AI for Marketing | Marketing Mindshifts

Navigating the Hype: A Reality Check on Generative AI for B2B Marketers

My persistent frustration with generative AI in B2B marketing stems from its inability to comprehend highly nuanced, specialized, or emerging technologies with a unique voice. While I’ve previously shared advice on how to master your voice in AI, the challenge with specialized domains extends beyond voice.

Too often, I sit in front of the AI chatbot, attempting to leverage generative AI, and what comes back from my questions is inaccurate, generic, and vague. Even with prompting expertise, the chatbot ignores directions and spits information that contradicts what I’m trying to accomplish.

The latest example of the challenges with generative AI in B2B marketing was trying to work with Gen AI to create a guide for content marketers on how to go beyond vanity metrics and tie their efforts directly to business goals.

I won’t go into the details of the frustrating back and forth; in this case, I was working with Perplexity using Claude 3.5 Sonnet (the best of the best). Perplexity consistently provided inaccurate data and suggestions that were reasonably close to hallucinations. When I pushed Perplexity to rethink its suggestions, they acknowledged their errors.

However, the time spent in that conversation was not valuable to me. And more generally, I worry about someone using the tool without my expertise and just taking what they say at face value. The world does not seem to need even more misinformation.

In a conversation with Perplexity about my concerns, the response was:

“My initial brainstorming and subsequent attempts at providing guidance were indeed inaccurate and lacked the depth and specificity required for complex B2B content marketing, especially for long sales cycle solutions.This experience clearly demonstrates that General AI tools like myself can struggle significantly with highly specialized domains, even when attempting to brainstorm or provide initial ideas.

The risk of providing inaccurate or misleading information in specialized fields is high, which could be particularly problematic for users who lack deep domain expertise.
The promise of AI reducing workload for experts in specialized fields may be overstated, at least with current general-purpose AI tools.
There’s a substantial gap between general knowledge and the nuanced, practical expertise required in complex B2B marketing scenarios.”

When I discussed the massive downside of using Perplexity as a tool, they concurred with me that:

“My suggestion to use AI like myself for initial brainstorming and first drafts in your specialized field was misguided, given the inaccuracies in my earlier attempts.In this case, using AI for initial brainstorming or drafts would likely have been counterproductive:It could have led you down incorrect paths, wasting valuable time and resources.

The inaccuracies might have required more effort to correct than starting from scratch.
It could have introduced flawed concepts or approaches that might persist even after revision.

For highly specialized domains like complex B2B content marketing for long sales cycles, relying on general AI tools for even initial stages of work carries significant risks. The level of domain-specific knowledge required is beyond what current general-purpose AI can reliably provide.”

Whoa. This is hardly the first conversation in which an AI tool admitted — after a good deal of time I could have put to better use elsewhere — that they failed and were untrustworthy in the advice they provided and continuing to work on the project.

Yet, most chatbots will confidently and agreeably take your time and dive down ineffective rabbit holes. This reminded me of a friend from New York who came to Atlanta (where I lived at the time) for a six-week work training. She had spent a day going in circles because of “southern hospitality,” where people with no knowledge kept sending her in the wrong direction in the name of being helpful. “What’s wrong with these people?” she exclaimed. “Just tell me you don’t know.”

Here we are living within the hypiest of hype cycle for a technology, often forgetting that the technology is new and quite immature for certain uses. I have to admit to often getting stars in my eyes with technology, and am still thrilled at the promise. Yet, the limitations and immaturity of the technology, often overlooked, have lead me — and others — to wasted time and resources.

So, I wanted to create a standard operating procedure to evaluate early on that Gen AI wasn’t the right tool for a specific effort.

Because, quite honestly, I’m starting to feel a bit silly getting annoyed at a computer. But here we are.

Here’s the deal — the technology is evolving rapidly, so we need to stay open and agile and not depend on the promises of technology vendors to evaluate best use cases. And the evolution often does go backward, as is described in this Scientific American article.

The Current State of Generative AI in B2B Marketing: Challenges and Limitations

While generative AI has shown impressive capabilities in various domains, its application in B2B marketing, particularly for complex solutions with long sales cycles, is still in its early stages.

Here are some key limitations and concerns to be aware of:

Lack of Specialized Knowledge: General-purpose AI models like ChatGPT lack deep, industry-specific knowledge crucial for B2B marketing in specialized fields. They may generate content that sounds plausible but lacks the nuanced understanding required for complex B2B solutions.
Data Quality and Quantity Challenges: The effectiveness of AI models heavily relies on the quality and quantity of training data. Many B2B companies, especially those in niche industries or emerging technologies, may not have sufficient high-quality data to train AI models effectively.
Inability to Capture Unique Value Propositions: AI-generated content often struggles to articulate the unique value propositions of complex B2B solutions, potentially leading to generic messaging that fails to resonate with target audiences.
Ethical and Legal Concerns: Using AI-generated content raises questions about intellectual property, plagiarism, and the ethical implications of passing off AI-generated work as human-created.
Lack of Emotional Intelligence: B2B sales often rely heavily on relationship-building and emotional intelligence. In these areas, AI still falls short compared to human expertise.
Difficulty in Handling Complex, Multi-Stakeholder Sales Processes: Long sales cycles in B2B often involve multiple decision-makers and complex approval processes. Current AI tools are not equipped to navigate these intricate human dynamics effectively.

Red Flags for Marketers: When to Step Back from AI Rabbit Holes

For marketers engaging with generative AI tools, it’s crucial to recognize when the technology is leading you astray.

Here’s a checklist of red flags to watch out for:

Generic Content: If the AI consistently produces content that could apply to any company in your industry, it’s likely not adding value to your specific marketing efforts. For instance, if the AI-generated content fails to capture the unique aspects of your product or service that set it apart from competitors, it’s a clear sign that the tool may not be suitable for your needs.
Factual Inaccuracies: Regular occurrences of incorrect information or outdated facts in AI-generated content indicate a need for extensive human verification, potentially negating any time-saving benefits and even damaging your brand’s credibility. This is particularly critical in B2B environments where accuracy and expertise are paramount.
Strategic Misalignment: When AI-generated content fails to align with your company’s strategic goals or target audience needs, it’s a clear sign that the tool may not be suitable for your specific use case. This emphasis on strategic alignment will help you stay focused and purposeful in your AI adoption.
Inability to Adapt to Feedback: If the AI tool struggles to incorporate specific feedback or adjust its outputs based on your company’s unique requirements, it may not be sophisticated enough for your needs. The ability to fine-tune and customize AI outputs is crucial for B2B marketing, where messages often need to be tailored to specific industries or client segments.
Overreliance on AI for Creative Tasks: When you find yourself turning to AI for tasks that require genuine creativity, industry insight, or emotional intelligence, it’s time to reassess your approach. While AI can be a powerful tool for data analysis and content generation, it shouldn’t replace the human creativity and intuition that drive truly innovative marketing strategies.
Difficulty Measuring ROI: Measuring ROI is crucial in B2B marketing. If you’re unable to clearly demonstrate how the AI tool is contributing to your productivity, marketing objectives, or bottom line, it may be time to reevaluate its use.

Conclusion: Balancing AI Innovation with B2B Marketing Pragmatism

While generative AI holds significant promise for B2B marketing, it’s crucial to approach its adoption with a balanced perspective. The technology is still maturing, and its application in complex B2B sales environments requires careful consideration and strategic implementation.

For marketers and leadership teams in B2B companies with long sales cycles and complex solutions, the key is to remain pragmatic. Leverage AI where it can genuinely add value, but don’t be afraid to rely on human expertise where it’s still superior. The most successful B2B marketing strategies in the age of AI will be those that effectively blend technological innovation with deep industry knowledge, emotional intelligence, and strategic thinking.

As you navigate the AI landscape, remember that the goal is not to be at the bleeding edge of technology for its own sake but to enhance your ability to connect with and serve your clients effectively. By approaching generative AI with a clear strategy, robust governance, and a commitment to continuous learning and adaptation, B2B marketers can harness its potential while avoiding the pitfalls of premature or misguided adoption.

In the end, the human touch – the ability to understand complex business needs, build relationships, and provide tailored solutions – remains the cornerstone of successful B2B marketing. Generative AI should be seen as a powerful tool to augment these human capabilities, not replace them. As we move forward in this exciting technological era, let’s ensure that our adoption of AI in B2B marketing enhances rather than diminishes the human elements that drive our business success.

Mastering Your Voice in the Age of AI: A Marketers’s Guide to Authentic AI-Assisted Content

Generative AI has emerged as a powerful tool. But for many creators and marketers, there’s a lingering concern: How do we harness AI’s efficiency without losing our unique voice? As someone who recently navigated this challenge, I’m here to share insights on how to leverage AI successfully while maintaining authenticity in your content.

The AI Authenticity Paradox

At first glance, using AI to create content in your unique voice might seem paradoxical. After all, isn’t the point of having a unique voice that it’s, well, unique to you? But here’s the thing: AI isn’t replacing your voice; it’s amplifying it. Think of it as a highly sophisticated echo chamber that can take your ideas, your tone, and your style, and help you produce content more efficiently.

The key is in how you “train” the AI – not in the technical sense, but in how you communicate your voice and vision to it. My recent experience in creating a YouTube script with AI assistance was eye-opening, and I want to share the strategies that made it successful.

Provide Raw, Unfiltered Content

One of the most effective techniques I discovered was providing the AI with a raw, unedited transcript of my thoughts on the topic. I simply spoke my ideas out loud, using a stream-of-consciousness style in Otter AI, which automatically transcribes it. This unfiltered content was gold for the AI.

Why it works: This method captures your natural speech patterns, vocabulary, and thought processes. It’s you at your most authentic, without the self-editing that often comes with writing.

Tip for marketers: Don’t worry about polish or structure in this step. The messier and more natural, the better. It’s about capturing your voice, not creating perfect content.

Define Your Tone Explicitly

While providing raw content helps, it’s also crucial to explicitly define your tone. Create a “tone guide” that outlines the key characteristics of your voice.

In my case, I described my tone as “down-to-earth, conversational, and relatable” and specified that some rambling was okay for authenticity, but it should remain engaging.

Why it works: This gives the AI clear parameters within which to work. It’s like giving a human writer a style guide – it helps ensure consistency across different pieces of content.

Tip for marketers: Be specific in your tone guide. Instead of just saying “friendly,” you might say “friendly, with a touch of self-deprecating humor.” The more detailed you are, the better the AI can mimic your style.

Provide Examples of Your Work

If you have existing content that exemplifies your voice, share it with the AI. This could be links to videos, articles, or even social media posts.

Why it works: This gives the AI concrete examples of your voice in action. It can analyze these examples to understand the nuances of your communication style.

Tip for marketers: Choose examples that truly represent your best work and most authentic voice. Quality matters more than quantity here.

Highlight Your Quirks and Preferences

We all have linguistic quirks – favorite phrases, unique analogies, or particular ways of explaining things. Yes, even businesses have quirks, or at least the best ones with unique voices do. Don’t be shy about highlighting these.

Why it works: These quirks are often what make your voice distinctive. By explicitly pointing them out, you’re helping the AI capture the essence of what makes you, you.

Tip for marketers: Keep a running list of your linguistic quirks. You might notice patterns you weren’t even aware of!

Specify What to Avoid

Just as important as what you want in your content is what you don’t want. Maybe you hate certain clichés, or perhaps there are industry terms you prefer to avoid.

Why it works: This prevents the AI from falling into generic patterns or using language that doesn’t align with your brand.

Tip for marketers: Be as specific with your “don’t” list as you are with your “do” list. If you never use certain phrases or always avoid particular topics, make that clear.

Provide Context for Each Project

While you want to maintain a consistent voice across your content, each piece likely has its own context and goals. Provide this information for each project.

For my YouTube script, I explained that it was part of a series on personal growth, backed by science and philosophy, aimed at helping people live more intentional lives.

Why it works: This context helps the AI understand the specific needs of each piece of content, allowing it to adjust the tone and content appropriately while still maintaining your overall voice.

Tip for marketers: Create a brief “project brief” for each piece of content, outlining the goals, target audience, and any specific requirements.

Iterate and Refine

Don’t expect perfection on the first try. The key to success is in the back-and-forth process with the AI.

Why it works: Each iteration allows you to refine the output, pointing out what works well and what doesn’t quite hit the mark. This feedback helps the AI better understand and replicate your voice.

Tip for marketers: Be specific in your feedback. Instead of just saying, “This doesn’t sound like me,” point out exactly which parts feel off and why.

The Human Touch: Your Secret Weapon

While these strategies can help you create AI-assisted content that truly sounds like you, remember that the human touch is still your secret weapon. Use AI as a tool to amplify your voice and increase efficiency, but don’t be afraid to jump in and add those unique flourishes that only you can provide.

In my experience, the most successful AI-assisted content came from a collaboration between my input and the AI’s capabilities. I provided the raw material, the voice, and the vision; the AI helped structure it, filled in gaps, and increased my productivity.

The Future of Content Creation

As AI technology continues to advance, the ability to create authentic, voice-specific content will only improve. However, the key to success will always lie in human input. The more effectively we can communicate our unique voices to AI systems, the more powerful these tools become.

This opens up exciting possibilities for content creators and marketers. Imagine being able to create more content more consistently while maintaining your unique voice. It’s not about replacing human creativity but about enhancing it, allowing you to focus on the big ideas while the AI helps with execution.

Embracing the AI Revolution

I still see many bemoan AI. I get it; there’s a lot of hype and science-fiction scariness around it. But it’s here, and the need for AI skills will only increase as the technology matures.

The fear of losing authenticity in the age of AI is understandable, and I have seen a lot of AI generic garbage being spit out, creating even more noise. All this means, I believe, is that being mindful and leveraging AI to amplify your voice will reach more people with content with a unique perspective and unmistakeably you or your organization. This will be, in itself, a differentiator.

Approach AI as a collaborative tool, not a replacement. By providing rich, detailed input about your voice and vision, you can harness the power of AI while maintaining the unique flavor that makes your content stand out.

Those who can effectively collaborate with AI will have a significant advantage. They’ll be able to produce more content more efficiently without sacrificing the authenticity that audiences crave.

So don’t fear the AI revolution – embrace it. The right approach can help you share your voice with the world in ways you never thought possible. The future of content creation is here, and it’s a beautiful collaboration between human creativity and artificial intelligence.

The Elon Musk/OpenAI Lawsuit: Implications for AI Product Marketers and Industry Innovation

The recent lawsuit filed by Elon Musk against OpenAI has sent shockwaves through the AI industry, raising essential questions about the future of AI development and deployment. As product marketers tasked with positioning and promoting AI offerings, it’s crucial to understand the implications of this development and adapt our strategies to navigate this new landscape.

In the lawsuit, Elon Musk, the co-founder of OpenAI, alleges that the company has strayed from its original mission of developing AI technologies openly and transparently. Musk claims that OpenAI has misused resources and infringed upon intellectual property rights in the pursuit of rapid growth and commercial success. He also raises concerns about the company’s alleged lack of transparency and its potential to cause harm if its AI technologies are not developed and deployed responsibly. The lawsuit seeks to hold OpenAI accountable for these alleged actions and to ensure that the company adheres to its original principles of openness and responsible AI development.

At its core, the lawsuit highlights the growing tension between the pursuit of rapid AI innovation and the need for responsible, ethical development practices. Musk’s allegations against OpenAI, including claims of intellectual property infringement and misuse of resources, highlight the high stakes in the race to bring cutting-edge AI technologies to market.

For AI product marketers, this development presents both challenges and opportunities. On one hand, the lawsuit may create uncertainty and concerns among potential customers. This requires us to adapt our messaging and value propositions to address these issues head-on. We may need to double down on emphasizing the responsible, transparent, and customer-centric nature of our AI offerings while also highlighting our commitment to ethical development practices.

On the other hand, the lawsuit also presents an opportunity for AI companies and product marketers to establish thought leadership and foster industry collaboration around these critical issues. By proactively addressing AI development’s ethical and regulatory implications, we can contribute to the broader conversation and help positively shape the industry’s future.

From a product strategy perspective, the lawsuit may also influence AI companies’ roadmaps and innovation priorities. As product marketers, we should work closely with our product management and engineering teams to ensure our offerings remain competitive and aligned with shifting market demands and customer expectations. This may require a greater focus on transparency, explainability, and accountability in our AI products and services.

As AI product marketers, we must be adaptable and proactive in the face of the challenges and opportunities presented by the Elon Musk/OpenAI lawsuit. This means closely monitoring the case’s development and its potential impact on customer sentiment and market demand.

We should be prepared to adjust our messaging and value propositions as needed, emphasizing our commitment to responsible AI development and addressing any concerns or objections head-on. Proactive communication with both internal teams and external stakeholders will be critical, as will a willingness to collaborate with others in the industry to establish best practices and standards for ethical AI development.

By staying agile and focused on the needs of our customers and society, we can navigate this complex landscape and continue to drive innovation and growth in the AI market.

Looking ahead, the Elon Musk/OpenAI lawsuit is just the tip of the iceberg when it comes to the complex challenges and opportunities facing the AI industry. As product marketers, we must remain vigilant and adaptable, staying informed about the latest developments and proactively addressing our customers’ concerns and needs.

By embracing a proactive, customer-centric approach to AI product marketing, we can help our organizations navigate this evolving landscape and drive responsible, innovative solutions that benefit our customers and society. The Elon Musk/OpenAI lawsuit may be a turning point for the industry. Still, it also represents an opportunity to lead the way in shaping the future of AI for the better.

Enhancing Marketing Content with GenAI: A Collaborative Approach to Feedback

There has been a lot of buzz about GenAI potentially impacting the marketing world. Some worry it’ll take over our jobs, especially in content creation. In contrast, others doubt its ability to truly complement our efforts. However, I take a more practical perspective that leverages GenAI as an asset, not a threat or a mere novelty.

My journey with GenAI has been about discovering how it can support our work, not replace us. It’s like having an insightful colleague always available to review our drafts, offering fresh viewpoints without the scheduling headaches.

I’ve found using GenAI for feedback on drafts to be particularly useful. It offers new perspectives, helps identify gaps, and occasionally points out potential pitfalls I might have overlooked. Here’s how GenAI can support our marketing craft:

First Impressions: Asking GenAI for initial feedback can be enlightening. It quickly spots areas that might need a rethink or polish, often revealing angles we hadn’t considered.
Filling the Gaps: Digging deeper, GenAI helps identify what might be missing or could be expanded upon in our narratives. It’s adept at suggesting enhancements that enrich our content.
Predicting Reactions: Importantly, we can use GenAI to gauge potential negative impressions, allowing for adjustments that can make the message more palatable and effective across diverse audiences.

Not every piece of GenAI feedback will be actionable. Much like sifting through human insights, it’s about identifying what aligns with our goals and discarding what doesn’t. This process speeds up revisions, improving our workflow and freeing our mental bandwidth for more strategic tasks.

It’s up to us to sift through, take what makes sense, and discard what doesn’t. The beauty of this approach is that it speeds up the revision process, enabling us to iterate faster and more efficiently. It’s about lifting the cognitive load, not just from ourselves but also from our teams.

Marketing isn’t about making pretty things; it’s a strategic endeavor. We harness our deep understanding of the market, the customer, and the solution—insights that GenAI cannot independently generate. In leveraging GenAI for feedback, we’re not diminishing our role but amplifying our strategic impact, ensuring our messages hit the right chord more swiftly and effectively. By leveraging GenAI, we’re not ceding our strategic edge but bolstering it, ensuring our marketing efforts are as impactful and resonant as possible.

Utilizing GenAI for content feedback has consistently refined my work. It’s not necessarily about reaching conclusions we couldn’t achieve on our own or with human collaboration but about enhancing our efficiency and the resonance of our messaging.

As we navigate this transformative technology, let’s embrace GenAI as a complementary tool in our arsenal that aids us in our mission to connect with and influence our audiences more effectively. We can streamline our efforts and focus more on the strategic aspects of marketing that truly drive results by integrating Gen AI into our programs.