Mintegral T-CPE Optimizer
【What is Target CPE Campaign】
Target CPE stands for Target Cost Per Engagement, which is an advertising strategy offered by Mintegral to optimize the cost of events. It leverages Mintegral's algorithmic capabilities to optimize the Day 0 or Day 7 cost per target event on unique device basis set by the advertiser (currently only supports optimization of purchase events), and charges based on an oCPI (Optimized Cost Per Install) model.
 This approach effectively controls the cost of target events and improves advertising effectiveness.
（oCPI is an abbreviation for Optimized Cost Per Install, a non-fixed pricing model based on deeper user level metrics according to the optimization goals）
●For a detailed introduction to Target CPE Campaign, please refer to 
﻿Introduction to Mintegral Target CPE Campaign﻿
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【Before you begin】
Requirements for Starting a Target CPE Campaign
Products suitable for testing
For products with a revenue share of over 70% from in-app purchases, the promotion goal is mainly to attract paying users.
Test conditions
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（The target product needs to meet condition1 at least）
Condition1: all network installs and events postback (Required)
For D0 Target CPE testing, it is necessary to enable all network installs and events postback at least 7 days in advance and correctly configure the mapping for in-app purchase event category. 
For D7 Target CPE testing, all network installs and events postback should be enabled at least 14 days in advance, along with the correct configuration of in-app purchase event category mapping. 
Condition2: Requirements for the number of events across all network (Optional)
The average daily number of all network D0/D7 unique paying devices in the corresponding region over the past week should reach a minimum of 100 devices.
Condition3: CPI data accumulation (Optional)
CPI Offer should be delivered on Mintegral for at least 7 days in advance.
Notes
How to configure mapping?
●Select "Manage Event" and add event, fill in the "Package Name" and the original event name, and select "Purchase" as "Mintegral Event".
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●For more data postback, please refer to 
﻿Mintegral Revenue Postback Guidelines﻿
Events postback suggestion
We highly recommend that you forward not only purchase data but also other in-app events across all networks (such as registration, game levels, character creation, etc.). This will enable the algorithmic models to learn from a multidimensional user data and reach high-value users more effectively.
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【Campaign Set Up】
Target CPE Campaign Settings Guide
Set Up Campaign
Step 1: 
 Create an ad campaign (or use an existing one).
Set Up Offer
Step 2: Choosing an existing Campaign and add a new offer
●Quickly create a new ad offer by duplicating an existing one using Quick Add.
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Step 3: Fill out the basic information
●Select "Target CPE" as the Bid Goal.
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●Naming the offer, it is recommended to choose a later date as the start date for promotion, and manually start it after the offer is ready.
●Note: If you are unable to see the "Target CPE" option under Bid Type, please contact Mintegral team at growth@mintegral.com, requesting them to enable Target CPE. Make sure to also add your Mintegral user name, and email used to create your account.
Step 4: Choosing targeting options
●Select specific countries
●We suggest minimize the use of Advanced Targeting
Step 5: Set bid type and budget
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Optimization goals suggestion:
We suggest you set the Target CPE goal in Mintegral based on the D0 or D7 cost per unique paying user across all networks from user acquisition in the target region.
●D0 cost per unique paying user = Total spend on user acquisition across all networks/D0 unique paying user (excluding organic users)
●D7 cost per unique paying user = Total spend on user acquisition across all networks/D7 unique paying user (excluding organic users)
Step 6: Set budget
●If the offer is running in multiple countries/regions, different budgets can be set for each region.
●We recommend setting a daily budget of at least 10 times the target event price (Daily Budget = 10 * Target CPE), and the minimum daily budget should be $200. (For example, if Advertiser A sets a Target CPE price of $60, we suggest setting a daily budget to at least $600.) This will help avoid insufficient budget constraints that could hinder progress in subsequent stages of model optimization.
Step 7: Upload creatives
●T-CPE offers are default targeted at all ad type, we suggest to upload creative sizes and types as complete as possible to fully explore the traffic. The actual ad types used will be determined by the creatives you upload, and the system will automatically fill in the available ad types that can be covered.
●We highly recommend uploading and using Playable creatives.
●Creative size requirements:
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Optimization Phase
Learning Phase
●The duration of the learning phase: 
○The learning period for D0 Target CPE campaigns is typically around 1-2 weeks.
○ The learning period for D7 Target CPE campaigns is typically around 3-4 weeks.
●As the number of unique paying users increases in a Target CPE campaign, the algorithm model will gradually improve, leading to further optimization and better performance.
○When a Target CPE campaign stabilizes and reaches a stable number of 5-10 unique paying users per day, the optimization effect tends to improve, and the CPE price may decrease. 
○When a Target CPE campaign stabilizes and achieves more than 20 unique paying users per day, the learning phase concludes, and the optimization effect tends to improve significantly.
●During the learning period, you may encounter the following situations:
○The number of paying users is unstable, and there might be days without any paying users, making it difficult to achieve the set Target CPE cost. 
○The cost per engagement (CPE) exceeds the set Target CPE by 1-1.5 times. 
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During the first week, the eCPI may be higher compared to the regular CPI campaigns by 1-2 times. 
Normal delivery phase: 
●When the daily number of unique paying users consistently exceeds 20, and the CPE steadily meets the set price, it can be considered as the end of the learning phase, and the algorithm model is in a good state. It is recommended to continue monitoring the performance and gradually increase the budget, while considering raising the Target CPE bid to scale up the volume based on the return on investment.
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