In 2025, the global gaming advertising market size exceeded 180 billion US dollars, yet the industry average ROI is only 1.37—earning only $1.37 for every $1 spent on advertising.
In the current era where the traffic dividend is exhausted, extensive deployment is dead, and refined operations reign supreme.
Today, we will combine the latest overseas cases from 2024-2025 to deeply analyze 5 practical A/B testing techniques to help you achieve exponential growth in advertising effectiveness.
1. Multi-dimensional Material Testing: Finding the User "Click Password"
Case Study: 37GAMES "Doomsday Rumble" Material Iteration
37GAMES, in promoting "Doomsday Rumble," conducted comparative tests of 2D and 3D materials through the Liftoff platform.
The results revealed that the combination of 3D visuals + narrative plot in advertisements led to a 264% surge in installations, with D7 ROAS exceeding the target by 40%.
The team further divided "UI interaction" and "gameplay demonstration" into 12 testing dimensions, ultimately refining the golden combination of "3D character close-ups + limited-time gift packs," which increased the ad CTR by 37%.
Operational Steps:
Element Decomposition: Divide the material into 12 dimensions such as BGM, visual scenes, character actions, etc.
AB Grouping: Create a control group (original material) and an experimental group (modify a single element)
Data Tracking: Monitor core metrics such as click-through rate, completion rate, conversion rate, etc., through the platform
Combination Optimization: Combine the best-performing elements into new materials
Industry Insight:
The Australian casual game "Farming Game" discovered through heat engine testing that the combination of "dynamic expressions + limited-time discounts" reduced CPI by 15% and increased the paid conversion rate by 22%.
Data shows that in 2024, the lifecycle of quality materials has shortened to 3.2 days, requiring a daily material update rate of 30%.
2. Bulk Advertising Matrix Testing: Breaking Through Media Algorithm Limitations
Case Study: T Games Chess Game Matrix Deployment
T Games, in promoting "CashPusher," created 3000 ads in a single day through the NetMarvel platform, covering 200 targeted combinations.
The tests found that the CPI for the targeted group of "35 years old + female + payment history" was 44% lower than the regular group.
The team quickly replicated the successful model, expanding the advertising matrix to 5000 ads, achieving a first-day ROI of over 70%, becoming the TOP1 channel in the US market.
Technical Points:
Smart Templates: Save commonly used targeting, bidding, and copy combinations as templates
Material Deduplication: The system automatically avoids the same material being allocated repeatedly
Dynamic Tuning: Temporarily pause advertising plans with an ROI below 1.5 in real-time
Industry Data:
In 2025, advertisers using bulk creation tools had their testing efficiency increased by 8.6 times compared to manual operations.
3. Attribution Model Comparative Testing: Locking in High-Value Users
Case Study: "Mushroom Hero Legend" Snapchat Channel Optimization
4399, in promoting "Mushroom Hero Legend," compared the 28/1 attribution model (28 days click + 1 day exposure) with a 7/0 optimization window.
The results showed that the 7/0 model increased Android ROI by 110% and reduced CPI by 29%.
The team further targeted "high-paying users," increasing their conversion rate by 75%.
Model Selection Logic:
Short-term Burst: Use the 7/0 model for rapid volume increase
Long-term Value: Combine the U-shaped attribution model to assess the full-link contribution
Dynamic Switching: Adjust the model according to the product stage (e.g., use 7/0 during the testing phase, 28/1 during the mature phase)
Industry Trend:
In 2025, advertisers using a combination of multiple attribution models had a 53% higher LTV for their users compared to those using a single model.
A certain SLG game, through the combination of "linear attribution + time decay," accurately identified that the "third click" contributed 41% of the paid conversion.
4. AI-Driven Dynamic Bidding Testing: Cracking the Traffic Fluctuation Code
Case Study: Pixel Edge "Farming Game" Algorithm Optimization
The Australian team Pixel Edge, in promoting "Farming Game," integrated the oCPA intelligent bidding system of the heat engine.
By real-time feedback of payment data, the algorithm automatically adjusted the bidding strategy.
The tests showed that the ROI of the AI group was 126.9% higher than that of the manual bidding group, and the cost of acquiring high-value users decreased by 38%.
Algorithm Core Logic:
Real-time Bidding: Dynamically adjust bids based on current traffic quality
User Layering: Identify "high-potential paying users" and bid at a premium
Budget Allocation: Allocate 80% of the budget to advertising plans with an ROI>2
Technical Breakthrough:
In 2024, a certain advertising platform launched the "predictive bidding" feature, using LSTM neural networks to predict the next day's traffic trends, allowing advertisers to strategize 24 hours in advance.
A certain idle game using this feature saw its ROI increase by 67% during weekend peak traffic periods.
5. Version Update Node Testing: Maximizing Traffic Dividends
Case Study: "Honor of Kings" Spring Festival Version Marketing
"Honor of Kings," in its 2025 Spring Festival release of the new 10v10 gameplay, determined the optimal deployment strategy through A/B testing:
Experimental Group: Intensively deployed "new gameplay preview" 3 days before the version update
Control Group: Regular version update publicity
Data showed that the first-day DAU of the experimental group was 42% higher than that of the control group, and the paid conversion rate increased by 29%.
The team further combined "city cultural tourism linkage" and "celebrity endorsement" for combined testing, pushing the overall marketing ROI to 4.8.
Version Update Testing Key Points:
Preheating Rhythm: Release suspense in stages (e.g., character silhouette→skill demonstration→gameplay details)
Material Combination: Combine version highlights with festival elements (e.g., Spring Festival limited skins)
Data Closure: Feedback post-update 7-day retention and payment data to optimize subsequent deployments
Conclusion
In the era of AI and algorithm-dominated advertising, a 500% ROI increase is no longer a myth.
Through material atomization testing, advertising matrix layout, dynamic switching of attribution models, AI intelligent bidding, and precise version update node blasting, advertisers are building a "data-driven" deployment system.
In the future, those who integrate A/B testing into every marketing cell will harvest the last traffic dividends in the 200 billion dollar advertising battlefield.
After all, while others are still "guessing" in advertising, you are already using "mathematical formulas" to make money.
