AI Marketing Signals in B2B: The New GTM Playbook for SaaS Expansion

When Joliene van Grieken, Co-founder of The Growth Syndicate, joined Nicola Calabrese on The Multilingual Content Podcast, the conversation quickly moved beyond the usual advice on international expansion. Joliene, who has spent her career building and scaling marketing functions inside startups and scale-ups , shared a perspective that caught our attention: marketing is shifting from campaigns to signals.

What does that mean in practice? Instead of running a campaign, measuring results after six weeks, and adjusting for the next quarter, the most effective B2B SaaS marketing teams are now building systems that detect demand and intent in real time. And when you're expanding internationally, that shift changes everything, from how you structure your team to how you localize your go-to-market approach.

Here's what we unpacked from the conversation.

What Are AI Marketing Signals in B2B?

AI marketing signals are data points, generated, detected, or interpreted by AI, that indicate buyer intent, emerging demand, or competitive shifts in your market. Instead of relying on periodic reports and manual analysis, B2B SaaS companies can now use AI to monitor and act on these signals continuously.

Think of it this way: a traditional competitive analysis might happen every six to eight months. Someone on your team puts together a battle card, it gets shared with sales, and it sits in a folder until the next update. By then, your competitors have shipped new features, changed their positioning, or entered markets you're also targeting.

With AI marketing signals, that battle card updates itself. A sales person can input the company they're about to speak with and get the ten most relevant talking points , pulled from live data, not a six-month-old document.

Joliene described this shift as one of the most important changes happening in B2B marketing right now. And it has a direct impact on how companies approach international expansion.

Why Signals-Based Marketing Changes International Expansion

When a B2B SaaS company enters a new market, the traditional approach involves a significant upfront investment in research: understanding the local competitive landscape, identifying industry-specific pain points, mapping the buying cycle, and figuring out which messaging resonates.

That research is still necessary. But the way you gather and act on it is changing.

AI tools can now monitor competitive movements across markets in real time , not just what your competitors are saying on their English-language website, but what they're doing in Germany, France, the Nordics, and beyond. They can track shifts in buyer behavior, surface intent signals from different regions, and help your team respond faster than a quarterly review cycle would allow.

This is especially valuable in markets where you're still building credibility. As Joliene pointed out in the episode, you can't just copy-paste what worked in your home market and expect the same results elsewhere. Different countries have different buying cycles, different stakeholders with different levels of authority, and different expectations about how solutions are evaluated.

AI marketing signals help you understand those differences faster , and adapt your approach before you've spent months and budget learning the hard way.

What Filippo Irdi of Orderchamp shared about European expansion reinforces this: the companies that succeed internationally are the ones that build local intelligence early, not the ones that assume their home-market playbook will transfer.

The New B2B Marketing Team: Smaller, Sharper, Signal-Driven

One of the most practical parts of the conversation was Joliene's view on how marketing teams should be structured now , especially for companies scaling across borders.

Her recommendation: you need fewer people, but the right people.

The core team she described looks different from what most B2B SaaS companies are used to.

But the real shift is in the third hire: what Joliene called a GTM engineer. This is someone who can build the infrastructure for detecting and acting on signals , connecting different tools, setting up automated workflows, and creating systems that surface intent data so your team can move on it quickly.

This role didn't exist in most marketing teams two years ago. Now, according to Joliene, it's one of the first hires she'd recommend , right alongside content and design.

For companies expanding internationally, this has a specific implication. A signals-driven approach means you can test a new market with a leaner team. Instead of hiring a full local marketing function upfront, you use AI-powered signals to identify where demand is forming, validate your messaging with smaller experiments, and invest in local resources only once you have evidence that a market is worth scaling into.

Why Niche Agencies Can Be a Trap

Joliene raised a point that's worth sitting with: the more specialized your external marketing partners are, the more likely they are to tell you their channel is working , even when it's not.

The same goes for design agencies or any partner whose scope is limited to a single function.

This doesn't mean specialized expertise isn't valuable. But for B2B SaaS companies in expansion mode, Joliene argues you're better served by broader, more strategic partners , people or teams who care about scaling your company, not just scaling one function within marketing.

In the context of localization, this is a pattern we see often at Undertow. Companies hire a translation vendor for one piece of the puzzle, a local SEO agency for another, and a content agency for a third. None of them are talking to each other, and none of them have visibility into whether the overall market entry strategy is working.

A signals-based approach flips this. Instead of measuring each channel in isolation, you build a system that tracks whether your combined efforts are actually generating demand in a specific market , and you adjust the mix based on what the signals tell you, not what any single agency reports.

Credibility Still Comes from People

For all the talk about AI and automation, Joliene came back to a point that anchors everything:

AI can detect signals, generate content, and accelerate your go-to-market. But it can't build the kind of trust that closes deals , especially in B2B, especially across borders.

Joliene shared an example from a client expanding into the Nordics. They ran an ABM campaign targeting two specific industries, with small, localized events , just 10 to 15 prospects, one existing client, and a local sales person. No expensive booth at a conference. Just a dinner, a conversation, and face time with the right people.

It worked because the signals told them where to focus, but the credibility came from showing up in person.

This is something Hugo Pereira highlighted as well: trust signals vary dramatically by market. What builds credibility in the Netherlands is different from what works in Germany or Spain. AI can help you identify the right signals, but the human element , local presence, relationships, cultural understanding , is what converts those signals into pipeline.

And as Björn Ingmansson of Kognic described, localization is a muscle. The earlier you start building local credibility , through adapted content, local case studies, and market-specific messaging , the faster your signals-based approach will produce results.

What This Means for Multilingual Content Strategy

If your marketing is becoming more signals-driven, your content strategy needs to keep up , across every market you operate in.

That means your content isn't just about publishing regularly. It's about producing content that feeds the signals you're tracking. When AI tools detect that a specific topic is generating intent in your German market, you need to be able to produce a credible, localized response quickly , not start a translation project that takes three weeks.

As Nicola put it during the conversation: "Everybody has the same 80%. That 20% difference is going to make the difference." That 20% is what your human team brings.

It also means your multilingual content needs to be built for AI visibility. The same AI tools that help you detect buyer signals are the ones that your buyers are using to research solutions. If your content in French or German isn't structured for AI extraction , clear definitions, answer-first formatting, strong off-site citations , you won't show up in the conversations that matter.

The connection between signals-based marketing and localized content production is tighter than most companies realize. You can't act on signals in a market where you have no content. And you can't build content that resonates without understanding the local signals first.

Key Takeaways

• AI marketing signals in B2B are shifting marketing from periodic campaigns to real-time detection of demand and intent. This changes how teams plan, execute, and measure , especially across international markets.

• The new core marketing team for SaaS expansion is smaller and more technical: a content person, a designer, and a GTM engineer who builds the signals infrastructure.

• Signals-based marketing lets you test new markets with less upfront investment. Use AI to identify where demand is forming before committing to full local teams and resources.

• Avoid over-reliance on niche agencies during expansion. Partners who can see the full picture , and tell you honestly what's working , are more valuable than specialists who optimize one channel in isolation.

• Credibility still comes from people. AI can surface the right signals, but trust is built through local presence, relationships, and culturally adapted content.

• Your multilingual content strategy needs to feed your signals. The ability to produce localized, AI-optimized content quickly is what turns market intelligence into pipeline.

FAQ

What are AI marketing signals in B2B?

AI marketing signals are data points detected or interpreted by AI that indicate buyer intent, competitive shifts, or emerging demand. They allow B2B marketing teams to monitor markets continuously rather than relying on periodic manual analysis, and to act on insights in real time.

What is a GTM engineer?

A GTM engineer (go-to-market engineer) is a marketing role focused on building the technical infrastructure that supports a signals-based approach. This includes connecting tools, setting up automated workflows, and creating systems that surface intent and demand data so the marketing and sales team can act on it quickly.

How does signals-based marketing help with international expansion?

It allows companies to detect demand in new markets earlier and with less upfront investment. Instead of committing to a full local team before validating a market, signals-based marketing lets you monitor buyer behavior, competitive activity, and intent data across regions , and invest local resources where the signals point.

Do you still need local teams if you have AI marketing signals?

Yes. AI can surface insights, but trust and credibility in a new market still come from human relationships, local presence, and culturally adapted content. Signals tell you where to focus , people are what make that focus convert into results.

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This blog post is based on Episode 56 of The Multilingual Content Podcast: "From SEO to AI Search: Rethinking International Growth with Joliene van Grieken, Co-founder of The Growth Syndicate." Listen to the full conversation for more on how AI is reshaping B2B marketing across borders.

Building your go-to-market for a new market and need content that works across languages and channels? Undertow helps B2B SaaS companies produce multilingual content that's built for real buyers and AI visibility , so your signals-based approach has something to work with in every market. Let's talk about your expansion.