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How To Responsibly Implement AI Marketing & Company Strategies

Written by: Will Soprano, Executive Contributor

Executive Contributors at Brainz Magazine are handpicked and invited to contribute because of their knowledge and valuable insight within their area of expertise.

 
Executive Contributor Will Soprano

Generative AI is everywhere – especially embedded into companies and marketing workflows. This critical mass is unique in that how we use the technology is more important than whether or not we use it. And I believe we’ve created inefficient market conditions in relation to generative AI.


AI in marketing - responsible implementation

As of December 2023 51% of marketers were using generative AI – a tool so new that a deep, personal understanding of the tooling hasn’t yet been explored en masse. This is why it’s an inefficient market, and has me wondering if anyone has asked the question: How do we use AI tools/techniques uniquely for us and our customers – maybe in a different way than others are sharing?

 

From on-page content marketing to demand generation through SEO, social media marketing, and paid ads, AI is an assistant all throughout the lives of a marketer today. Is it a necessity? No. Generative AI is incredibly useful, but that sweet sweet honey has a swarm of bees around it. And when companies don’t use AI well they get stung and stung badly.

 

So this post is all about how companies and marketers can respond to AI now that it’s reached critical mass – and given that I focus on content, product and SEO – that’s where we’ll focus our efforts today. But many of these concepts can be extrapolated into any of the AI trends in marketing like Social Media, Pay Per Click, PR, etc.


Current state of affairs: Marketing and AI


Executives and marketing departments everywhere are either leery of AI or using it in droves. Both curious and afraid, empowered and in the grips of FOMO. It’s all relevant and it’s all accurate, regardless of your current approach.

 

Search Engine Optimization (SEO) is in the midst of its most significant tumult since Google built their first index of the web in 1996, both in perception from executives and irresponsible incorporation of AI.

 

Our ever-personal vehicles like social media and email marketing have been turned upside down by an over-adoption of AI without first building out and testing models that work for their customer’s considerations and needs.


Competitor Research Paralysis


A part of any marketing department’s research is understanding its competition – after all, how can we know the market if we don’t know our competitors? This is an important step in asserting yourself – but it cannot be your basis for content creation. I call this Competitor Research Paralysis. And AI has fueled the destructive nature of this type of research that flies directly in the face of user, customer and marketing qualified lead (MQL) research that delivers the most successful results.

 

One of the ways this happens is when marketing tools that analyze competitor content are paired with AI, and either purposefully or not, becomes the sole basis for content creation rather than part of the research that informs the direction.

 

Add it all up and you’ve got one big mess – piling onto a content problem that we’ve been wrestling with for years. But it doesn’t have to be a mess – AI can actually be a tool that kicks free an age of personalization in human-led business, supported by a technological assistant.


Companies and marketing departments' use of Ai in content marketing and operations


Your industry is using AI, so are your competitors and their marketing departments in content marketing. They’re using it to scale content creation, optimize marketing tactics, and increase operational efficiency. From personalized recommendations to predictive analytics, AI and algorithms are driving targeted marketing campaigns and delivering more relevant content to audiences. However, the widespread adoption of AI has also raised concerns about content quality, user privacy, and the erosion of authenticity in marketing communications.

 

The critical mass that’s accumulated so quickly has created an inefficient market – ripe for disruption and anyone asking these types of questions is a little further along than their peers. So how do we increase authenticity, content quality and user experiences – all while maintaining the speed and scale that generative AI offers?


How to implement AI in marketing operations


Before you use AI one more time, it’s vital that we understand its role: an assistant to you and your team. When we remember all forms of AI as an assistant, we can better divvy up the tasks and duties. The next most important thing is to understand your customers, users and MQLs as well as understand your company and product. And if you’ve crossed the first two barriers, here are a few ways to implement AI in marketing:

 

  • Avoid Competitor Research Paralysis

  •  Generative AI Models for predictive analytics

  • Media buying to find where / when to buy

  • Content summaries & report creation

 

I have a process for content and marketing operations that is assisted by AI and models that I create (and iterate on constantly). But the number one thing that I never compromise on is the data and information used. AI can only know what we tell it – sure, it can scrape the web, but it will fall to the lowest common denominator rather than the most precise and educated answers. That means that in order for you to deliver on your customer needs you MUST lead the conversation with information directly from, or with your customer’s unique needs in mind.


SEO and AI


Executives are right in their fears of SEO because marketers have been irresponsibly implementing tactics and AI to scale efforts. But this conversation doesn’t have to be binary. The core of SEO is writing and creating for your users – and only considering their needs. But time and again marketers look to the competition to copy what they’re doing instead of learning what the users, customers and MQL actually need.

 

So, can SEO and AI be used together? Yes. When AI is used as an assistant it can weave personas, tone and research into your customer data, user research and MQL needs. This enables marketers to then spend their time analyzing user behavior and patterns across the web with tools and sleuthing. The result is a big mess of user data, ideas and themes. AI can be pretty good at incorporating keywords, semantic analysis and content structure to support the data, ideas, and themes, but a human has to create the first version.


How to use AI in SEO today


All technical, design and content optimization begins and ends with the user – so regardless of the type of SEO you’re doing your number one goal is your user’s needs. There’s no trick, no secret sauce. That means that AI is an instrument, and here’s how to use it:

 

  • Applying user research

  • Implementing your (human-created) structures

  • Integrating keywords into well-written content

  • Repurposing long-form content

 

Overall, the integration of AI in SEO represents a problem just as much as it does opportunity. By leveraging AI we’re taking on a high responsibility of leading the technology, ever reminding us to do user research and to never skimp on the precise nature of our user’s needs. But if we are responsible and managing the tools well then we have a real paradigm shift in how marketers approach research, implementation and growth.


AI in digital marketing


Thanks to generative AI, digital marketing folks have more access to user data and behavior. Big Data and software consuming large data sets to produce insights isn’t a new concept, but giving direct access to marketers is. When paired with timeless concepts of personas and personalization, AI can actually make a meaningful impact. Here are a couple of ways:


Personalization


When a technological assistant handles the vast majority of the grunt work, marketers can focus on personalizing first-touch messages (social media responses) and remarketing efforts (landing pages). And when I say personalize – I don’t mean have AI do it for you.. No, I mean an actual human creates the first touch / remarketing content.


Diversify content portfolio


You know all of the different types of content out there, and if you’re creating content well you’re focused on one at a time doing the design thinking all the way through to inception and launch. Instead of crafting an expert prompt to create a new type of content, you can phone-an-AI-friend to repurpose your most in-depth content into shorter-form content and diversify your content portfolio. It works because you’re providing AI all of the context and content that it needs – it won’t be guessing its way through a Google search and your expertise is woven into the content, leaving you in the driver’s seat to edit and publish.


How are marketers responding to AI?


Marketers everywhere are talking about increasing efficiency and scale with AI – and it is a cautionary tale. Thus far, I’ve yet to see a real “response” to AI by marketers, just mass adoption. Yes, we’ve far exceeded critical mass – and also yes, most folks are doing the same thing. It looks something like this: Prompt AI to do something, edit some, then copy–paste–publish. Whew… What a mess that produces.


What I’m driving at here is that I’ve seen a whole lot of adoption and copy pasta but very little actual response to Ai. I started asking this question in December 2023, and have found very few people who have actually responded to the market conditions. Sure, people have decided to either use or not use the technology but for those that have chosen to use it I’ve yet to see a response or a decidedly different application of generative AI. 

 

We’ve seen whole domains lost, customer bases enraged, and people left confused. Why? Because we are humans and we want to work with humans. The entire intended purpose of (responsible) SEO is to create for the user, publish in consideration of their needs, and deliver on your promises. And if we’re not writing well with AI (using it as an assistant rather than a driver) then we are not thinking about our users – and thus we are not delivering what they need.


The inefficient market created by AI


More than ever we’re a follow-the-leader society, simply because we’re able to share (at scale) what is working for us. People are creating content – and sharing their wins with the world. That’s fine – and probably good process until you realize that you’re sharing untested methodologies and using a technology that can undermine some of the most important first principles in marketing.

 

That means you have an opportunity here and now to use AI differently than the competition. Not use their tactics, but rather use the technology of generative AI in a more responsible, managed way. That’ll look different for every company, agency and department – so I won’t begin to share just how you should use it. But if you want to disrupt these market conditions and win with AI then your task is just as much a matter of unique creation and implementation as it is avoiding the not so obvious traps hidden in the technology.


Generative AI: A marketer’s dream, maybe?


People do business with people that they like – and AI is only fueling that old adage. No one wants to do business with a robot. That means the inefficiency of the marketplace that you can act on is to learn how to keep AI in its role as an assistant, with humans in the lead. If you’re able to identify when, where and how to use AI then you’ll have taken the first responsible step in using it well.

 

And just how do we do the next step? A singular prompt expecting a usable output won’t suffice. When we work with generative AI we have to nurture the conversation – a beginning prompt, some context, and continuing on with the conversation. It’s this back-and-forth that creates what some call models. Some models or prompts, depending on their nature, can be repeated and copied/pasted, but most cannot. You can even tell the technology that you need an assist in doing a task, which I find more useful than asking it to create.

 

Taking this to still another, maybe deeper level has great value too. Incorporating the metadata – the core pieces to your business or product that never change. You can bake things like tone, brand guidelines, mission, etc. into your models. You can even instruct AI what not to do, like using some of those words and phrases it loves so much.

 

So whether or not AI is the future of your company and marketing is entirely dependent on how you use it and the questions you ask before using it. You can either find the honey or be stung by the bee.


Learn more about Will Soprano on LinkedIn and his personal blog.


Will Soprano Brainz Magazine
 

Will Soprano, Executive Contributor Brainz Magazine

From writer to all things dev & tech Will has spent a lifetime trying, failing, learning and growing. In nurturing his ability as a writer he found that he had a knack for supporting software developers & connecting orgs across functions. As his career arc was hitting its first peak he found himself broken physically, emotionally, and professionally. That was the beginning of his personal growth. After years of trial and error he finally realized that sobriety was the answer. With nearly 4 years sober, he's not just a new person socially but professionally as well. The mental health community and his peers professionally have responded to his willingness to serve and authenticity.

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