Navigating AI & ML in Digital Marketing: Best Practices and Pitfalls to Avoid

It's likely that your company has already integrated artificial intelligence (AI) and machine learning (ML) tools into your digital marketing efforts. According to Salesforce, four out of five businesses are utilizing these technologies. Their research also reveals that 70 percent of high-performance marketing teams have a well-defined AI and ML strategy, compared to 35 percent of their counterparts. Undoubtedly, AI and ML have the potential to streamline your digital marketing processes and significantly enhance efficiency. However, it's crucial to acknowledge the potential challenges and pitfalls associated with leveraging this technology. As you implement and engage with AI and ML, understanding both the benefits and risks becomes essential.

What is Artificial Intelligence and Machine Learning in Digital Marketing?

Artificial Intelligence (AI): Computer software designed to emulate human thinking for task execution and learning through experience.

Machine Learning (ML): A subset of AI utilizing algorithms to build models that perform tasks, with applications "learning" through the analysis of datasets.

Examples of Artificial Intelligence Implementation in Digital Marketing

Nearly any software used to automate digital marketing processes operating on predefined rules harnesses AI, though not necessarily ML.

Chatbots: Rule-based chatbots employ basic AI, initiating interactions with questions like, "What department do you need to reach?" and offering choices. They may even recognize keywords and search for relevant articles to provide users with helpful responses.

Segmentation: Programs can divide audiences and lists based on selected criteria.

Reporting: Numerous analytics programs automatically compile and share reports at specific intervals.

Planning: Many project management tools for marketing teams leverage AI. For instance, Wrike can convert handwritten notes into digital documents, create action items from your notes, and help you balance workloads.

Examples of Machine Learning in Digital Marketing

Testing: Certain A/B testing programs use predictive analytics to gauge which variant will win using small datasets.

Segmentation: Certain platforms can autonomously categorize individuals based on their behavior, exemplified by the creation of lookalike audiences.

Paid Ads: Platforms like Google provide insights into the expected number of clicks achievable by increasing your ad budget.

Generative AI, a subset of machine learning, is employed for various purposes. For instance, OpenAI utilizes machine learning algorithms to analyze extensive datasets and generate content on demand. Marketers leverage generative AI to power chatbots, generate blog content, and more. Developers use it to write code for new programs and identify bugs. This technology can also automatically generate images and videos.

The Controversy Surrounding AI Tools

Despite their efficacy as marketing tools, there are apprehensions regarding the potential misuse of AI and ML technology.

Potential for Misuse: From the creation of deepfakes to concealed code enabling unauthorized access by hackers, there exists a risk of the technology being exploited or abused.

Misinformation: Generative AI lacks the ability to discern fact from fiction, often resulting in hallucinatory outputs. Its reliability in conveying truthful information is questionable, and tools automating content production may intentionally contribute to the rapid dissemination of inaccurate information.

Plagiarism: These tools learn through data processing, and consequently, their generated content reflects the input they have received. They are susceptible to blatant plagiarism, reproducing material they have "read" without proper attribution or originality.

Google’s Stance on AI-Generated Content

Google has officially stated that all content is treated with equality. The search engine's algorithms do not discriminate based on how the content is created; it undergoes the same processing regardless of its origin.

“Appropriate use of AI or automation is not against our guidelines,” Google says. “This means that it is not used to generate content primarily to manipulate search rankings, which is against our spam policies.”

How AI-Generated Content Could Affect Your SEO

While Google's assurance may provide a sense of relief to businesses already incorporating websites filled with AI-generated content, it warrants a cautious interpretation. The company is consistently striving to enhance the user experience and, in pursuit of this goal, assesses content for indicators of experience, expertise, authoritativeness, and trustworthiness—collectively known as E-E-A-T signals—outlined in its quality guidelines.

Considering the inherent shortcomings of AI, such as inaccuracies, potential plagiarism, and a lack of personal experience in the subjects it addresses, the question arises: Can AI-generated content genuinely align with the E-E-A-T guidelines on its own? The short answer is "no."

Furthermore, recognizing that search engines, including Google and other platforms, are now capable of identifying AI-generated content, overloading a website with such material might be detrimental to its overall quality, leading to a decline in SEO rank.

This doesn't imply that generative AI has no place in your digital marketing strategy; rather, it emphasizes the necessity of careful consideration and judicious use when incorporating it.

Embracing ML and AI in Digital Marketing: Dos

Adhering to recommended practices while incorporating AI into your digital marketing strategy ensures you reap the advantages while avoiding potential pitfalls.

Focus on Meeting User Needs

Everything you do should center on one goal: meeting user needs. You can use tools to support your initiatives and work more efficiently, but if what you're doing isn't helping the real people who visit your site and view your content, it won't help your business in the long run, either.

Use AI-Generated Content as a Starting Point

Treat generative AI like a content brainstorming tool rather than a content creation tool, especially with long-form content that search engine algorithms will scrutinize for quality.

Include Other AI Tools in Your Content Creation

Keep working with content aggregators/curation tools, keyword analyzers, grammar checkers, and other platforms to help ensure your content is relevant, put together well, and delivers maximum value. Generative AI tools don't do it all.

Ensure Accuracy and Quality in AI-Generated Content

Don't assume your AI tool is providing you with accurate information. If you don't have a subject matter expert (SME) reviewing content for accuracy, be sure to research any statements you make to ensure they're factual. Keep Google's E-E-A-T guidelines in mind.

Incorporate Accurate Author Bylines in AI-Generated Content

Google favors content created by a subject matter expert. The company even hires evaluators to review websites to look for details on who created the content and what their credentials are. If a human with expertise reviewed or wrote your content, include a byline that links to information proving their status as an SME.

Check All Content for Plagiarism

Run everything your AI tool creates through a plagiarism checker before publishing.

Avoiding Pitfalls in ML and AI Applications: Don'ts

In addition to following the best practices highlighted above, it's essential to avoid the common missteps below.

Exclusively Depend on AI

AI can't do it all. Humans must be involved in your content creation and review process.

Trust AI-Generated Images without Verification

Sometimes, the mishaps seen in AI-generated images are comical, like when a program "forgets" to add hands to a person or adds an extra row of teeth, like in the product photo shown here. But bear in mind that the images you share, even simply for illustrative purposes, represent your brand. Always proof them for accuracy.

Use AI to Manipulate Search Rankings or Spread Misinformation

Your site can get permanently blacklisted by Google if you violate its terms. That means it will never appear in search results no matter what you do or may only appear with a warning, the company reports. This is a traffic source most businesses can’t afford to lose, considering that more than 90 percent of searches go through Google, per StatCounter.

Assume AI-Generated Content Adheres to Google’s Guidelines

Even if you try to seed your prompts with phrases like "only provide proven and factual information," generative AI tools will do whatever they "want" to do in the moment.

Neglect a Holistic SEO Strategy or Best Practices

While AI can help you improve your SEO, identify opportunities, and craft content, it's not a substitute for a comprehensive SEO strategy that includes obtaining relevant backlinks, creating a sensible site structure, developing topical authority, and more. You must address SEO holistically to have a site that ranks well.

Get Help Improving Your Digital Marketing with AI and ML

In my role as a digital marketing consultant, I seamlessly integrate artificial intelligence and machine learning into my strategies, utilizing them as supportive tools that enhance the efficiency of digital marketing teams and yield superior results. If your digital marketing team needs help realizing its full potential or you want to boost your digital marketing results, let’s talk. Contact me for a complimentary consultation.

You can also read this article on my website, The Dos and Don’ts of AI & ML in Digital Marketing.

For a regular dose of exclusive content and the latest marketing insights, sign up for my bi-weekly newsletter – it's completely free!