AI Creative Analytics 101: How AdSkate Helps Brands Navigate Walled Gardens

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Why Creative Analytics Matters in 2025

In 2025, artificial intelligence has become the engine of digital advertising. Platforms like Google, Meta, and TikTok run on complex AI systems that optimize campaigns in real time. Yet while these platforms deliver reach and automation, marketers are realizing that campaign success still hinges on the creative itself.

An ad’s ability to capture attention, resonate emotionally, and inspire action depends on elements like tone, visuals, and calls-to-action. Without clear insights into which components work, advertisers risk wasting budget. That’s why AI creative analytics is becoming one of the most important tools in modern marketing.

As Akaash Ramakrishnan, co-founder and CEO of AdSkate, explained in a recent interview with tipsheet.ai:

“We enable the advertiser to understand their creatives better by breaking the creative down into its elemental composition. So, it’s different aspects such as image, tone, calls-to-action, color, audio style, music and many other components.”

Recently featured on tipsheet.ai, AdSkate is positioning itself at the forefront of this shift by helping brands and agencies analyze, test, and optimize creative before it reaches the walled gardens. You can read the full interview here.

The Problem: Walled Gardens and Limited Transparency

Marketers face a common frustration: while walled gardens like Google and Meta offer powerful AI-driven campaign optimization, they rarely reveal the why behind performance. Advertisers may see higher conversions, but they don’t know which creative elements, color palette, tone of voice, or soundtrack, were responsible.

These platforms are primarily designed to maximize revenue. As Ramakrishnan explained:

“Most of the AI systems that are created by the ‘walled gardens’ are about fundamentally pouring more money into the campaign that you run in that specific platform – so essentially optimizing for a higher ad spend.”

This lack of transparency leaves brands flying blind. They know whether a campaign worked, but not what made it work. Without that knowledge, future campaigns often repeat the same inefficiencies.

AdSkate’s Solution: AI-Powered Creative Analytics

AdSkate tackles this problem by shifting the focus from platform-level optimization to creative-level insight. Its system uses multiple AI models to evaluate ads across dimensions like:

• Visual composition (objects, colors, layout)
• Audio analysis (tone, soundtrack, music)
• Messaging (calls-to-action, emotional tone, phrasing)
• Format performance (image, video, or mixed media)
  

Instead of relying on the platforms to provide incomplete data, AdSkate delivers granular insights that apply across ecosystems. As Ramakrishnan explained, the platform is designed to be neutral:

“We essentially are agnostic when it comes to the different platforms that exist in the ecosystem, and we’re able to collect a cohort of information that is applicable across all their marketer’s campaigns.”

This cross-platform approach ensures advertisers are optimizing for creative performance, not just platform revenue.

Pre-Campaign Testing with Synthetic Audiences

AdSkate has also built the ability to test ads before a campaign launches. Rather than spending heavily on live A/B tests, brands can run creatives through AdSkate’s synthetic audience models to predict resonance with different demographics.

These synthetic audiences are built on detailed ethnographic and demographic research, offering insights into how real audiences are likely to respond.

“When you run the creative – a static image or a video – you’re getting a much more in depth understanding of whether that ad works well,” Ramakrishnan explained.

For example, a retailer launching a holiday campaign with five creative variations can quickly identify which visuals resonate best with younger shoppers versus older demographics. Performance marketers can test copy variations to see which phrasing drives the highest likelihood of conversion, all before spending a single dollar in media.

Humanizing the Audience

AI-driven platforms often encourage advertisers to create hundreds of automated ad variations in search of incremental gains. But more doesn’t always mean better.

As Ramakrishnan emphasized:

“I wouldn’t say that having a mass quantity of creatives is better, but having a set amount of creatives is good and enables better engagement. I think one more important factor is to humanize the audience.”

AdSkate helps marketers shift from quantity to quality by focusing on:

• Emotional resonance: Which visuals and messages spark trust, joy, or urgency.
• Cultural nuance: How different demographics interpret messaging.
• Authenticity: Ensuring that campaigns feel human, not purely algorithmic.
  

The result is a smarter, more empathetic approach to creative development, one that respects the audience and builds stronger long-term brand relationships.

Who Benefits: Agencies, Brands, and Performance Marketers

AdSkate’s flexibility means it can deliver value to multiple groups in the marketing ecosystem.

• Agencies: Gain cross-platform transparency, helping them compare campaign performance across clients and ecosystems.
• Brands: Use pre-campaign testing to reduce guesswork in major launches.
• Performance Marketers: Optimize for CTR, conversions, and engagement with actionable creative insights.
  

As Ramakrishnan noted, marketers today are focused on deeper metrics:

“Usually they look at click through rate. They’ll also look at conversions. People have gone beyond just looking at impressions – in video, a lot of marketers are focused on video plays and also the number of seconds people are spending.”

Whether the goal is awareness, engagement, or conversion, AdSkate helps ensure creatives are designed for measurable impact.

The Bigger Picture: Integrating Into the AI Ecosystem

Looking ahead, AdSkate isn’t just building standalone tools. The company is positioning itself as a core part of the AI advertising ecosystem.

By embracing the Model Context Protocol (MCP), AdSkate integrates with leading AI systems like Claude, Gemini, and ChatGPT. This allows agencies to centralize workflows, bringing creative analytics into the same environments where they already manage strategy and execution.

As Ramakrishnan explained:

“We felt integrating our solution into Claude, Gemini and ChatGPT was an imperative for our company. And, it’s likely going to be imperative for all the ad technologies that are being used today.”

This vision ensures that creative insights won’t sit in isolation, they’ll flow seamlessly into the AI-driven tools marketers already rely on.

Key Takeaways & Client Advice

For marketers evaluating AI solutions, the most valuable tools are often the simplest. As Ramakrishnan put it:

“If a solution can answer a question in a manner which is easy enough for someone to digest, then that solution has a lot of value, power and impact.”

Here are five guiding principles for evaluating AI creative tools:

1. Test creatives before launch – reduce wasted spend with synthetic audiences.
2. Look beyond walled gardens – independent analytics provide transparency.
3. Optimize for quality, not quantity – fewer, smarter creatives deliver stronger engagement.
4. Seek granularity – choose solutions that break creatives down into components.
5. Prioritize simplicity – tools must be intuitive to drive adoption.
   

The Future of AI Creative Analytics

Advertising is entering a new era. Walled gardens will always optimize for their bottom line, but marketers need insights that optimize for creative performance and human connection.

By combining synthetic audience testing, creative breakdowns, and platform-agnostic insights, AdSkate demonstrates how AI can make advertising more effective, efficient, and empathetic. The message is clear: the future of advertising isn’t about creating more ads, it’s about creating smarter ads.

To explore more about AdSkate’s vision, read the full tipsheet.ai interview here.