Alex stared at the performance data for creative #47 on his screen.
As the head of user acquisition at a global mobile game publisher, his team had just launched a new anime-style RPG. The budget was there, but creative capacity had become the biggest bottleneck.
Designers were waiting for brief approvals. Media buyers were waiting for creatives to go live. The VP was asking why Return on Ad Spend (ROAS) was declining. Alex's daily mantra:
"We're not playing the game — the game is playing us. We're chasing creative deadlines while the market moves on."
What Alex was facing is the classic "Impossible Triangle" of modern ad campaigns:

| The Dilemma | |
|---|---|
| Need Volume | Cold start requires 10-20 creatives for A/B testing, but the team can only produce 2-3 per day |
| Need Precision | Creative data lives in spreadsheets, campaign data in ad platforms, and creative files on designers' laptops |
| Need Speed | Creative lifespan is just 3-5 days, but the analysis + iteration cycle takes 10-15 days |
Alex's dilemma is being replayed at scale across the global advertising industry in 2026. Nearly half of all advertisers are trapped in the same system.
Tension 1: Production Capacity vs. Demand
"You never know which creative will be a hit. Platform algorithms, user preferences, competitive landscape, even the day's trending topics — everything is in flux. A creative you think is 'brilliant' might flop, while a casual throwaway might become your best performer."
According toAppsFlyer's State of Creative Optimization 2025— which analyzed 1.1 million creative variations and $2.4 billion in ad spend — the top 2% of creatives still capture 53% of gaming marketing budgets. The only way to find winners is through relentless creative iteration and testing.
Tension 2: Data vs. Creative
"I have the data, but I can't make the data create ads for me."
A User Acquisition lead at a major gaming studio put it bluntly: data is fragmented across platforms, dimensions are inconsistent, and update frequencies don't align. Teams spend hours every day manually consolidating spreadsheetsjust to get basic reporting — let alone deep analysis of "creative type × audience segment × monetization outcome."
Creative data in Excel. Campaign data in ad platforms. Creative files on designers' laptops — three systems doing their own thing.
Tension 3: Speed vs. Creative Lifespan
"By the time I figure out what works, the trend is already dead."
Creative fatigue is accelerating, with ad lifespans shrinking from weeks to just 3-5 days. Yet traditional A/B testing cycles still take 10-15 days. As Singular's 2025 creative fatigue report notes, advertisers are burning through creatives faster than they can replace them.
"One person manages 300 ad plans a day — mistakes are inevitable." "Why did the good creative work? Why did the bad one fail?" "Data silos, inaccurate attribution, delayed decisions."
Alex has tried nearly every AI video generation tool on the market. He can list the pros and cons of each.
But the problem isn't that the tools aren't good enough.
AI tools can already solve the "single ad video" problem quite well.
Give it a prompt, and it produces a polished, well-paced video. The visuals, camera movement, music — all on point.
But the problem is: running ad campaigns isn't about making one. It's about making a hundred. A thousand.
When "single generation" becomes "mass production," the question shifts from "Can AI do it?" to "How does AI work with data?"
The ad industry doesn't need "a tool that generates videos." It needs "a system that generates ads" — one that connects data insights, creative production, and campaign optimization into a single loop.
The industry consensus in 2026 is clear: it's about the workflow, not the model. The breakthrough isn't in "better AI tools" — it's in "bringing AI closer to your data."

Hologres builds its solution around a simple but powerful idea:
Hologres isn't just "an AI creative tool" — it's a unified creative production and analytics platform.
Traditional approach: Use Tool A for creative generation, Platform B for ad delivery, System C for data analytics — three tools, three data migrations, three teams to maintain.
Hologres approach: Creative generation and campaign analytics run on the same engine. Analysts use a single SQL connection to both generate ads and analyze their performance.
Step 1: Creative Ingestion and Unified Asset Management
Using Object Table, Hologres automatically maps videos, images, and documents stored on OSS into database records, creating a unified creative asset library. External creatives, internal assets, historical materials — all in one table.
Step 2: Intelligent Tagging and Matching
Leveraging Dynamic Table incremental computation and AI Function, the system automatically analyzes creatives, generating multi-dimensional structured tags (style, characters, scenes, mood, etc.) and correlating them with campaign performance data to answer "which creative works best in which context."

Step 3: AI-Powered Creative Generation
Based on the tagging system and prompt engineering, the system calls Qwen models to generate storyboard scripts, then calls the Wan model to produce video creatives. The entire pipeline is SQL-driven, producing results in minutes.

Step 4: Campaign Analytics and Intelligent Optimization
After ads go live, Hologres ingests cross-platform campaign data (spend, CTR, CVR, ROAS, etc.) and correlates it with the creative tagging system, automatically answering "which creative works best on which channel for which audience." AI Function performs intelligent attribution and trend prediction on campaign data, outputting optimization recommendations that feed back into the next round of creative generation — forming a complete "generate → launch → analyze → optimize" loop. This isn't two systems bolted together — it's a natural continuation within the same engine: the same SQL you used to generate creatives now analyzes campaign performance.
The entire architecture is built around "one dataset, one compute engine, one closed loop," organized in four layers:
Layer 1: Data Sources + AI Models On the data side, Hologres uses Object Table to map videos, images, and documents on OSS into database records, while connecting to MaxCompute and operational databases. On the AI side, it integrates Qwen models (text reasoning, multimodal understanding, image generation), Wan (video generation), and text-embedding (vectorization) through Alibaba Cloud's Model Studio platform.
Layer 2: Hologres Unified Compute Engine Three core capabilities:
Built-in multi-modal search and analytics (OLAP, vector search, full-text search, hybrid search), plus a Creative-Campaign Correlation Engine — Hologres' key differentiator from pure AI creative tools: creative tags and campaign performance data are correlated within the same engine, answering "which creative works best on which channel for which audience."
Layer 3: Dual Output — Creative Generation + Campaign Analytics
Layer 4: Ad Platforms (Data Feedback Loop) Spend, CTR, CVR, ROAS data from Meta Ads, Google Ads, TikTok Ads, AppLovin, and other platforms flow back into Hologres in real time, correlating with creative data in the same table.
The Loop: Analytics Feeds the Next Round of Creative Generation The "winner element guide" from campaign analysis becomes the input for the next creative generation cycle, forming an automated "generate → launch → analyze → optimize" loop. No cross-system switching, no data migration, no tool changes — one SQL connection generates ads and understands them.

┌─────────────────────────────────────────────────────────────────────────┐
│ Hologres Intelligent Creative & Analytics Platform │
├─────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────────────────────────┐ │
│ │ Data Sources │ │ AI Models (Model Studio) │ │
│ │ │ │ │ │
│ │ OSS Storage │ │ Text: Qwen / DeepSeek │ │
│ │ Images/Video │ │ Multimodal: Qwen-VL │ │
│ │ MaxCompute │ │ Generation: Qwen-image / Wan │ │
│ │ Biz Databases│ │ Embedding: text-embedding │ │
│ └──────┬───────┘ └──────────────┬───────────────────┘ │
│ │ │ │
│ ▼ ▼ │
│ ┌──────────────────────────────────────────────────────────────────┐ │
│ │ Hologres Unified Compute Engine │ │
│ │ │ │
│ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ │
│ │ │ Object Table│ │AI Function │ │ Dynamic Table │ │ │
│ │ │ Multimodal │ │ SQL→LLM │ │ Incremental │ │ │
│ │ │ Mapping │ │ │ │ Computation │ │ │
│ │ └─────────────┘ └─────────────┘ └─────────────────┘ │ │
│ │ │ │
│ │ ┌────────────────────────────────────────────────────────────┐ │ │
│ │ │ Multi-Modal Search & Analytics │ │ │
│ │ │ OLAP | Vector Search | Full-Text | Hybrid | Point Query │ │ │
│ │ └────────────────────────────────────────────────────────────┘ │ │
│ │ │ │
│ │ ┌────────────────────────────────────────────────────────────┐ │ │
│ │ │ Creative-Campaign Correlation Engine │ │ │
│ │ │ Creative Tags × Campaign Performance → Attribution | ROI │ │ │
│ │ └────────────────────────────────────────────────────────────┘ │ │
│ └──────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌──────────────┐ ┌──────────────────────────────────┐ │
│ │ Creative Out│ │ Campaign Analytics Out │ │
│ │ │ │ │ │
│ │ Ad Copy │ │ Dashboards | Attribution Reports │ │
│ │ Storyboards │ │Audience Insights | Recommendations│ │
│ │ Video Assets│ │ │ │
│ │ Multilingual│ │ │ │
│ └──────────────┘ └──────────────┬───────────────────┘ │
│ │ │ │
│ └────────────── Closed Loop ←─────────┘ │
│ Analytics feeds next creative cycle
Key Architecture Benefits:
Hologres includes a rich set of AI Functions, callable through standard SQL:
| Function | Capability | Example Use Case |
|---|---|---|
| ai_gen | Intelligent content generation | Marketing copy, ad scripts, creative concepts |
| ai_embed | Embedding vectorization | Creative semantic search, similarity matching |
| ai_classify | Text classification | Auto-tagging creative styles |
| ai_extract | Structured information extraction | Extract tags from video descriptions |
| ai_summarize | Intelligent text summarization | Long copy condensation |
| ai_translate | Multilingual intelligent translation | Global ad localization |
| ai_analyze_sentiment | Sentiment analysis | Ad comment sentiment tracking |
| ai_parse_document | Multimodal document recognition | PDF/image to text conversion |
Your challenge: More Martech tools, but data silos make ROAS harder to calculate. AI creative sounds great, but new tools mean new learning curves, new data migrations, new security risks.
What Hologres changes: AI creative generation embedded directly in your existing data warehouse. No new tools, no new teams, no data migration. Your analysts use SQL to go from data insight to ad generation end-to-end.
"Query Your Data, Generate Ads" — do what was impossible before, using the tools you already know.
Your challenge: You need hundreds of ad variants daily for A/B testing, but manual production can't keep up with campaign pacing. By the time a creative tests out, the market window has closed.
What Hologres changes: SQL batch generation — one query produces hundreds or thousands of ad variants. After launch, the same system analyzes performance data and tells you which creative works on which channel for which audience. The cycle from creative testing to winner validation shrinks from 10-15 days to minutes, all on one platform.
Creative production speed up 10x, testing cycle down 90%.
Your challenge: Business teams want AI creative capabilities, but new tools mean new data pipelines, new operational overhead, new tech stacks.
What Hologres changes: Extend your existing SQL skills with AI capabilities. No Python, no new systems. AI Function makes LLM calls as simple as SUM() or COUNT().
From "data analyst" to "AI-driven content engineer" — no career change, just a tool upgrade.
Your challenge: Multi-client data needs secure isolation, multi-platform campaigns need unified workflows, global ads need multilingual support.
What Hologres changes: Enterprise-grade security architecture with built-in encryption and compliance controls. One platform supporting multi-client, multi-platform, multilingual workflows.
Secure, scalable, global — agency-grade creative infrastructure.
A global mobile game publisher built its own intelligent User Acquisition platform centered on data-driven automation for cross-channel media buying and precision user operations.
Before Hologres:
After Hologres:

The advertising industry in 2026 is at a crossroads: teams struggling with fragmented tools on one side, teams generating ad creatives with a single SQL query and driving data-informed campaigns on the other.
The gap isn't in AI capability — AI is within reach.
The gap is in whether you've brought AI close to your data.
Hologres' answer is straightforward:
It doesn't just help you generate ads — it helps you understand why they work. No new tools, no new languages, no data migration. Use the SQL you already know, and turn your data warehouse into a smart factory that both produces ads and reads them.
Want to explore Hologres technical details or discuss your use case?
👉 Try Hologres: Alibaba Cloud Hologres
Pay-as-you-go pricing, or monthly/annual subscriptions.
Explore the open-source Hologres AI CLI and skills on GitHub:
github.com/aliyun/hologres-ai-plugins
Industry data sources:AppsFlyer — The State of Creative Optimization: 2025 Edition,HubSpot — 2026 State of Marketing Report,Adobe — AI and Digital Trends 2026,Singular — Creative Fatigue in 2025,Search Engine Land — Your Ads Are Dying,AppGrowing Global — Mobile Game Marketing White Paper,RevenueCat — Detecting Ad Fatigue in 2025.
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