How to Seamlessly Integrate AI Marketing Into Your Strategy

As marketing evolves, technology plays a bigger role in our strategies, processes, and outcomes. And today, the darling of technology is AI, or artificial intelligence. 

AI functionality has already been added to most marketing tools and software. Once trained, it provides customized solutions, allowing marketers to work more effectively with fewer resources. 

But you may still be wondering how to be more intentional about integrating AI marketing into your strategy, how to use AI for marketing, or how AI is changing the future of digital marketing.

In this article, we’ll answer these questions and more:

• What is AI marketing?
• What are the benefits of AI in marketing?
• What are the potential challenges of using AI in marketing?
• Key areas to integrate AI-powered marketing
• Steps to integrate AI marketing into your strategy
• Measuring success: KPIs and metrics
• Preparing for the future of AI Marketing

What Is AI Marketing?

AI marketing is the use of artificial intelligence to improve marketing programs’ capabilities and results. Designed to mimic the deep learning and problem solving abilities of humans, AI tools are proving to be a key differentiator for marketers, especially for tasks that require a lot of data analysis, repetition, or speed. 

While it may appear to be the new kid on the block, AI has been quietly integrated into marketing tools since the early 2000s. A good example is Amazon’s recommendation engine, which showcases products you may be interested in based on your shopping habits and searches.

Another good example is Google. Before you begin typing (or speaking) your query, it shows you a list of trending searches. Then as you type, it generates a list of possible keywords based on your online behavior, topics you’ve shown interest in, and websites you’ve visited. 

Marketing tools are already using AI to provide:

• Email personalization and send-time optimization that increases open rates and engagement
• Customer service chatbots that answer customer questions and recommend next steps
• A/B testing that automatically serves the variations most likely to yield results
• Ad targeting that identifies specific audiences and optimizes ad placement for the best ROI
• Social media optimization that uses engagement metrics to suggest the best times to post
• Personalized marketing campaigns that segment audiences and deliver personalized content, offers, and recommendations

These are just a few examples of how AI has been working with traditional marketing tools to leverage data-driven insights and automation for competitive advantage. And AI’s role in marketing is likely to continue expanding as businesses understand how powerful and flexible it can be.

Types of AI Marketing Solutions

Every day, marketers find more use cases for AI marketing tools. Currently, they are focused on four key areas: managing and analyzing databases, natural language processing, conversion rate optimization, and integrated applications.

Data Analysis & Prediction

This type of AI marketing solution is designed to gather and consolidate data from various sources — for example, marketing activities, customer interactions, third-party apps, website behavior, and sales transactions — and prepare it for analysis. 

AI can enhance database management. For instance, AI can quickly identify and fill in empty data fields or reformat data to ensure it’s in the correct format. 

AI algorithms can analyze the data to find patterns, trends, and correlations. It can compare new insights with historical data to make predictions or classify information. It can then make recommendations or perform optimization tasks, depending on the use case.

A good example of this is NeuronWriter.

This tool does your SEO competitor research in minutes. You only need to enter your target keyword. The AI reviews competitor pages and tells you what it would take to rank at the top of the SERPs for that keyword. Then, as you write, it grades your article based on NeuronWriter’s recommendations.

AI tools that leverage data analysis and prediction include:

• Customer relationship management (CRM) platforms
• Predictive analytics
• Customer behavior forecasting tools
• Marketing automation tools
• AdTech platforms
• Chatbots and virtual assistants
• Analytics and business intelligence tools
• Marketing attribution software

Natural Language Processing (NLP)

AI solutions using natural language processing can improve the customer experience by making human-computer interactions feel more natural and efficient.

NLP does this by analyzing user input, identifying the intent and sentiment behind the query, and answering the user’s question or providing the right information.

An example of this is Apple’s Siri. Ask it any question, and it will provide answers or recommendations. Here’s what she told me when I asked for a list of NLP applications:

AI tools that leverage NLP include:

• Search engines
• Voice search optimizations
• Autocorrect and spell-check features
• Voice assistants
• Customer support chatbots

Ad Targeting Platforms

Ad targeting platforms use automation to streamline the research and decision-making behind successful marketing campaigns, ultimately improving results. They can take care of:

• Data collection and analysis
• Audience segmentation
• Real-time bidding
• Ad creative personalization
• Ad placement and scheduling
• Budget allocation
• Performance tracking. 
• Fraud detection
• A/B testing 

This type of AI tool is designed to help marketers maintain a data-first approach to advertising without having to dedicate hours (or days) reviewing databases and spreadsheets. And it typically returns better results.

In 2015, Volkswagen decided to test AI’s ability to improve its advertising results, giving its digital business to a Danish media agency that uses AI and predictive analytics to forecast ad spend decisions. Between September and December 2016, it saw a 14% rise in orders from Volkswagen’s dealerships. 

Similarly, luggage brand Monos decided to test Meta’s machine-learning technology against its usual complex ad campaign setup. Again, AI won:

• 58% decrease in incremental cost per purchase using Meta’s AI 
• 35% increase in incremental return on ad spend with Meta compared to a usual campaign setup

AI tools that leverage targeting include:

• Automated email marketing software
• Social media scheduling platforms
• Programmatic ad placements

Integrated Applications

Another type of AI marketing solution, integrated applications, has built-in AI capabilities. They use AI machine learning to enhance functionality and provide intelligent features. 

A good example is Google Workspace. The search giant is committed to using AI to streamline people’s work, making them more productive. So it seamlessly integrates AI into all of its applications, including Gmail, Calendar, Docs, and Sheets. 

According to Google Senior Fellow Jeff Dean, “We want to use AI to augment the abilities of people, to enable us to accomplish more and to allow us to spend more time on our creative endeavors.”

Of course, Google isn’t alone in this effort. You can see AI technology integrated into most digital applications, including:

• Recommendation engines
• AI-driven content curation tools
• Personalized ad servers

What Are the Benefits of AI in Marketing?

With the depth and breadth of AI solutions available now, AI has become an integral part of the modern marketing program, benefiting both practitioners and the business as a whole. But you may still be asking yourself, “Can AI marketing increase conversion rates?” 

Fortunately, AI can not only improve conversion rates, it can streamline your entire workflow, helping you get better results in less time. Let’s look at a few ways it’s doing that.

Data Analysis at Scale

AI can consolidate and analyze data more efficiently, accurately, and cost-effectively than humans. (Sorry, but it’s true!) Because the data is available in near real-time, it can give you a significant competitive edge.

One of the best examples is Burger King’s 2018 “Whopper Detour” campaign, which later won the 2020 Grand Effie award. 

Using geofencing technology, Burger King’s AI-powered app notified customers when they came within 600 feet of their competitor, McDonald’s. The offer? A Whopper for one cent. 

Customers were told to order their Whopper on Burger King’s app. They were then directed away from McDonald’s to the nearest Burger King restaurant to pick up their food.

AI-driven data analysis was essential for identifying the target audience and optimizing the geofencing strategy. According to Jose Cil, CEO of parent company Restaurant Brands International, “We generated over 1.5 million downloads from the initiative, making the Burger King app the number one most downloaded app in the Apple store for several days in a row and the most downloaded QSR app in the U.S. among our direct competitors in December.”

More Efficient Customer Segmentation

AI algorithms can quickly analyze customer data to segment customers based on a range of factors, including demographics, past purchase history, online behavior, and interests. As a result, marketing campaigns are more likely to hit the mark.

One notable example is Netflix. Their algorithm analyzes users’ viewing history and interactions to deliver personalized movie and TV show recommendations.

Personalized Marketing Campaigns

This level of segmentation helps marketers deliver the right message to the right people at the right time:

• Making content and product recommendations
• Personalizing email campaigns, including sending them at the optimal time
• Displaying dynamically generated website content
• Delivering more relevant ads

Personalization can reduce customer acquisition costs (CAC) by 50%, increase revenue by 5-15%, and boost ROI by 10-30%, according to McKinsey’s Next in Personalization 2021 Report.

Test and Optimize Pricing

With AI’s ability to assess risks and opportunities, collect and analyze data, and predict behavior, it’s being used to optimize prices across the customer and product mix. 

That’s exactly what Levi’s did during the pandemic. Relying on AI recommendations, they were able to raise prices and increase margins when many retailers were discounting heavily. This chart by Business of Fashion shows how quickly they were able to adjust their strategy when the pandemic hit, ensuring their finances stayed strong. 

Cost Reductions

For better or worse, many marketing teams are operating leaner, choosing to invest in AI rather than more employees. This has given them an immediate cost savings. But it’s not the only way AI is helping marketers reduce costs. 

The first is productivity. In a report on the economic potential of generative AI, McKinsey found that generative AI could increase the productivity of the marketing value between 5 and 15% of total marketing spending, a cost savings of approximately $463 billion. 

The second economic impact is more derivative. Because generative AI can provide deeper data insights, better targeting, and more efficiencies in ad spend, it has the potential to reduce costs on external channels and agencies. 

A third area, as mentioned above, is AI’s ability to optimize pricing in near real time. According to the Global Tech Council, this doesn’t just reduce marketing costs. It also brings in more revenue.

What Are the Potential Challenges?

As excited as people are about the benefits of AI, there are also concerns, largely because it’s hard to imagine a world powered by AI. Will AI technology ultimately replace humans? Will it dumb down marketing and business, or worse, raise the bar so high that it’s difficult to compete? How do we manage privacy and security, overreliance on AI, and keeping up with changing technology?

AI may feel like Pandora’s box — now that it’s open, there’s no going back. But it’s important to remember, AI is just a tool. If we remain adaptable, collaborative, and ethically aware, it will serve us, and not the other way around. 

Every advancement in history has required people to retool and acquire new skills. We need to invest the time and resources into learning more about AI and other advancements in technology. 

We need to use AI properly, not to replace humans but to free them to do work that humans excel at, such as networking and thinking outside the box. 

We need to stay informed about data privacy and security regulations and be cautious about sharing personal information online. 

We need to advocate for ethical AI development and deployment, promoting transparency, accountability, and fairness in AI systems. 

We need to engage with policymakers and industry leaders to ensure AI benefits society as a whole.

Key Areas to Integrate AI-Powered Marketing

To stay competitive, businesses need to embrace AI marketing. So let’s look at four ways you can develop an AI marketing strategy.

Predictive Analytics

Predictive analytics predicts future trends based on patterns, relationships, and insights from current and historical data. In the business world, it’s primarily used to inform future business decisions and strategies. 

For example, you might use it to:

• Gather insights from huge amounts of historical and real-time data
• Anticipate future market trends
• Identify potential opportunities and risks
• Allocate resources more effectively
• Optimize marketing strategies

Some industries that rely heavily on predictive analytics are e-commerce and retail, financial services, healthcare, hospitality, and travel.

Chatbots and Virtual Assistants

Another way to integrate AI into your marketing is to use chatbots to improve customer service on your website and call center. The benefits are undeniable: 

• They can support a high volume of customer queries at the same time. 
• They’re available 24/7.
• They reduce response times and give customers a consistent brand experience. 
• They’re able to understand the context and sentiment of a conversation.

They are also more consistent about delivering brand messaging than humans can be, which is one of the reasons they can lift sales. According to Ometrics, chatbots can increase average order value (AOV) by 5-35% and revenue by 20-40%.

And in case you’re having doubts, chatbots can provide a customized experience for users. 80% of consumers seem satisfied with their chatbot experiences, according to a study by Uberall. 

Content Creation and Curation

One of the most talked about uses for AI is content creation and curation. Used properly, GPT (Generative Pre-trained Transformer) tools can help marketers create more content at scale, including text, images, music, and more. But without the human touch, AI content can still come off as flat or generic. 

That said, these tools can improve content creation if they’re used to leverage marketing AI’s greatest strengths: data analysis, NLP, and machine learning. For instance, these tools can save hours on marketing strategy, research, and optimization by:

• Analyzing competitor content
• Optimizing headlines
• Improving image selection and placement
• Generating topics based on engagement
• Analyzing content performance
• Identifying the best platforms and times to publish content
• Recommending content that users are most interested in

Personalized User Experience

Another great place to integrate AI into your marketing strategy is to create highly personalized experiences that resonate with individual customers and website visitors. For example:

• Recommending products and services similar to those they’ve already viewed or purchased
• Customizing content based on the user profile and behavior
• Dynamic pricing that adjusts pricing in real-time
• Generating custom content that aligns with user interests and preferences
• Location-based personalization
• Privacy and consent management

AI-driven personalization is becoming more sophisticated, creating a more relevant and engaging experience. And it’s paying off: 

• Higher AOV 
• Better retention rates
• Lower cart abandonment rates
• Better marketing ROI
• Increased customer loyalty
• More engagement

Steps to Integrate AI Marketing into Your Strategy

There’s no arguing the value of AI marketing. The challenge is transitioning from where you are to where you want to be. To help, we’ve come up with a five-step process for integrating marketing artificial intelligence into your current strategy:

1. Set your objectives.
2. Choose the right AI tools.
3. Collect and organize your data.
4. Test and optimize your strategy.
5. Regularly update your marketing strategy.

Step 1: Start with Your Objectives

Before making wholesale changes to your marketing strategy, you need to know what you’re trying to achieve. 

The technology itself won’t transform your processes or improve your outcomes. So take some time to identify the specific improvements you’d like to make with AI capabilities. For example:

• Increase personalization
• Improve conversion rates
• Cut CAC by X percent
• Optimize ad spend
• Increase cross-selling and upselling
• Enhance lead scoring
• Reduce marketing automation errors

Step 2: Choose the Right AI Tools

Now that you’ve set your objectives, you need to choose the appropriate AI marketing tools and platforms that will help you achieve those goals. Here are some popular tools, sorted by category (some products cross categories).

CRM

• HubSpot CRM
• Insightly
• Microsoft Dynamics 365 AI
• Salesforce Einstein
• Zoho CRM Plus

Personalization

• Adobe Target
• Dynamic Yield
• Evergage
• Qubit
• Sitecore

Ad Optimization

• Adobe Advertising Cloud
• AdRoll
• Criteo
• Skai (formerly Kenshoo)
• WordStream

Analytics and Behavioral Insights

• Crazy Egg
• Google Analytics 4
• Mixpanel
• Quantcast Measure
• Smartlook

Chatbots

• Drift
• Gupshup
• IBM watsonx Assistant
• Intercom
• Zendesk Answer Bot

A few tips: To choose the best product for your needs, start with the categories that align with your goals. While you do need to consider your budget, try to avoid shopping by price. Look closely at the tools’ features and how they function. Verify that they will integrate with the other tools you use. And look for reviews to get an idea of how they work and how responsive customer support is.

Step 3: Collect and Organize Data

Data is critically important in AI since the technology is built on a foundation of high-quality, well-organized data. You’ll need to clean your data regularly, keeping it complete, accurate, and error-free. 

Of course, you can use AI to clean your database, removing duplicates, entering missing fields, and verifying that all formats and units are consistent.

Step 4: Test and Optimize

Markets, customer behaviors, and trends are always evolving. Testing helps you validate the assumptions made during the development of AI strategies. It also ensures your strategies align with real-world outcomes. Here are a few methodologies that are used to optimize AI tools:

• A/B testing – compares two versions of a strategy or algorithm to find the one that performs better
• Performance optimization – identifies areas where the AI needs to continue learning
• Adaptation to changes – keeps your AI systems relevant and competitive
• Benchmarking – compares your AI system’s performance against industry standards

Step 5: Regularly Update Your Strategy

AI is rapidly advancing. When you adopt AI marketing, you’re committing to continuous learning — it’s essential to stay on top of AI technologies, tools, and best practices. 

Make sure you’re up-to-date on the ethics of AI in marketing, especially data privacy, security, transparency, and bias. Your AI practices should always align with ethical standards and regulations.

Of course, you should also track and measure the ROI of AI and adjust your AI marketing strategy accordingly.

Measuring Success: KPIs and Metrics

The KPIs (key performance indicators) that are relevant to AI-driven campaigns aren’t that different from the KPIs you’re already tracking:

• Conversion rate
• Clickthrough rate
• Customer acquisition cost (CAC)
• Customer lifetime value (CLV)
• Churn rate
• Customer retention rate
• Lead quality

But you can test the effectiveness of your AI tools with these KPIs:

Personalization Effectiveness: Assess the impact of AI-powered personalization on user experiences, conversion rates, and customer satisfaction scores.

Predictive Analytics Accuracy: For predictive AI models, measure their accuracy in forecasting outcomes such as customer behavior, sales, or demand.

Time-to-Insight: Evaluate how quickly AI-driven analytics can provide actionable insights to inform marketing decisions.

Customer Segmentation Performance: Assess the effectiveness of AI-driven customer segmentation in tailoring marketing messages and offers to specific audience segments.

Fraud Detection Accuracy: For fraud-prevention-AI systems, monitor their accuracy in identifying and preventing fraudulent activities.

Compliance and Data Privacy: Ensure AI campaigns comply with data privacy regulations and assess the number of data privacy-related incidents or breaches.

Preparing for the Future of AI Marketing

AI is evolving quickly, which means it’s not a once-and-done strategy. Here are some emerging AI trends you need to be aware of:

Conversational AI and Chatbots 

Anyone who has interacted with ChatGPT will find traditional algorithmic chatbots frustratingly unhelpful. AI is learning to speak more naturally and understand the nuances of human conversations. This will only enhance its ability to perform customer support, lead generation, and user engagement activities.

AI-powered Content Generation

As GPTs improve, you’ll be able to leverage AI more effectively for content creation. But don’t let go of human quality control and oversight yet. The current crop of GPTs are notorious for “hallucinating,” requiring fact-checking by writers and editors. 

Voice Search and Voice Assistants

With Alexa, Siri, and other virtual assistants, voice search is on the rise. Not only should you start developing voice-based marketing strategies, you need to make sure content is optimized for voice search. 

Visual Search

Search algorithms now allow users to search for products or information using images. This is a boon for e-commerce businesses, but visual search can be leveraged by all of us. Make sure you optimize images for search, adding alt-tags and descriptions, so search engines know when to include them in search results.

Ready to Take the Leap with AI-Powered Marketing?

AI and marketing may feel like radically different strategies. In reality, they work together to help you crunch data faster, develop deeper insights and strategies, and achieve better outcomes with fewer resources.

For data-driven marketers, AI marketing can actually simplify the process of finding brilliant solutions that lead to impactful conversions.

Looking for AI optimization services from people who understand the critical importance of data? When you partner with Conversion Sciences, you get better conversion rates as well as a well-optimized process. Let’s chat.

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