Consumer Acquisition by Brainlabs Media Buying Model
As a complementary tool to our Ad Concept Model, we are introducing our Media Buying Model which uses a similar matrixed approach to systematize best practices for user acquisition campaign development. Any mobile app can leverage a unique combination of distinct UA strategies and campaign parameters to develop a robust testing harness for ongoing mobile campaigns across social platforms.
In its most generic state, our Media Buying Model looks like the matrix below, prior to building out a mobile app user acquisition strategy. The entire matrix is tailored to a respective ad network and operating system requirements and constraints. Geographies, languages, and bid types are all modified based on the client’s needs. Each campaign is structured to meet specific goals at the intersection of strategies and parameters.
The entire matrix is tailored to a respective ad network and operating system requirements and constraints. Geographies, languages, and bid types are all modified based on the client’s needs. Each campaign is structured to meet specific goals at the intersection of strategies and parameters.
Testing on Android
Even prior to IDFA loss, Consumer Acquisition conducted creative and UA testing on Android because it was less expensive, and results translated well to iOS. We saved iOS testing for the rare clients without an Android app or those who were solely targeting iOS users.
Unlimited ad accounts and campaigns
Unobstructed deterministic tracking
Comprehensive A/B testing with full reporting
Distributed scale and spend across campaigns
Rapid testing, unlimited test campaigns
Success drivers easy to identify and scale
Google Firebase enables tROAS, delivering ~15% lift on CPA campaigns with better user mapping
iOS IDFA Impacts
Many accounts but only 9 campaigns, 5 ad sets
SKAN tracking disabled after 24-48 hours (See AppsFlyer Conversion Studio below)
A/B testing in DCO blobs, no asset reporting
Fewer campaigns, higher budgets, more significant edits
Restricted testing, only 9 campaigns
Aggregate insights drive slower optimization
Post-IDFA, iOS lookalike audiences have lost -65% of their reach and effectiveness
Testing on iOS with AppsFlyer
If you use AppsFlyer on iOS, we recommend testing through Conversion Studio, released September 9, 2021. Conversion Studio helps maximize LTV measurement for post-install activity by:
Extending post-install event collection up from 24 hours to 72 hours and enabling D3 optimizations
Tracking multiple iOS KPIs instead of only one in SKAN
Measuring sequential events in the conversion funnel
Marrying SKAN data to AppsFlyer attribution
Why use a model like this?
Our industry expertise comes from managing over $3.5 billion in creative and paid social spend for the world’s largest mobile apps and performance advertisers. We run our tests using our software AdRules via Facebook, Google, and TikTok APIs. Our Media Buying Model systematizes the UA campaign process, so we know what works, why it works, how to do more of it, and how to easily communicate status. Our process is designed to save time and money by optimizing quickly to reduce non-converting spend and to scale as pockets of efficiency are uncovered.
Below, see our Media Buying Model built out for sample mobile app campaigns across Facebook Android, Facebook iOS SKAN, Google iOS SKAN, and TikTok iOS and Android.
Facebook Android Media Buying Model
On Facebook, UA campaign goals may include:
High scale AAA campaign in top-performing countries
Broad targeting split by geo, using CBO to auto-optimize with additional ROAS boost from the top-performing demo.
Split broad targeting by time zone, using CBO to auto-optimize.
High Performing LAL audiences based on Primary Metric Value, using CBO to auto-optimize.
Exploratory spend split by interest groups, using CBO to auto-optimize.
Benefits of Testing on Android
Android unimpacted by IDFA
Optimization maintains deterministic efficiency
Android Facebook primary for A/B creative and audience testing
Rollout Android Facebook winners to iOS and other platforms
Scale: increase installs
Exploratory: test creative, audiences to feed scale
Interests: bridge volume of broad and precision of lookalikes
CBO structure allows for maximized testing/learning
The highest-performing ad sets are relaunched as standalone campaigns to increase scale and performance
Initial 3% Lookalike likely to drive the best performance
High-performing LALs are immediately scaled as new campaigns
High-performing audience seeds are recreated with Frequency parameters
Use FB activity to create Lookalike Audiences (ex: Page Engagement, IG Engagement, Video Views, App Value-Based Lookalikes)
Purchase: Last 180 days
Frequent app users: Last 90 Days
Interest Group Testing
Build interest clusters using contextual targeting best practices leveraging personas, likes, pages, competitive apps, etc.
Ongoing identification and testing of iterative Interest Groups as campaigns progress
Utilize top creative combinations – image/video + body copy, headline, CTA
Creative Format testing- DCO, Carousel, PAC
Ad Copy Testing
Phased creative testing, conducted on Android with winners transferred to iOS campaigns
Facebook iOS Post-IDFA Media Buying Model
Embrace SKAN limitations: 9 campaigns max, 5 ad sets per campaign max, max 45-60 permutations
Optimize account to achieve a minimum of 128 conversions (installs) per campaign per day
Scale: drive volume + performance
Exploratory: Test VO vs. AEO and Broad vs. Top Demos with single vs. bundled Geos to identify highest-performing Optimization/Geo/Audience (lowest CPT cost per trial)
Move winning creative from Android
AAA most successful with groups of high performing creative and copy
VO based on $CPT insights from Exploratory Campaigns
Initial AAA campaigns segregated by Geo can bundle US/CA/UK to reduce SKAN campaign slots (only if needed)
Campaigns 1-2-3 budgets must be sufficient to support a minimum of 128 installs/day
Leverage CBO structure in all campaigns to test individual/bundled Geos within single campaigns
Test Broad vs. Top Demo in campaigns 5, 6
Test AEO vs VO in campaigns 4, 5
Pinpoint opportunity for volume and $CPT efficiency by testing low-CPM images vs. video
Measurement Limitations for iOS Campaigns
Pre-IDFA Loss, iOS < 14.5
Lifetime deterministic tracking provided in AppsFlyer
28 days of attribution across Facebook, Google, Snap, and Tiktok for bid optimization and creative testing
Measurement Post-IDFA Loss: iOS 14.5+ Limits
User is anonymized; install and event reporting delayed 24+ hours
Limited to a single conversion value; only one KPI can be reported back to your ad campaign
Limited to 24 hours post-install for event attribution timeframe
Event reporting is triggered after a minimum of 24 hours of inactivity
SKAN provides 6 bits of information to hold your conversion event data
This conversion value is set each time a user triggers specific events in your app, like a purchase
Each time you set it, a 24-hour timer starts, and at the end of that timer, your conversion will be reported back to the ad network with a random delay buffer added
Each time you set an event, the 24-hour timer restarts, potentially delaying your reporting to 64 days post-install!
Google iOS SKAN and Android Media Buying Model
On Google, UA campaign goals are progressive:
Identify primary event performance and establish a baseline for video creative
Test messaging with upper-funnel campaign type
Event testing with a creative baseline established by geo
Continue message testing refinement
Full expansion by platform with top CPA event and performance messaging determined
Ramp up top event campaign from the previous week
Revenue optimization if FB enabled
Exploratory, Expansion, and Scale Campaigns:
Learning > Scale
Single Event CPA, graduated to event testing by Week 2
All Purchasers Last 180 days
Event Testing and Consolidation
Supplement opening creative tests with Install + campaign