AI has shown its value in content creation—we’re exploring how much further it can take us in B2B marketing. Join Scott Losasso, CEO, and David Fabbri, CSO, as they discuss how AI is revolutionizing B2B marketing, from lead enrichment to custom GPTs for client knowledge bases.
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Quick note: This conversation was transcribed with the help of artificial intelligence and has been lightly edited for content.
Scott LoSasso (00:01)
Hi, I'm Scott Losasso.
David Fabbri (00:03)
Hey, I'm David Fabbri. We're two principals here at LoSasso Integrated Marketing, a B2B marketing agency in Chicago. Today, we're going to talk about how we are leveraging AI in our work and some exciting new things that are happening.
Scott LoSasso (00:16)
Yep, interesting time for sure. Where do you want to start, David?
David Fabbri (00:20)
Well, I kind of want to start with something a little different than what we’re typically seeing and hearing out there. A lot of the AI discussion revolves around generative AI for content and graphics. But we're developing an offering for our B2B clients that enhances lead quality using AI. Maybe we start there?
Scott LoSasso (00:47)
Yeah, one of the challenges for B2Bs is that everyone wants lead generation. Often, you use gated content and high-value materials to capture leads. The fewer fields you require, the easier it is to get people to provide their data—but that means you don’t have much to work with.
We're finding that you can use AI-driven tools to enrich those low-information leads by bouncing them off various databases, which makes them significantly more valuable.
David Fabbri (01:24)
So, what kind of data are we talking about? Obviously, you want to know who the person is, what their company does, and whether they are a viable lead. But it seems like there's even richer data we can leverage.
Scott LoSasso (01:39)
Exactly. If you start with just a name and an email, you can often pull their full title, company name, firmographics like company size and location, and even a synopsis of what they do. If they list equipment on their website, you can pull that data, too.
The more you feed these tools, the more they refine the data, identifying why a lead might be reaching out and what their interests might be. This gives the sales team a head start.
David Fabbri (02:18)
Yeah, and there are even ways to tap into LinkedIn posts, company news, or industry updates. For example, if a company announces a new facility and you're selling equipment for that type of facility, you've identified a high-value, active prospect. That’s something meaningful for sales to follow up on.
Scott LoSasso (02:46)
Right. And most B2B decisions involve a committee. If you know the typical titles involved in the decision-making process, you can append the lead data with additional contacts within the organization. That helps assess lead quality and determine readiness.
This is especially useful for transitioning from a marketing-qualified lead (MQL) to a sales-qualified lead (SQL). AI helps take several steps down that path, making it easier to prioritize follow-up.
David Fabbri (03:32)
Exactly. This also addresses the classic disconnect between marketing and sales. Marketing says, “We’re generating all these leads—what are you doing with them?” Sales says, “Great, but you’re sending us names and emails with no context.”
With AI, we’re providing sales teams with vetted, higher-value leads.
Scott LoSasso (04:31)
Yeah, and another way we’re improving the process is by using AI to draft initial email responses. A salesperson can review a dossier that includes background information, k
ey talking points, and reasons why the lead is a good prospect. They can fine-tune a suggested email and send it off, getting further down the road with less effort.
David Fabbri (05:14)
Some companies are even taking this a step further by automating pre-scripted, AI-generated email responses. But for B2Bs, we usually recommend treating leads with a higher degree of personalization.
People are getting good at spotting AI-generated outreach, and poorly executed automation can undermine relationships. It’s about striking the right balance b
etween automation and thoughtful engagement.
Scott LoSasso (05:30)
That makes sense. And for marketers wondering, how does this even work? and is it expensive?—the answer is, not necessarily.
The tools are evolving rapidly, and like marketing automation before it, AI-powered lead enrichment is becoming more accessible and cost-effective. The key isn’t just choosing a specific tool but understanding how to integrate AI into your workflow.
David Fabbri (06:08)
So how quickly do you think this will become standard practice in lead gen?
Scott LoSasso (06:15)
This year.
David Fabbri (06:16)
Yeah, I agree. The tools are only going to get better.
Scott LoSasso (06:22)
Right. And companies are using different AI tools—ChatGPT, Gemini, and Perplexity, plus automation platforms like Casper, Clay, and Apollo. The key is combining the right mix of tools to gather and integrate data into CRM systems like Salesforce or client-side databases for immediate and ongoing use.
David Fabbri (07:07)
And AI isn’t just about automation—it adds an intelligence layer. It doesn’t just append data; it interprets it, making recommendations based on industry trends, buying signals, and potential timing factors.
Scott LoSasso (08:05)
Exactly. Even if AI is only 50-80% accurate, it still provides valuable context, helping sales teams start more meaningful conversations.
David Fabbri (09:08)
Another exciting AI use case we’re working on is custom AI knowledge bases for clients.
With enterprise versions of AI tools, we can build custom GPTs that store client-specific knowledge, training the AI to respond with industry-relevant insights. This helps retain and consolidate subject matter expertise, so new team members can quickly get up to speed, and existing t
eams can easily access past learnings.
Scott LoSasso (10:55)
That’s a huge advantage—especially in technical B2B industries where we rely on subject matter experts. Having a centralized, AI-powered knowledge base ensures consistency and reduces the learning curve.
David Fabbri (12:22)
Right. And it’s not just for content creation. AI-driven segmentation and personalization allow us to tailor content more effectively. Instead of a one-size-fits-all approach, we can dynamically generate industry- or persona-specific versions of marketing materials at scale.
Scott LoSasso (13:26)
And from an agency perspective, AI also improves continuity. Employees come and go, but AI helps retain institutional knowledge, ensuring smoother transitions. It also speeds up research for pitches and industry deep dives. What used to take hours can now be done in minutes.
David Fabbri (14:18)
Yeah, the more we use these tools, the more mind-blo
wing—but also unsurprising—they become.
Scott LoSasso (14:44)
Totally. We recently prepped for a new business pitch in an industry we hadn’t worked in before. AI helped us research the space and tailor our creative brief so well that the client was shocked at how dialed in we were.
David Fabbri (16:07)
And AI’s impact is only accelerating. By the end of this year, some experts predict that AI-powered programming will be as good as 99% of human developers. The key will be learning how to engineer and train AI effectively.
Scott LoSasso (17:20)
Yeah, and strategically, it’s about understanding what you’re trying to achieve with AI and why. The tools make execution easier, but smart marketing fundamentals remain the same.
David Fabbri (17:36)
Exactly. So, what’s your prediction for AI in marketing a year from now?
Scott LoSasso (17:51)
A year from now, the hesitation around AI will be gone. Everyone will be focused on how to use it effectively. If you’re not leveraging AI, you’re going to be left behind. This is disruptive, and we have a choice—be disrupted or be the disruptors. The AI train has left the station, and getting on board will only make us better.
