How Demand Gen Helped Drive Real B2B Growth With AI 

The Hidden Cost of AI Adoption: Indecision 

As more marketing teams start using AI, we’ve seen a common trend among the organisations we work with: indecision. 

When AI comes into play, it can feel like anything is possible. Teams see workflows they could automate, roles they might change, and channels they could reinvent. 

Instead of finding clarity, teams often end up overwhelmed. They try out lots of ideas because they’re not sure what will really make a difference. Activity goes up, but focus drops. Without strong guidance, too many choices and powerful tools can quickly lead to chaos. 

Why Focus Wins on AI-Driven Marketing 

Successful teams do things differently. They narrow their focus, set clear time limits for decisions, and make necessary trade-offs. Rather than trying to fix everything at once, they work on one system until it delivers real results, then move on. 

Marketing is already a complex, sprawling discipline. Applying AI across every channel and tactic simultaneously only amplifies that complexity. The only model we’ve seen work consistently is focused, time-boxed execution, short cycles where teams choose a single system, build it properly, and ignore distractions until it’s delivering value. This approach also protects against the constant churn of new tools and models that threaten to derail long-term plans. 

Redesigning Demand Generation  

This mindset shaped how we approached our work with a well-known retail brand.  

Rather than simply layering AI tools on top of their existing efforts or “trying ChatGPT,” we rethought their demand generation strategy from the ground up. The objective wasn’t to use AI for its own sake, but to apply it deliberately, combining advanced AI-driven audience modelling with clear, human-led positioning.  

Teaching Meta Who the Real Buyer Is 

We chose to go deep on a single channel: Meta Ads. Using AI tools, we built custom conversion events designed to teach Meta exactly who this brand was trying to reach. These events went beyond surface-level engagement signals and instead optimised for behaviours that indicated genuine buying

intent. In effect, we gave the algorithm clearer instructions about what success looked like. 

The results were meaningful and measurable: 

• Form fills increased by 90% 

• Qualified leads increased by 70% 

• Leads converting into customers increased by 60% 

These improvements translated into a significantly stronger pipeline and far more efficient growth without adding new channels or unnecessary complexity. 

This outcome wasn’t driven solely by automation. It came from pairing AI’s ability to analyse and model behaviour at scale with disciplined human judgment around messaging, positioning, and prioritisation. By resisting the temptation to experiment everywhere, we were able to build one demand engine that actually worked. 

The Real Role of AI in Demand Generation 

The takeaway is straightforward: AI doesn’t create demand on its own. Demand Gen does. AI is a powerful multiplier, but only when it’s applied with focus and intent. Used indiscriminately, it adds noise. Used strategically, it accelerates results. 

For our client, clarity, not chaos, was the advantage. By committing to a focused system and letting both humans and machines do what they do best, they were able to turn AI from a distraction into a growth driver. 

 

Leading Sales and Marketing in the AI Era

A New Go-to-Market Playbook for B2B Growth

B2B sales and marketing are entering their most significant transformation since the rise of digital. AI is no longer an efficiency layer or an experimental add-on; it’s becoming the primary interface between buyers and brands.

What’s changing isn’t just how teams execute, but where demand is created, how decisions are influenced, and who controls discovery.

Leading analysts are already clear on this direction. In its recent work on AI agents in B2B sales, Boston Consulting Group outlines a future where AI doesn’t just support sales teams – it actively runs workflows, orchestrates engagement, and connects signals across the revenue engine. The implication is clear: B2B leaders must rethink their entire go-to-market model, not just adopt new tools.

At DemandGen, we see this shift every day. The brands winning in this new environment are those redesigning their strategies around AI-mediated buyer behaviour, not legacy funnels.

 

The Buyer Has Moved Beyond Google

For years, B2B demand generation was built on a simple assumption: buyers search, click, compare, and convert. That assumption no longer holds.

Today, buyers increasingly start their journey inside AI systems – asking tools like ChatGPT to summarise vendors, recommend solutions, or explain complex categories. These systems don’t present ten links; they present one synthesised answer.

This creates a fundamental shift:

• Discovery is no longer driven by rankings, but by AI references
• Traffic is no longer the primary signal of influence
• Brand perception is shaped before a buyer ever reaches your website

In this world, traditional SEO alone is not enough

How leading teams are responding

Forward-looking B2B organisations are actively optimising for AI visibility, not just search visibility. At DemandGen, we support this shift using GeoScore – a platform that measures how often and how prominently brands appear in AI-generated answers across commercially relevant prompts.

Instead of asking “Are we ranking?”, the better question becomes:
“When buyers ask AI about our category, are we part of the answer?”

This is the new front line of demand generation.

 

AI Agents Are Becoming the Revenue Workforce

One of the most important ideas emerging from analyst research is the rise of AI agents – systems that don’t just automate tasks, but take ownership of outcomes.

BCG describes a future in which AI agents qualify leads, personalise outreach, recommend next actions, and continuously optimise performance throughout the sales cycle. In practice, this is already happening.

But the highest-performing organisations aren’t handing control to AI – they’re designing workflows where AI augments human judgement.

From tools to systems

At DemandGen, we architect AI-enabled revenue workflows that connect:

• Intent and behaviour signals
• Automated prospecting and outreach
• Human-led sales engagement

Platforms like Lemlist, CRM systems, and purpose-built AI agents are combined to accelerate speed and relevance – while keeping humans responsible for context, nuance, and relationships.

The goal isn’t automation for its own sake.
The goal is shorter time-to-revenue with higher signal quality.

 

Metrics Must Evolve with Buyer Behaviour

As discovery shifts into AI systems, measurement must evolve with it.

Clicks, sessions, and even MQLs still matter – but they no longer tell the full story. Many buying decisions are now influenced by off-site, inside AI interfaces you don’t control.

That’s why leading B2B teams are expanding their metrics to include:

• AI brand references
• Share of voice across AI-generated answers
• Visibility on high-intent commercial prompts

Using GeoScore, DemandGen tracks these signals alongside traditional performance metrics to give a more accurate view of brand influence in an AI-driven market.

If your brand isn’t visible where AI is shaping decisions, you’re invisible earlier than you think.

 

Automation Without Empathy Is a Dead End

As AI accelerates execution, one truth remains unchanged:
B2B buying is still built on trust.

AI can generate content, optimise targeting, and surface insights – but it can’t replace empathy, credibility, or long-term relationships. The organisations succeeding with AI are those investing just as heavily in people, training, and best practices as they are in technology.

At DemandGen, we actively train our teams to use AI tools to:

• Increase speed and efficiency
• Improve relevance and personalisation
• Maintain human tone and judgement

AI becomes a force multiplier – not a substitute for experience.

 

From Experimentation to Measurable Impact

The difference between AI hype and AI leadership is results.

For one B2B client, DemandGen augmented existing demand generation and paid media strategies with advanced AI-driven audience modelling – including deeper, more strategic use of Meta and LinkedIn’s AI audience capabilities.

By combining:

• AI-powered targeting and optimisation
• Human-led messaging and positioning
• Proven demand generation fundamentals

The campaign delivered a 100% increase in sign-ups, demonstrating what happens when AI is applied strategically – not superficially.

 

What B2B Leaders Should Do Now

The AI era doesn’t require incremental change – it requires structural rethinking.

For sales and marketing leaders, the priorities are clear:

• Redesign discovery strategies for AI-driven search and recommendations
• Architect AI workflows that connect signals to revenue
• Adopt new metrics that reflect AI-mediated influence
• Upskill teams to use AI responsibly and effectively
• Protect the human layer that builds trust and differentiation

 

Final Thought

AI isn’t just changing how B2B teams operate – it’s redefining how buyers decide.

The organisations that win won’t be the ones using the most tools, but the ones with the clearest strategy for combining AI, data, and human insight into a single revenue system.

For demand generation leaders, this shift isn’t coming.
It’s already here.

And those who act now will define the next decade of B2B growth.

 

The Search Revolution Nobody’s Talking About: Why B2B Marketers Need to Prepare for AI-First Discovery

Remember when we all obsessed over keyword rankings and backlinks? Well, while most of us were perfecting our SEO strategies, the entire search landscape shifted beneath our feet. And the brutal truth is: most B2B companies haven’t even noticed yet.

Let me share some numbers that should make you sit up and pay attention.

The Data You Can’t Ignore

39% of marketers report their website traffic has declined since Google launched AI Overviews in May 2024. That’s not a minor fluctuation; that’s a fundamental change in how your potential customers find information online.

But here’s where it gets really interesting. Zero-click searches increased from 56% to 69% between May 2024 and May 2025. Think about what that means for a moment: more than two-thirds of searches now end without anyone clicking through to a website. Your beautifully optimised landing page that you spent months perfecting? Your ideal customer might never see it because the AI answered their question first.

And before you think this is just about Google, ChatGPT has grown to over 250 million weekly users in 2024, with many sessions lasting far longer than the quick in-and-out of a typical Google search. These aren’t casual browsers; these are people having in-depth conversations about their business challenges.

What’s Actually Happening Here

The shift isn’t just technological – it’s behavioural. Your buyers are fundamentally changing how they research solutions.

Here’s what that looks like in practice:

A few years ago, a procurement manager searching for a demand generation agency would type “best demand gen agency UK” into Google, click through ten websites, read reviews, compare offerings, and slowly build a shortlist over days or weeks.

Now? They open ChatGPT and ask: “I need a demand generation agency in the UK that specialises in B2B SaaS. Who should I consider and why?”

The AI responds instantly with 3-5 recommendations, complete with reasoning about why each might be a good fit. If your company isn’t one of those names being cited, you’ve lost the opportunity before you even knew it existed.

This isn’t some future prediction. 92% of Fortune 500 companies report leveraging OpenAI’s products. Your buyers are already there, having these conversations without you.

The Uncomfortable Truth About Traditional SEO

I’ve spent years helping companies optimise for search engines. Domain authority, quality backlinks, keyword density, schema markup—we all know the playbook inside out. And yes, these fundamentals still matter.

But increasingly, they’re not enough.

Studies show average drops of 15% to 70% or more in organic clicks for website traffic, depending on your industry and search intent. Even if you’ve fought your way to the #1 position on Google for your target keyword, that ranking means significantly less if people are getting their answers without ever scrolling to see your perfectly crafted title tag.

The reality is brutal: you can have flawless traditional SEO and still be invisible in the platforms where your buyers are actually doing their research

Why This Matters Even More for B2B

In B2B, we already know the buying journey is complex. Multiple stakeholders, long sales cycles, high-value decisions that require internal buy-in. Now add AI platforms into the mix, and you’ve got buyers doing their initial research, building shortlists, and forming opinions about vendors through conversational interfaces that either know about you—or don’t.

Think about your own behaviour for a moment. When you need to evaluate a new martech tool or find a specialist agency, do you still click through ten review sites and comparison pages? Or do you ask ChatGPT or Perplexity to give you a quick rundown of your options?

Be honest.

Your buyers are doing exactly the same thing. And if AI platforms don’t surface your company in those critical early-stage conversations, you’re simply not in the consideration set. You don’t even get a chance to compete.

The Four Factors That Determine AI Visibility

So what makes an AI platform like ChatGPT cite one company over another? Through extensive testing and analysis, we’ve identified four core parameters that Large Language Models consistently evaluate:

1. Authority – Your domain’s credibility and reputation across the web. This isn’t just about backlinks anymore; it’s about whether the broader internet considers you a legitimate, established player in your space.

2. Relevance – How closely your content aligns with what the user is actually asking. AI platforms are remarkably good at understanding intent and matching it to genuinely helpful information.

3. Context – The depth and quality of information on your pages. AI models favour comprehensive, well-structured content that provides real value, not just keyword-stuffed fluff designed to game algorithms.

4. Keywords – Yes, keywords still matter, but not in the way you might think. It’s about semantic relevance and natural language that matches how people actually talk about problems and solutions.

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Check the AI visibility of your website now at – https://geoscore.app/

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The challenge? These parameters interact in complex ways, and what works for one search query might not work for another. There’s no simple checklist you can follow.

What B2B Companies Should Be Doing Right Now

Here’s the strategic reality: most companies are still pouring resources into traditional SEO while largely ignoring AI visibility. That creates a massive opportunity for early movers.

Audit your current AI presence. Start by searching for your company and competitors in ChatGPT, Claude, and Perplexity. What comes up? Are you being cited? For what queries? This isn’t vanity research—it’s competitive intelligence about an entirely new channel.

Understand where you’re losing visibility. If a competitor is being recommended instead of you, why? What do they have that you don’t? This requires more than ego—it requires honest assessment of your digital footprint from an AI perspective.

Optimise your content for AI discovery. This doesn’t mean abandoning SEO best practices. It means ensuring your website content is genuinely informative, well-structured, and clearly explains who you are and what problems you solve. AI platforms reward substance over tricks.

Monitor how this landscape evolves. AI search is changing rapidly. What works today might not work in six months. Companies that stay ahead of these changes will have a significant competitive advantage.

The Window Won’t Stay Open Forever

Here’s what concerns me: we’re currently in that sweet spot where most B2B companies are still asleep to this shift. The ones who recognise it now and take action will build a considerable moat before their competitors even understand what’s happening.

This reminds me of the early days of content marketing or the initial rise of LinkedIn as a B2B channel. The companies who moved first gained disproportionate returns. The laggards spent years playing catch-up.

The same pattern is happening again with AI visibility. Except this time, the stakes are higher because the shift is happening faster.

What Comes Next

We’re not suggesting you abandon everything you know about traditional search marketing. Far from it. SEO fundamentals remain important.

But if you’re only optimising for Google and ignoring the platforms where your buyers are increasingly starting their research, you’re setting yourself up for a nasty surprise when you review next year’s lead generation numbers.

The companies that thrive in the next few years won’t be the ones with the best SEO. They’ll be the ones who figured out how to be visible everywhere their buyers are looking—including the AI platforms that are rapidly reshaping the discovery process.

The question isn’t whether AI search will impact your business. The question is whether you’ll be ready when it does.

Start Getting Your Website Visable to AI Now – https://geoscore.app/

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What’s your experience been? Have you noticed changes in your website traffic since AI Overviews launched? Are you seeing prospects mention they found competitors through ChatGPT? I’d genuinely love to hear what you’re seeing on the ground. Drop me a message—this is too important for any of us to figure out alone.arketers can unlock its full potential and create a more engaging and personalised campaigns and customer experience.

Could Gen AI Enhance Your Content Pillars

Generative AI is rapidly changing the landscape of content creation and customer experience. The technology offers a wide range of applications for marketers, beyond just automatic content generation, with many starting to explore applying the technology to curate a personalised customer experiences.

What is Generative AI?

Although you might be aware of what Artificial Intelligence is, Generative AI is a type of artificial intelligence that can create new content, such as text, images, audio, and video. It works by learning the patterns and structures of existing content and then using that knowledge to generate new content that is similar.

How Can Generative AI Benefit Marketers?

Generative AI offers a number of potential benefits for marketers. It can increase efficiency by automating many of the tasks involved in content creation, freeing up marketers to focus on more strategic work. It can also improve personalisation by creating personalised content experiences for customers, which can lead to increased engagement and conversions. Additionally, Gen AI can enhance creativity by generating new ideas and formats for content, helping marketers to break through the clutter and capture attention. Finally, generative AI can create entirely new formats of content, such as virtual influencers and brand avatars.

Practical Applications of Generative AI for Marketing

Here are some specific examples of how generative AI can be used in marketing:

• Text generation: Generative AI can be used to create marketing copy, news stories, social media posts, and other types of written content. For example, a company could use generative AI to create different versions of ad copy to see which performs best.
• Image generation: Generative AI can be used to create images for marketing materials, social media, and websites. For example, a clothing company could use generative AI to create images of models wearing different outfits.
• Video generation: Generative AI can be used to create marketing videos, product demos, and even personalised video messages for customers. For example, a real estate company could use generative AI to create virtual tours of properties.
• Personalised experiences: Generative AI can be used to create personalised email campaigns, website experiences, and even product recommendations. For example, an e-commerce company could use generative AI to recommend products to customers based on their past purchase history.
• Virtual influencers and brand avatars: Generative AI can create virtual influencers and brand avatars for social media and the metaverse. For example, a beauty company could use a virtual influencer to promote its products on Instagram.

Challenges and Considerations

While AI offers many potential benefits, it is important to be aware of the challenges and considerations. Gen AI can be used to create deepfakes and other types of misleading content. It is important to use this technology responsibly and ethically. AI models can also be biased, which can lead to the creation of discriminatory or offensive content. It is important to carefully evaluate and mitigate bias in models.  AI could also unknowingly potentially create content that infringes on existing copyrights, meaning marketers must be aware of the legal implications of using this technology. While AI can automate many tasks, it is important to remember that it is still a tool. Human oversight is essential to ensure that the content created is high-quality and meets brand guidelines. AI also works by replicating content meaning the work will always be lacking in originality. It is also important to consider the human reaction to AI, many large brands have faced criticism and backlash in recent times for using AI instead of paying artists, designers, or copywriters.

The Future of Generative AI in Marketing

Gen AI is still a relatively new technology, but it will continue to evolve rapidly. As it continues to develop, we can expect to see even more innovative applications of this technology in marketing. In the future,  AI may be able to create even more realistic and engaging content, maybe even leading to the creation of content that is indistinguishable from human-created content!  Marketers will be able to create hyper-personalised experiences tailored to individual customer preferences and needs, automating the entire process of creating and executing marketing campaigns, from content creation to ad targeting. AI could power new forms of customer interaction, such as highly intelligent AI-powered chatbots and virtual customer assistants.

Conclusion

Generative AI is certainly a powerful technology that has the potential to transform marketing. By automating content creation, enabling personalisation, and enable creativity. Marketers will be able to achieve better results and connect with customers in new and innovative ways. However, it is important to remain aware of the challenges and considerations associated with applying this technology. By using AI responsibly and ethically, marketers can unlock its full potential and create a more engaging and personalised campaigns and customer experience.

Choosing a CRM system that best fits your business needs

A CRM (customer relationship management) system is crucial for winning and retaining business. CRM is not only about managing customer relationships. It’s also about gaining a better understanding of your business and clients. It helps you stay in control and effectively meets their needs. In the first few years of the business’s lifecycle, business owners usually store customer information in excels sheets only to realise that when it comes to analysing the customer data and using it to either:

• Create personalised marketing plans
• Improve customer experience through action insights

Hence, choosing a CRM system should be one of the first few decisions a growing business should make based on how it intends to use the customer data.

Identifying Your Needs and Goals

Choosing the appropriate tool is crucial for you and your colleagues to continue advancing the business. With plenty of choices available in the market, it is essential to identify the reason WHY you require a tool and WHAT specific tasks you want it to perform.

What are the benefits of a CRM system?

• A CRM system allows you to see the accurate picture of your customers
• Helps identify, define and segment an Ideal Customer Profile (ICP)
• Build relationships with clients and improve customer service, thanks to insights
• Improve your client communication
• Identify opportunities to upsell or cross-sell
• Help track sales and marketing activities against each client

Factors to consider when choosing a CRM system

What are your most significant needs?

CRM platforms can significantly enhance your business’s efficiency by automating tedious and time-consuming tasks such as data entry and reporting. Therefore, it is crucial to select the right CRM platform that caters to your specific needs and requirements.

When considering different CRM suppliers and platforms, it is essential to identify your specific needs and requirements. Are you looking to improve your customer relationships? If yes, ensure the platform provides the tools to utilise this aspect effectively.

Or are you looking for a way to make quick and informed decisions? A CRM system can provide real-time data on customer engagement and activity through social tools, helping you determine where to focus your new strategies.

What is your budget?

Investing is crucial for growing and scaling a business, so CRM tools are no exception. However, the prices of these tools depend on various factors, such as the features and the number of users, as well as any upgrades or additional options. It’s also important to note that there may be extra charges on top of the initial upfront costs. Therefore, it’s essential to consider how many users you need and not opt for the all-in-one package if it’s unnecessary, especially if only a few staff members will be working on the platform.

What essential features do you require?

A Customer Relationship Management (CRM) tool cannot be expected to work perfectly from the beginning. Its purpose is to facilitate and improve the procedures that are already in place. However, as a business, you must determine what is most crucial for your company. Is it lead management to attract new customers or contact management to maintain relationships with existing clients?
The technology for lead management allows you to choose when to follow up. It analyses demographics and data to help you focus on leads at the right time and secure the sale.
Meanwhile, contact management is an essential factor. You can maintain your relationships with clients by using a tool that helps personalise emails and contacts for each client. This will make them feel special. Additionally, this tool can provide you with data on when to introduce new marketing strategies or products to them.

What sort of integration do you need?

Most CRM systems can integrate with other tools, so it’s essential to verify which software you want to integrate. If a chat function is necessary, or if HR software or website analytics are imperative to you, make sure they are compatible with your chosen CRM system to keep everything running smoothly.

Size of the database and growth forecast

Most CRMs are priced on the number of contacts you hold in the database, so having an idea of the number of contacts you have now in the database and how much you would expect to grow in the contract period with the CRM. Purchasing extra data bolt-ons often proves expensive in the long run, so it is good to have that in mind before purchasing.

Consider your reporting needs

Most CRMs have built-in templates for activity, sales, marketing, and director-level reporting. We strongly recommend testing these templates to see if they meet your reporting requirements.  

At Demand Gen, we are experts in utilising various CRM tools – including Hubspot, Monday.com, Salesforce, and more. Speak to our team to take your CRM journey to the next level.