The Ad Optimizer's Library of AI Tools: Copywriting, Graphics & Video Full Link Breaking

"A day in the life of an ad optimizer: checking account data at 7 a.m., writing copy at 10 a.m., creating material at 2 p.m., and adjusting placement plans at 9 p.m. ......"

An infomercial optimizer left a message at 2am saying, "Party A asked for 50 sets of copy and 100 images, so it looks like we'll have to work all night again tonight!"

Who can help these hard-working ad optimizers out?

The purpose of this article is to introduce how to use AI technology to realize the flow of material production, so as to free the energy of ad optimizers from the tedious material production, so that they can focus on more important data analysis and strategy optimization work.

Explosive copywriting fast generation: three steps to efficiently produce a manuscript

Core Tools Combo: ChatGPT + DeepSeek + Secreta Writing Cat

The operation process is explained in detail:

Step 1: Injecting AI with "Memory"

• Integrate past high-performing pop-up copy, product manuals, user reviews, etc., and import them into the AI tool (recommended) ChatGPT (the document analysis function).
  For example, for a beauty customer, 300 popular comments from the Xiaohongshu platform will be input into the AI system, and the AI can automatically extract high-value user pain point keywords such as "staying up all night with dull complexion" and "nourishing the skin without smothering acne".

Step 2: Build a copywriting generation formula

• Distill and combine key elements to form a formula for efficient copywriting generation:[User Pain Points] + [Core Product Selling Points] + [Scenario-based Marketing Hooks]The
  For example, to address the problem of late-night skin, you can generate a text: "Still worried about the haggard and dull face after working late at night? The new XX Serum brightens your complexion in three seconds, so you can look as good as when you return from vacation, even when you're facing a demanding client!"

Step 3: Copywriting Batch Fission and Testing

• utilization DeepSeek The "Multi-Modal Generation" feature provides one-click batch generation of copy variants with different moods and styles to meet diverse marketing needs.
• With the help of tools such as the Secret Tower Writing Cat for prohibited word detection, we can effectively avoid the risk of copywriting audit and ensure a smooth advertising process.

Advanced Tips:

• The top 5 conversion rate texts will be fed back to the AI system, and through continuous learning and optimization, the AI will be able to deeply grasp the account's exclusive "pop-up genes", so as to generate high-conversion texts that are more in line with the account's characteristics.

Creating Highly Clickable Material: The Golden Rules of AI Graphics

Core Tool Set: Midjourney + PS Beta + Canva AI

Material four-dimensional production methods:

Step 1: Targeted Material Feeding

• Upload images of bursts of material that have historically performed well, utilizing the Midjourney Tools such as "3D Stereoscopic" + "Strong Contrasting Color" + "Dynamic Splash Effect" can be used to analyze the structure of the Prompt and provide style references for subsequent AI drawings.

Step 2: Set negative directives to circumvent low-quality drawings

• Add negative directives such as "no cartoonish, no watermark" to Prompt to avoid generating cartoonish or low quality images with watermarks and enhance the professionalism of the material.
• Use the "--style raw" parameter to ensure that the resulting image maintains a realist style, effectively reducing the "plasticity" and making the material more realistic and attractive.

Step 3: Intelligent Material Extension

• When you enter ad copy into Canva and other platforms, AI can automatically match suitable templates and use Magic Edit and other functions to quickly replace background elements, thus realizing rapid iteration and scenario-based extension of materials.
  For example, for an education client, using PS Beta's "Generate Fill" feature, it only takes 5 minutes to expand a course promotional image into marketing materials for different scenarios, such as subway ads, elevator posters, and friend circle promotions.

Step 4: Material Compliance Testing

• Accessing services such as Tencent Cloud Content Security API, it conducts risk scanning of batch-generated materials, identifies and avoids violation risk points in the materials in advance, and ensures the safety and compliance of advertisement placement.

Industrialized production of short videos: 100 videos per day is no longer a dream

Core Toolset: Runway + Cutout AI + HeyGen

Fully automated short video production process (SOP):

Step 1: Intelligent Script Generation

• Entering product parameters and other information, the AI system can automatically generate short video scripts and intelligently recommend popular BGM references (for example, using suspense music library material at the key node of the "golden second") to enhance the attractiveness of the video.

Step 2: Portrait Digital Cloning

• Uploading video footage of a human being and training to generate an exclusive digital human image (the HeyGen platform requires only a 1-minute video sample to complete the cloning).
• Use tools like Runway to quickly create multi-scene video content by replacing backgrounds, costumes, props, and other elements of digital demo videos with a single click.

Step 3: Batch Video Mixing

• With the smart features of tools like Cut & Screen, it automatically cuts video footage and intelligently matches transitions to improve video editing efficiency.
• Automatically add e-commerce conversion components such as "price tag" and "countdown timer" in the key frame position to effectively improve the conversion effect of short videos.
• Measurement data shows that after a local life service client applied this process, it quickly produced 528 store scouting videos within 3 days, and the click-through rate (CTR) of the ads significantly increased by 23%.

Advanced Player Secret: AI Predicts Material Lifecycle

Core Tool Set: Google Analytics 4 + TensorFlow

Operational Steps:

Data return: Correlate and tag ad conversion data with material features (e.g., color tone, subtitle speed, product display duration, etc.) to build a foundation for multi-dimensional data analysis.

Model Training: Machine learning frameworks such as TensorFlow are used to build prediction models to predict the decline cycle of the material and provide data support for material optimization.

• An apparel brand analyzed the data and found that the decay rate of the "cold tone" + "3 seconds product close-up" clip was significantly slower than the warm tone clip, and the decay period was extended by 40%.

Intelligent warning: When the AI model monitors a continuous drop of 15% in the click-through rate of the material, the system will automatically trigger the AI material refurbishment command to update the material in time to maintain the effect of advertisement placement.

A Guide to Avoiding the Pitfalls of AI Collaboration

⚠️ Three Principles for Preventing "AI Rollovers":

Principle 1: Reject egalitarianism and select quality material

• To avoid indiscriminate batch generation of materials, it is recommended to use AI to quickly generate the first draft of 500 pieces of copy, and then select and retain the top 5% of high-quality copy through the "manual screening funnel" mechanism.
  The practical experience of a 3C brand client shows that after generating 200 sentences of product selling point copy through AI, only the more impactful and strong emotional copy such as "knocking down the bottom price" is retained in the manual filtering process.

Principle 2: Break through the homogenization trap and create differentiated material

• Incorporate conflicting elements such as "cyberpunk" + "ink style" into the Prompt prompts of AI painting tools such as Midjourney to break the homogenization of AI-generated materials and give them a unique style.
• Stable Diffusion's ControlNet feature locks down the structure of the product, preventing AI free play from distorting the material and ensuring that the material is highly consistent with the product itself.

Principle 3: Circumventing platform traffic restrictions and reducing the risk of non-compliance

• After using AI tools to generate materials in bulk, it is still necessary to perform "pixel-level fine-tuning", such as mirror flipping and local color block modification, as a way to reduce the algorithmic similarity of the materials and avoid the risk of platform flow limitation.
• We have established a dynamic update mechanism for the sensitive lexicon, and accessed the Zhihu "Know One Voice" public opinion interface, etc., so as to capture the latest risky words in real time, and update the prohibited lexicon in a timely manner to ensure the safety of the content.

Future Battlegrounds: Three Evolutionary Directions for AI Optimizers

Evolutionary direction I: cross-platform material genetic recombination

• Extracting the "rhythm gene" of the explosive material of the ShakeEn platform and successfully transplanting it to WeChat's Friend Circle advertisement placement to realize the reuse and maximize the value of the cross-platform material.
• A gaming client feeds infomercial creative with the popular "Pop-up Stunner" from Station B's second-generation videos, resulting in a significant increase in ad click-through rate (CTR) of 47%.

Evolutionary direction II: real-time hotspot blitzkrieg

• Real-time monitoring of microblogging hot search list, using ChatGPT to quickly generate hot spot copy, combined with DALL-E 3 and other tools to quickly create hot spot pictures, to realize the hot spot material production and on-line placement within 2 hours, to seize the first opportunity for marketing.

Evolutionary Direction 3: AI-Enabled "Anti-Common Sense" Strategies

• In some of the ad copy, "imperfect" elements around 5%, such as minor grammatical errors, are strategically retained to enhance the user's sense of authenticity and trust in the content.
• Use tools like Runway to generate "bug art" style material, such as glitchy, pixelated effects, etc., to attract the attention of Gen Z users with new and unique visual styles.

"The ad optimizer of the future is far from being a replacement for AI, but rather a commander of excellence in harnessing AI."

While competitors are still relying on traditional manual optimization methods, ad optimizers who are the first to master the AI arsenal are already able to use models to accurately predict traffic trends and lead marketing changes.

See here, take action now, choose an AI tool, start from generating 10 ad copy, let AI become your powerful digital assistant, and open a new era of intelligent ad optimization together.