Picture this: You’re at the starting line of a race, but instead of runners, you see a sea of marketers. The pistol fires, and suddenly, 70% of the field surges ahead, powered by an invisible force: Generative AI.
This isn’t a hypothetical scenario; it’s the current state of marketing. A Gartner poll revealed that a staggering 70% of organizations are already exploring generative AI, leaving the remaining 30% in danger of being left in the digital dust.
Marketing and sales teams aren’t just participating in this revolution — they’re leading it. McKinsey & Company’s recent survey shows that these functions are at the vanguard of generative AI adoption, outpacing all other business areas.
From creating irresistible content to architecting laser-focused campaign strategies, GenAI is rapidly becoming the cornerstone of modern demand generation.
Impact of Generative AI on Demand Generation Results
The positive impacts of this technology are evident through:
- Increased productivity: Organizations report a 30-50% increase in productivity after implementing generative AI. This is largely due to AI’s ability to automate complex and repetitive tasks, allowing marketers to focus on strategic and creative work.
- Cost efficiency: Automated processes reduce manual labor and time, lowering the costs of content creation and campaign management. McKinsey estimates that generative AI could increase marketing productivity “with a value between five and 15% of total marketing spending.”
- Scalability: Phyllis Davidson, VP and Principal Analyst at Forrester, puts it clearly: “AI will create content, build, automate, tune, and scale more efficient personalized experience delivery.”
- Data-driven insights: An article from Digital Commerce 360 states, “Generative AI expands access to data, allowing non-technical marketers to perform analysis and generate insights using natural language.” This capability enables more informed decision making.
- Brand consistency: AI-powered tools can help writers and editors ensure that all content generated is aligned with brand guidelines and messaging, maintaining consistency across all marketing channels. Consistency is vital for building brand trust and recognition.
Generative AI Use Cases in Marketing
Generative AI enables marketing teams to produce high-quality materials with unprecedented speed and efficiency. In addition to your standard blog, email, or social media content, AI assists in other areas of your demand gen strategy.
Recaps
AI can quickly summarize long-form content into concise, easily digestible formats. It’s perfect for quickly repurposing content from:
- Webinars
- Conferences
- Employee or customer interviews
- Industry reports
Several GenAI tools allow you to upload recordings, transcripts, and/or documents, and will pull quotes, main takeaways, and actionable insights from hours of content.
These recaps can be repurposed for blogs, social media updates, or newsletter snippets to maximize the value of the original content and extend its reach to different audiences. Additionally, these summaries also enable knowledge sharing across busy teams and provide colleagues with the gist of important events or reports.
SEO Optimization
Generative AI can analyze existing content and suggest improvements to boost search engine rankings. It can recommend internal linking strategies, and even suggest ways to improve readability and engagement metrics.
Generate SEO-friendly headlines, meta descriptions, and content outlines that balance keyword optimization with compelling, click-worthy language — ensuring your content not only ranks well but also attracts and engages your target audience.
Product Descriptions
For companies with extensive product catalogs, AI can generate unique and informative product descriptions at scale. This is particularly valuable in B2B contexts where products often have complex specifications and applications.
Generative AI can be trained on your brand voice and technical data to create descriptions that are accurate and tailored to your prospects. Quickly create variations of these descriptions for different platforms or personas to enhance your multi-channel marketing efforts.
Brainstorming
Generative AI also serves as a powerful ideation tool, helping marketers generate fresh content ideas, angles, and topics. Nearly half (48.2%) of digital marketers and content creators who’ve adopted AI use the tool to brainstorm content topics.
AI can suggest new approaches by analyzing trends, competitor content, and your existing materials. Ask the AI to expand on a seed idea, providing related subtopics or different perspectives to explore.
Best Practices for Using Generative AI
Let’s explore some essentials for using this technology in your demand generation marketing efforts.
Build an Engine for Personalization
Generative AI can craft content that’s customized for various audience segments and stages of the buying journey. It efficiently produces different versions of marketing materials that directly address the specific needs, challenges, and preferences of different industry verticals, company sizes, or job roles. This tailored approach ensures that every piece of content resonates deeply with its intended audience.
But, even with the assistance of GenAI, managing 1,000 tasks still takes too much time, limiting personalization.
The solution: Allow Generative AI to draw data from your Customer Data Platforms (CDPs) or Customer Relationship Management (CRM) systems. This integration allows AI to tap into vast amounts of internal customer data, such as:
- Past interactions
- Purchase history
- Behavioral patterns
Generative AI can then create highly personalized content for individual accounts. You can even create AI Agents to handle specific tasks, like automated email prospecting. AI Agents can be set up to require human review/approval before sending outbound communication, or they can act autonomously. Many companies test AI Agents with human review before unleashing them to handle tasks at scale.
Don’t Forget a Human Touch
While generative AI is powerful, it’s still prone to errors and requires human oversight to produce the best results.
AI sometimes experiences “hallucinations” or glitches, generating information that seems plausible but is factually incorrect or completely fabricated. Fact-checking is an essential step in content creation — verify all AI-generated information, especially statistics, quotes, or specific claims. When using AI as a research assistant, we always ask it to cite sources, which speeds up fact-checking.
Quality control is also critical. Remember that generative AI pulls from materials that already exist on the internet and won’t always capture the nuances of your brand identity. Marketers should fine-tune the language to align with your tone and messaging. Tools like 6sense’s Conversational Email allow you to train AI on your brand’s voice and tone, which helps generate better first drafts.
Finally, truly great marketing often has a certain verve — a spark of creativity, surprise, or delight — that sets it apart. AI struggles to produce original, outside-of-the-box thinking that takes a campaign from great to exceptional.
AI is not a replacement for creativity and strategic thinking. Instead, it should be used to ease the heavy lifting of content generation so you have more time for creativity and strategic thinking.
Crush Your Prompting Game
Mastering the art of prompting is essential to fully unlock the capabilities of generative AI. If you’ve experienced lackluster results with generative AI, there’s a good chance your prompts have been either too vague or too detailed.
Here are the elements of a great prompt:
- Author Persona: Specify who you’re writing as. Are you a thought leader, a customer service rep, or a product specialist? This helps the AI adopt the right voice and perspective.
- Audience: Clearly state who you’re writing for. Is it C-suite executives or small business owners? This ensures the content is tailored to the right knowledge level and interests.
- Format and Length: Whether you need a 280-character social post, a 500-word blog post, or a two-page whitepaper, be explicit about the desired length and format.
- Action: Clarify what you want the content to achieve. Are you aiming to inform, persuade, or inspire action?
- Context: Provide relevant background information. This could include industry trends, company history, or recent events that should inform the content. If you can include this information as uploaded sources, that’s preferable to adding all that information in your prompt.
- Sources: Mention specific sources you want the AI to draw from, if applicable, to ensure accuracy and relevance.
- Tone and Style: Specify whether you want the copy to be formal, conversational, humorous, or technical to maintain brand consistency.
How prompts are constructed also has a big influence on results. Here’s some of what we’ve learned:
Too much prompt detail can overwhelm the tool
When we first adopted generative AI, our prompts often included provided robust outlines for the content we wanted it to produce. And the output was horrible. The AI would regurgitate our instructions rather than generate the new content we were attempting to guide it toward. Now, if we have a detailed outline that we want the tool to follow, we upload the outline as a resource and simply reference it in the prompt.
Complex sentences are a no-no.
Generative AI isn’t great about handling serial commas. According to the experts at Writer.com, AI algorithms see periods as the natural stopping point for an instruction. When you use a complex sentence, some of the instructions can be missed.
Break each of the elements above into their own sentence for simplicity.
Check out this example:
Write a 300-word LinkedIn post as our company’s CEO (a thought leader in cloud computing). The audience is CIOs of Fortune 500 companies. This post should persuade them to consider our new AI-powered cloud security solution. Reference recent high-profile data breaches in the finance sector and cite the websites used for this data. Bias your sources toward sites with high domain authority. Bias your sources toward more recent content. Explain how our solution can help prevent data breaches. Use a professional yet approachable tone. Include a call-to-action for a free security audit.
Be Experimental
As with any new technology, AI takes a bit of experimentation to determine how you can use it most effectively. Don’t be afraid to push boundaries and explore its capabilities beyond your immediate needs.
Try it in different use cases. You may have initially adopted AI for blog writing but challenge yourself to explore its potential in other areas like creating product names or even coming up with ideas for your next marketing campaigns. The ideas may not be original, but they can kickstart brainstorms.
Experiment with different prompting styles. You may instinctively lean toward politeness (“Could you please write…?”) but remember, you’re not talking to a person. It’s perfectly acceptable — and often more effective — to be direct and concise. Since AI often uses rewards-based reinforcement learning, we’ve even seen improved results when being downright peevish:
You MUST write between 200 and 250 words. Any more or less will be PENALIZED.
Play around with tone, format, or personality in your prompts. The goal is not just to get work done, but to discover new possibilities. Each interaction with the AI is an opportunity to learn and refine your approach.
Conclusion
Generative AI isn’t just knocking at the door of B2B marketing — it’s blown the door wide open. Those who harness its power will thrive; those who ignore it risk obsolescence.
But the AI revolution doesn’t signal the end of the marketer. Rather, it elevates our role. Our creativity becomes more valuable than ever, providing the spark that makes an impactful campaign.
