Building the Engine: MarTech Integration at GTT | Case Study

GTT Communications had invested substantially in marketing and sales technology. The problem was that none of it worked together.

As VP of Demand Generation, I found Marketo, Demandbase, and SalesLoft operating in complete silos: powerful tools that were producing almost no value. I applied my PRIME framework to integrate the platforms, enrich the data, automate key processes, and establish a 60-minute global lead routing SLA. The result was a high-functioning demand generation ecosystem that critically enabled our global sales team to win essential new business in 2023 and 2024.

The challenge

At a $3 billion global company, the MarTech stack looked impressive on paper and was nearly worthless in practice:

• Key systems like Marketo and Demandbase weren’t connected to the website or to each other
• Google Analytics implementation was incomplete, crippling analytical capabilities
• Data quality was poor, with incomplete prospect and account information throughout
• Marketing operations had been reduced to basic list acquisition via ZoomInfo
• Marketo’s sophisticated nurturing and scoring capabilities sat entirely unused
• Sales teams were frustrated by poor data quality and inconsistent processes

This fragmentation created a concrete business problem: the demand generation function couldn’t scale, and the sales team wasn’t getting the quality of leads and prospect insights they needed to succeed. Without fixing these foundational issues, ambitious revenue targets would stay out of reach.

The approach

I addressed this as a comprehensive integration and optimization initiative spanning all five PRIME phases.

P: Potential Mapping

The stack looked impressive and produced almost nothing, so I started by mapping where the value was trapped. Integrated platforms would let us move from generic outreach to personalized, data-driven communications: Demandbase account intelligence and enriched prospect data could deliver relevant messaging to specific segments, something that was impossible while the platforms sat disconnected. That gap defined the opportunity.

R: Roadmap & Strategy

I implemented predictive analytics to score accounts and contacts based on fit and potential value, segmenting them into practical tiers:

• 1:Many: scalable approaches for broader targeting
• 1:Few: focused engagement for promising segments
• 1:1: tailored outreach for the highest-potential accounts

This account-based structure gave the revenue engine a clear architecture to build around, rather than treating every lead the same.

I: Implementation Planning

The integration was the technical foundation everything else depended on, so I planned it before any connection was made. I mapped how Marketo, Demandbase, SalesLoft, and the company website would connect into a cohesive system, what the incomplete Google Analytics implementation needed to restore reliable data collection, and how cross-channel attribution would track SQL quality by inbound source so we could see which channels delivered the best prospects.

M: Migration & Execution

I led the build. We connected the platforms into a single working system, fixed the analytics implementation, and stood up the attribution tracking. I oversaw data enrichment initiatives across the platform stack so leads were properly scored, categorized, and routed with the context the sales team needed.

I then worked closely with Sales Operations to redesign the lead flow process. The centerpiece was a globally consistent routing system with a stringent 60-minute Service Level Agreement for lead assignment, a dramatic improvement in speed-to-lead. With analytics restored, I built reporting dashboards that tracked performance across the entire pipeline: lead source quality, conversion rates by tier, SLA compliance, and marketing-attributed revenue.

E: Enablement & Adoption

I deployed automation tools (Make.com) integrated with large language models and Marketo to generate and send hyper-personalized email communications at scale, enhancing prospect engagement while significantly reducing manual effort across the team. Automating that personalized content production later became its own initiative, cutting asset creation for a target account from 48 hours to minutes.

I also implemented automated data enrichment and validation workflows that kept leads categorized, scored, and routed with minimal human intervention, and I gave the sales team clear playbooks for following up on high-value prospects. A cadence of weekly check-ins with Account Managers kept the focus on progressing key opportunities to closed-won, so the team adopted the new system to move pipeline, not just fill it.

The results

The transformation delivered significant operational improvements that directly drove business outcomes.

Functioning, integrated ecosystem. Previously siloed MarTech platforms were unified into a cohesive stack that provided a complete view of prospect engagement for the first time.

Data visibility and actionability. Effective lead scoring became possible. Reliable tracking of lead sources tied to quality gave both marketing and sales richer prospect insights through automated data enrichment.

Operational efficiency. A rapid 60-minute global lead routing SLA was implemented and consistently met, dramatically improving speed-to-lead. Automation reduced manual effort across the organization.

Enhanced marketing capabilities. Personalized outreach scaled using automation and AI, enabling more sophisticated segmentation and nurturing based on integrated data, at a level that hadn’t been operationally feasible before.

Improved sales effectiveness. The global sales team gained faster access to better qualified, data-enriched leads, along with clear playbooks for follow-up, improving their ability to engage prospects effectively.

Critical business contribution. These operational improvements directly enabled the sales team to manage increased lead flow and successfully win the essential new business required for company performance in 2023 and 2024.

Why this matters

Expensive MarTech stacks that don’t deliver value are one of the most common and costly problems in B2B demand generation. The tools themselves are rarely the issue. The integration, the data quality, the processes around them, and the alignment with sales: those are where the value gets lost.

If your marketing platforms are operating in silos, the problem isn’t the technology. It’s the architecture connecting them. Getting that right turns a collection of expensive subscriptions into a working revenue engine.