For many companies, AI has become part of everyday operations. It’s used to automate tasks, generate content, and support faster decisions. But when it comes to improving how teams go to market—how they attract, engage and serve customers—AI is often underused.
That’s not a technology problem. It’s a go-to-market (GTM) problem.
Most organizations have built up strong capabilities in sales, marketing, customer experience (CX) and analytics. But those teams often work in silos, with their own tools, data and processes. AI can help—but only if it’s applied in ways that connect teams, improve execution and support shared goals.
At ZS, we’ve seen how forward-thinking companies are making this shift. They’re not chasing the latest tech trend. They’re rethinking how their GTM models work—starting with how customer needs are identified, prioritized and met.
Here’s what that looks like in practice.
Common gaps that hold teams back
Even with strong teams and advanced tools, many organizations still face the same challenges:
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Sales and marketing don’t share context. Leads are passed too early or too late. Campaigns miss the mark. Conversations repeat.
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Customer data is hard to act on. Insights are available, but not in the moments that matter—during planning, outreach or service.
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The model is built around the team, not the customer. Plans follow internal cycles, not real-world signals.
These gaps slow things down and create friction. And they make it harder to give customers the kind of fast, personalized experience they expect.
What a modern GTM model looks like
Top-performing teams are moving toward a more connected, responsive model. It doesn’t require a full rebuild. Instead, they focus on a few key shifts:
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Shared signals. By combining internal and external data—such as buying patterns, site behavior and service history—teams get a clearer view of what matters to each customer.
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Smarter prioritization. AI models help teams spot the most relevant next steps, so time is spent on what’s likely to drive progress.
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Modular systems. Instead of one-size-fits-all platforms, teams build flexible components that can be tested, scaled and updated quickly.
Building a smarter GTM model isn’t just about efficiency. It’s about giving people the right information, at the right time, to do their best work.
Results that matter
When teams take this approach, the benefits show up across the board:
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Marketing becomes more relevant. Campaigns reflect real interests and intent—not broad segments.
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Sales becomes more focused. Reps know which leads are likely to convert, and what matters most to each buyer.
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CX becomes more consistent. Service teams can see the full customer story and respond with the right context.
It’s not just better for customers—it’s better for business.
Your next steps
You don’t need to build a new tech stack to make progress. In fact, many companies start by making better use of the tools and data they already have. Here are three things we recommend:
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Form cross-functional teams. Bring together leaders from marketing, sales, CX and analytics to co-own priorities and outcomes.
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Start with a real use case. Pick a specific pain point—such as lead handoffs or campaign targeting—and test a smarter, AI-supported way to do it.
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Scale what works. As you learn what drives results, expand it to other areas.
The goal isn’t to automate everything. It’s to help teams move faster, serve customers better and make smarter decisions every day.
Let’s get started
Want to see how other organizations are doing it? Read the full article here: Modernizing GTM and customer experience with AI
At ZS, we help business and technology leaders improve how their teams reach, engage and serve customers. If you’re ready to make your GTM model faster, smarter and more connected, let’s talk about how we can help.
