If AI can generate anything, why does most brand work still feel so predictable? That’s the problem we wanted to solve with Groupon. How do you make it feel like a brand across markets, formats, and moments?
In our recent Performance+ Webinar, Allita Lavina Crasto, our Global Head of Creative; Eduard M. Arcediano, Brand Marketing Director for Groupon; Francis Roshan Kuttivelil, our Head of Technology; and Jonathan Yantz, our Managing Partner for US answer these questions and dive deep into the Turn Life ON with Groupon campaign that delivered 174 hyper-local video assets in just 2.5 months through a human-directed, AI-powered workflow.
Watch the full video here.
Download the webinar deck here.
Why This Matters Now?
Let’s start with the environment marketers are operating in today.
We’re in the middle of what feels like an AI Tsunami. In the last couple of years alone, dozens of AI-powered marketing tools have entered the market; promising everything from automated ad creation to fully generated campaigns, all from just a few prompts.
But when everything becomes automated, brands risk losing what makes them feel human.
The Shifts in Tech/AI
For the longest time, creative production has been a trade-off. If you moved fast, quality dropped, and if you protected craft, things slowed down. And now, with the sheer volume of content needed, it’s getting harder to hold on to meaning, emotion, and distinctiveness.
So the real challenge is finding that balance between speed and scale and knowing where AI should step in and where it really shouldn’t. Because AI is great at removing friction in the system and it is important to have it not replace creative thinking.
If anything, it frees up humans to spend more time on the parts that matter.
Where AI can help:
1. Rapid prototyping: Getting ideas out quickly, visualising them early, before investing too much time or effort
2. Smarter localisation: Adapting tone, language and context across markets, without starting from scratch every time
3. Creative analysis: Learning from what’s working, and helping refine creatives based on real performance signals
Modernizing Your Creative Production
If you want to modernize today, you can’t just “buy an AI tool” and hope for the best. AI is only as good as what you feed into it and most of the time, that’s the missing piece.
1. AI Ready Data: If you’re using AI to create, your foundation needs to be structured. That usually comes down to three things:
- Clear brand guidelines: Define your visual language, tone of voice, what “good” looks like.
- Strong brand guardrails: Setting and defining what’s allowed and what’s not (IP, brand safety, etc.) especially where human oversight comes in.
- Your past work: Properly organize your library of assets, and make sure they are tagged, and searchable, with performance data.
2. Cross – Functional Team: You will need:
- Creatives to bring taste and direction
- Tech to make the most of the tools
- Legal to make sure everything stays within the lines
3. A real test-and-learn mindset: You’re not going to get this right the first time. No one does. You’ll need to test quickly and figure out where AI adds value and where human input is still critical.
What “Turn Life ON with Groupon” Campaign Was All About?
Groupon’s purpose: Groupon is built around helping people get off their screens and into the real world; discovering and booking local experiences. Success is about getting users to act quickly, step away from technology, and actually live those moments.
Campaign Target: With this idea at the core, the goal was to drive reach and conversion across multiple markets, while keeping the work consistent, emotionally authentic, and locally relevant so people could truly connect with it.
The “Glocal” campaign: The approach was to create one global campaign platform that could flex locally, so every market felt seen, without losing a unified brand identity.
Execution: The process started with human thinking. The narrative, tone, and what each city should feel like were defined upfront. The idea was rooted in real local experiences and cultural cues, with scripts, story flow, and emotional intent shaped closely with the client before AI came in.
From there, AI was used to accelerate the process speeding up visual exploration, environments, and iterations so multiple markets could be developed in parallel.
AI then helped build the content scene by scene, while the team continuously refined tone, transitions, voiceovers, and storytelling to ensure everything remained intentional and on-brand.
Scaling the system: The work was designed to scale from the start. Three master films formed the foundation, which were then adapted across cities, formats, and use cases.
This modular approach made it possible to deliver 174 video assets in just 2.5 months, without compromising on consistency or quality.
Campaign Results:
+11% increase in brand searches
+31% unaided ad recall, showing the work stood out
+22% increase in brand salience, strengthening presence in real buying moments
How to Operationalize AI at Scale
Scaling AI would require one to establish the right setup around tools before plugging them in.
1. Build on the right platforms: Use enterprise-ready AI which is secure, compliant, and clear on how data is being used and trained.
2. Upskill teams on AI: Train teams to prompt effectively, understand tool capabilities, and adapt to different AI systems and structures.
3. Redesign processes with AI: Integrate AI into workflows to speed up execution and scale output, while keeping human intuition and decision-making at the core.
4. Measure real impact: Use creative testing and analysis to evaluate whether AI is actually improving performance and adding value.
Tools, Tech & What Separates Winners
Platforms like TikTok, Meta, and YouTube reward volume, diversity, iteration, and localisation so content demand isn’t slowing down anytime soon. Competitive advantage comes from faster testing cycles, better performance optimization, and lower cost of production while preserving cultural relevance.
The AI stack to focus on:
1. Generative Creative Tools – for image, video, and copy generation at scale
2. Dynamic Creative Optimization (DCO) Platforms – to automate ad variations based on audience data
3. Creative Analytics Platforms – to get AI-driven insights on what’s working
4. Workflow Automation – for localization, resizing, and formatting at scale
What separates the winners:
1. AI is embedded into how work gets done and not just as a side experiment.
2. Brands need to focus on solving real business problems with clear outcomes.
3. Strong guardrails should be defined early to enable safe and fast execution.
4. Teams should combine creative thinking with the ability to direct AI effectively.
5. Brands should treat AI output as a starting point and refine it to reach quality.
9 Key Takeaways for Brands:
1. Define the brand clearly: so AI has a strong foundation to work from
2. Build scalable systems: to create consistency across markets and formats
3. Protect the human layer: keep taste, storytelling, and judgment human-led
4. Clarity fuels AI: better inputs lead to better outputs
5. Distinctiveness wins: stand out in a world of sameness
6. AI shifts the bottleneck: from production to direction and decision-making
7. Set clear goals: align AI efforts to measurable outcomes
8. Iterate continuously: test, learn, and refine over time
9. Define AI’s role: be clear on where it adds value and where it doesn’t
