AI-Powered Marketing Automation System
Designing an AI-powered marketing automation system can be a daunting task, but it can also be a major catalyst for growth and success for your business.
Here’s how to do it:
Understand Your Business Objectives
Before you start selecting and integrating AI technologies, take a step back and reflect on what your business wants to achieve with marketing automation.
What tasks do you want to automate? What data do you need to collect and analyze to make informed decisions? Understanding your goals will help you determine which AI tools are best suited for your business.
Here are some common objectives:
- Increase Sales: Automating lead generation and nurturing processes can help businesses build relationships with potential customers and convert them into paying customers.
- Improve Retention: By personalizing content and segmenting customers, marketing automation can help you increase customer engagement and build stronger relationships.
- Lower Costs: Automating repetitive tasks, such as email campaigns and lead scoring, can free up your time to focus on higher-value tasks.
- Higher ROI: Marketing automation provides robust analytics and reporting capabilities that help track the success of your campaigns and measure return on investment.
Evaluate AI Marketing Automation Tools
As recently as the mid-2000s, most marketing automation tools were designed for enterprise use and inaccessible to many businesses. Today, there are tools for every budget and use case.
Let’s put them into a few groups for ease of evaluation:
Enterprise marketing automation
If you’re looking for a comprehensive marketing automation tool, enterprise tools like Marketo and Salesforce Pardot are well-suited for large companies with complex marketing needs, offering robust lead management, email marketing, and analytics capabilities. Some, like IBM Watson and Salesforce Einstein, are specifically designed to add a layer of AI and machine learning to enterprise marketing.
SMB marketing automation
If you’re a smaller business, you might find software like Active Campaign or Drift a better fit for your needs. Active Campaign is focused on email marketing, personalization, and CRM, while Drift is focused on conversational marketing and conversational AI.
AI marketing automation
All of these tools above—Marketo, Salesforce Pardot & Einstein, IBM Watson, Active Campaign, and Drift—have AI integrated to some degree.
But you may also want to consider some of the newer marketing automation tools that have been built from the ground up to take advantage of AI, like Peak.ai, a company aiming to be the “Salesforce of artificial intelligence.”
Integrate with Your Workflow
Once you’ve picked the tools that work for your use case, it’s time to integrate them into your marketing automation workflow.
The actual integration should be simple. For example, in the case of Drift, a simple API integration will integrate the software with commonly used CRMs like Hubspot or Salesforce.
From there, it’s time to take advantage of your new AI marketing automation features.
Here’s the best place to start:
- Start with easy wins to get momentum: Getting the most out of a new tool can be complex. Start with easy wins: set up predictive lead scoring, use AI recommendations to personalize your emails, and review predictive analytics for strategic insights.
- Use AI to segment your customers: You probably already have customer segments. But now that you have AI on your side, it’s time to go deeper. Use data analytics and machine learning to identify patterns and segment your audience in new ways.
- Adapt workflows: Workflows are the backbone of AI marketing automation. When designing your workflow, keep the entire customer journey in mind, and use triggers and actions that add value for your customers. If you’re importing workflows from your existing marketing automation system, you’ll want to adapt them based on the AI capabilities you now have.
- Personalize content: Now that you’ve got AI customer segments and AI-driven predictive lead scores, you can design highly-personalized content—especially for those customer segments that are most likely to convert. Use A/B testing to experiment with different messages and strategies.
- Keep refining: As time goes on, your customer segments may change. The messaging they respond to will change, too. Use data analytics to measure the effectiveness of your campaigns and keep adapting your workflows and content.
Remember to stay nimble when it comes to AI marketing automation software.
The application of AI to marketing is one of the transformative themes of this decade. New features are being released regularly. Review your workflow regularly to make sure you’re taking advantage of every feature you can.
The Future of AI and Marketing Automation
Popular brands like Amazon have already trained consumers to fall in love with personalization and AI-powered features. 66% of consumers expect personalized product recommendations from ecommerce brands, for example.
That means every brand that’s not already adding AI to its marketing automation workflow is behind the curve. The good news is that the latest AI tools make it simple—not only personalization, but so much more. AI will help you make sense of the vast sums of data generated by your customers, getting you closer to them than ever before.
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