Unlocking AI Ad Black Boxes with Antsomi CDP

What is AI Advertising?

This refers to methods using Artificial Intelligence (AI) to optimize advertising campaigns. AI streamlines a wide range of tasks—including target selection, personalization of ad content, automated bidding, and creative generation—to achieve more effective ad delivery.

What AI Advertising Can Do (Merits)

Automation by AI has streamlined vast amounts of work previously done by humans and delivered certain results.

What AI Advertising Cannot Do (Challenges)

However, many marketers are now facing new barriers.

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  Lack of Transparency (The Black Box):
  The logic behind "why AI chose that target" remains unknown.

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  Risk of Homogenization:
  If data is biased, ads may concentrate on specific demographics (Filter Bubbles), or brand ads may look too similar to competitors.

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  Limits of Customer Understanding:
  Because AI is limited to data measurable on the platform, it cannot incorporate offline behavior or a company's unique proprietary data (First-party data).

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  Lack of Human Insight:
  Since AI does not possess human-like intuition or the ability to understand complex emotions, there are limits to its ability to set strategic direction.

AI is extremely capable, but relying too heavily on data measurable only within specific economic ecosystems risks saturating effectiveness and homogenizing the brand experience. What is needed now is not to use AI merely as an "automation tool," but to inject human-unique strategies and insights to elevate AI into a true "partner." The key to this is Antsomi CDP.

A. Bias in Platform Data

Platform AI tends to optimize based on user characteristics measurable within its own ecosystem. As a result, "filter bubbles" occur where ads concentrate on specific groups, and because brands create content based on similar data, differentiation becomes difficult.

B. Insufficient Use of First-Party Data

Many companies are not fully utilizing the valuable first-party data (customer data collected by the company itself) they possess. While AI is efficient, it is difficult for AI alone to deeply understand the "face" of the "high-LTV (Lifetime Value) loyal customers" that a company truly wants to acquire.

[Without CDP: AI Advertising Only]

AI advertising judges customers mainly based on data held by each ad platform (click history, search behavior, etc.). In this case, AI can only "recognize" fragmented online behaviors.

• ❌ What is seen: Behavior within the platform (e.g., "Person who clicked this ad").
• ❌ What is NOT seen: Information such as what they bought in your physical store or what inquiries they made to customer support.

Therefore, the customer persona derived by AI is limited. As a result, there is a risk that ads become standardized or that you miss out on the loyal customers you should be targeting.

[With Antsomi CDP: Utilizing CDP]

By utilizing Antsomi CDP, you can centrally integrate and manage all customer data, including offline purchasing data, CRM data, and behavioral history. This diverse data is crucial for making AI "recognize" the full picture of the customer.

Antsomi CDP unlocks the AI black box, "visualizes" an accurate and comprehensive "customer face", and dramatically improves customer understanding.

Summary: Difference Depending on CDP Presence

What is "Strategically Guiding AI"?

It means incorporating elements that AI alone cannot possess—such as a marketer's strategic thinking—into the AI's learning process via the CDP. This allows AI to evolve from a mere automation tool into a "partner" that understands human intent.

Difference in Strategy

3 Concrete Approaches

Case 1: Finance & Insurance Industry

Rewriting AI's Judgment Criteria to Reduce Cost Per Acquisition (CPA)

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  Challenge: AI tended to learn only from immediate "web applications," resulting in low-quality leads.

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  Solution: Fed back "final contract data" and "attribute information" as Signals that the AI should prioritize.

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  Result: Achieved dramatic results in improving conversion numbers and reducing CPA.

Case 2: D2C & EC Industry

Increasing Conversions with Data Completion Not Reliant on Cookies

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  Challenge: With the cookie-less era, AI could not correctly grasp "who bought the product," making optimization less effective.

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  Solution: Implemented "Conversion API (CAPI)" via CDP to send purchase data directly to the AI, resolving learning "leaks."

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  Result: Ad operation precision restored to top-tier levels.