Algomarketing® x Google
How Google's EMEA marketing organisation replaced a fragmented vendor model with a single AI-native execution engine in Lisbon, and what it did to pipeline, speed to market, and team capacity.
The mandate
Google's EMEA marketing organisation was scaling fast, but performance was lagging the plan. If you carry an AI transformation mandate, this starting point will look familiar.
Multiple suppliers, multiple locations, manual workflows. Delivery quality varied and AI adoption stalled.
The model
Algomarketing partnered with Google to build a regional Centre of Excellence in Lisbon that goes beyond centralisation and cost savings: a living lab where AI-proficient talent runs live campaigns and continuously pioneers new AI-driven marketing best practice.
Individual working sessions with each marketer to map their current processes and rebuild them as AI-enabled workflows using Google's own tools.
A growing library of prompts, Gems, templates, and reusable workflows that marketers plug into and adapt for their roles and use cases.
Ongoing upskilling on GenAI and automation tools, plus higher-order skills: problem-solving, critical thinking, and refining AI outputs.
Structured paths to Google's Gen AI Business Leader certification and other credentials, signalling verified AI proficiency across the team.
Marketing impact
Centralisation stories usually stop at cost and headcount. This one didn't. Here is what happened to actual marketing performance when AI-native operators went to work inside live Google programmes.
GenAI campaign frameworks cut idea-to-launch timelines in half and were reused across markets, aligned to governance.
Optimised prompt workflows halved customer case study production time, enabling rollout across India and Singapore.
Monthly reporting collapsed from 20 hours to minutes using agentic flows that automate data collection, analysis, and storytelling.
Event speaker and venue research that once took over six weeks now happens in minutes with Deep Research workflows.
Account-level intelligence and GenAI-assisted segmentation improved segmentation cycles by 40 to 50 percent for EMEA campaigns.
Three new Google teams onboarded onto the nurture engine with zero additional infrastructure and zero extra hires.
Featured story
One of Google's highest-visibility marketing programmes spanned 12 languages, 4 regions, and 5 product streams: over 600 email versions refreshed every quarter. It was performing well, with $15M in pipeline already generated. But operationally, the team was drowning in spreadsheets, scattered approvals, and manual UTM formulas.
Programme complexity
Liane didn't wait for an engineering team. She taught herself to code alongside Gemini and shipped a role-based workflow application in weeks, replacing the spreadsheet sprawl with a single operational spine for the programme.
Audience growth, same team
The people behind the numbers
Every metric on this page traces back to a person embedded inside a Google team, rebuilding how the work gets done. Select a profile to see their impact.
Managed one of Google's highest-visibility nurture programmes, then taught herself to code alongside Gemini and rebuilt its entire operational infrastructure. She also uses Deep Research to compress event speaker and venue research from over six weeks to minutes.
Partner content was valuable, but timelines were long and localisation required multiple handoffs. Shermaine introduced modular workflows and GenAI-assisted scripting that made content creation repeatable and scalable for field teams across the region.
Teams were testing tools but lacked systems to scale what worked. Enes worked across marketing ops, engineering, and product to build the foundation: reusable campaign frameworks aligned with governance, and agentic reporting that runs itself.
Precision targeting comes down to how usable your data actually is. Embedded in the EMEA campaigns team, Connor worked across campaign and BDR functions to make insights usable, fast, and compliant.
Built to scale
The CoE launched with 40+ AI-native specialists and is targeting 200+ by 2027, expanding from Google Marketing EMEA into 8+ product areas. Behind that growth is a repeatable transformation methodology that rebuilds how marketing delivery works, then proves it with data. Tap each stage.
Understand the existing team, structure and operations
Surface legacy, repeatable and mundane processes
Remap the entire delivery model around AI-enabled workflows
Prove impact on live work, then scale what works
We embed alongside your marketers to understand the existing team, delivery structure, and operations as they really run: the tools, the handoffs, the governance, and where delivery genuinely creates value.
Why Lisbon
The country's largest concentration of multilingual, digitally native marketing talent
Mature enterprise and tech ecosystem, with strong relocation appeal for international talent
Reliable infrastructure, dual-ISP redundancy, and fully auditable VOVO compliance
algomarketing | evolve
Google chose Algomarketing because we don't just train on AI. We embed AI-native Evolved Marketers directly into real workflows, and the performance metrics follow. Let's build your AI-native marketing team.
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