Inside Spinta: How We Build High-Converting AI Video Campaigns

Introduction Turning Intelligence into Impact

AI video production isn’t just about speed it’s about precision.

At Spinta Digital, our campaigns aren’t random creative experiments; they’re engineered systems built to attract, engage, and convert audiences.

In this behind-the-scenes breakdown, we’ll show how our team uses AI tools like Sora, Kling, Google Veo 3, HeyGen, Eleven Labs, and Google Flow to create measurable performance lifts and how one brand achieved 3.8× ROAS using our AI video process.

The Challenge – Fast Growth, Slow Content

A mid-sized D2C brand approached us with a common problem:

• Their marketing team could only produce 1–2 video ads per month.
  
• Traditional shoots were costing ₹3–5L each.
  
• Creative refresh rates couldn’t keep up with Meta and YouTube algorithms.
  
• ROAS had dropped below 2×.
  
  

They didn’t lack creativity they lacked speed.

Our task: build an AI-powered creative system that could produce new ad variants weekly and bring efficiency back to performance marketing.

Phase One – Building the Creative Intelligence Layer

The first step was data-driven discovery.
We audited their ad accounts, landing pages, and creative performance from the last six months.

AI analytics surfaced patterns:

• Lifestyle visuals outperformed studio shots by 47 %.
  
• Voiceovers with calm tones had 25 % higher retention.
  
• Blue backgrounds correlated with a 30 % better click-through rate.
  
  

We fed these insights into Google Flow, creating a creative training model for their brand the foundation of every video we’d make going forward.

Phase Two – The AI Video Production Pipeline

Once strategy was set, we activated our hybrid AI-human workflow.

Within 72 hours, we produced the first batch of 8 ad variants each with different hooks, scenes, and CTAs.

Phase Three – Testing and Feedback Loop

We launched the campaign across Meta and YouTube with modest budgets for testing.
Using Flow’s analytics dashboard, AI tracked which ad variations performed best in real time.

After 10 days:

• 2 top-performing videos outperformed baseline ads by 115 % in CTR.
  
• CPA dropped from ₹360 → ₹190.
  
• Engagement time doubled (7.8 → 15.6 seconds).
  
  

We then refined scripts, replaced weaker scenes, and regenerated improved visuals in Kling and Veo 3 all within 48 hours.

This continuous testing loop is what we call creative compounding:

Every ad makes the next one smarter.

Phase Four – Personalisation at Scale

Next, we introduced personalised AI video variants.

Using HeyGen avatars and Eleven Labs, we localised voiceovers for three audience segments urban, aspirational, and family-focused buyers.

Results:

• Personalised versions delivered 28 % higher CTR.
  
• Bounce rates from retargeting ads fell by 35 %.
  
• “Add to cart” actions increased by 41 %.
  
  

The key insight?

Personalisation drives conversion not by changing the message, but by changing how the message feels.

Phase Five – Scaling the Creative Engine

Once winning patterns were clear, we scaled.

Using Google Flow, we automated weekly ad variant generation, each aligned with new offers, seasons, and promotions.

• 10 new AI videos produced every week
  
• 5–7 live ad variants running per audience
  
• All formatted automatically for Meta, Reels, and YouTube Shorts
  
  

By month three, the client’s campaign cadence had completely transformed from static to dynamic marketing.

The Results – Numbers That Tell the Story

The difference wasn’t just quantitative  it was strategic.
They now had creative velocity: the ability to test, learn, and pivot without waiting on expensive reshoots.

Why It Worked

Creative Volume = Learning Speed

AI video systems allowed us to test more ideas faster.

Emotional Relevance

Eleven Labs voice models and Kling avatars made the content feel personal and real.

Adaptive Optimisation

Google Flow’s data engine guided each new iteration based on performance analytics.

Brand Consistency

Templates ensured every AI-generated asset aligned with brand tone, colour, and message.

Human Oversight

Our editors and strategists added emotional timing, ensuring AI didn’t drift into monotony.

Together, these elements formed a repeatable, scalable content system.

How We Replicate This Framework for Other Brands

Every client’s AI-video journey follows five core stages:

Discover: Analyse data, audience, and brand personality.
Design: Build creative frameworks and prompts.
Develop: Generate and refine videos using AI tools.
Deploy: Test variants and measure engagement metrics.
Deepen: Feed learnings back into the creative AI model.

It’s not a one-time campaign; it’s a living ecosystem that evolves with audience data.

What This Means for Marketers in 2026

AI video marketing is no longer experimental  it’s operational.

The brands winning today are those that:

• Launch 10x more creative variations than competitors.
  
• Learn faster through data loops.
  
• Combine automation with authenticity.
  
  

By 2027, AI video pipelines will be as essential as CRM systems.
The early adopters are already seeing exponential gains.

Client Perspective

“Spinta’s AI videos changed our marketing speed completely. We now go from concept to campaign in under a week and every month, our ROAS keeps climbing.”  CMO, D2C Consumer Brand

That testimonial sums up what the technology delivers: agility, clarity, and results.

Final Takeaway  Creative Systems, Not One-Off Videos

The future of video marketing isn’t about producing content; it’s about building content engines.
At Spinta Digital, we turn AI video creation into an operational advantage blending data, design, and direction to keep your campaigns learning and growing.

Whether you’re running e-commerce ads, SaaS explainers, or brand stories  AI-driven video systems can cut cost, shorten timelines, and multiply conversions.

Ready to See How an AI Video System Could Work for You?

Let’s design a high-converting AI video engine for your business tailored to your goals, audiences, and ad funnels.