📊 Viewing Campaign Analytics
Whether you're running ads on Meta or Google, campaign analytics typically begin populating within 12 hours of launch. If you don’t see data after 24hrs, try these steps:
Refresh the App: Ensure your AdScale dashboard is refreshed so it can pull in the most recent performance metrics from Meta and Google.
Update the Date Range: Use the date picker to view "Yesterday" or the "Last 7 Days." This helps eliminate delays from real-time data syncing.
⚙️ Optimizing Campaign Performance (Meta & Google)
AdScale uses AI to learn from your store and campaign performance over time. Here's what to expect:
Initial Results: Some early performance may be visible in the first few days, but these are still within the learning phase.
Learning Phase: Both Meta and Google need a stable learning period—typically 14 to 30 days—for their algorithms (and AdScale’s AI) to gather enough behavioral data.
Tip: Avoid making frequent changes during this period. Stability helps the system optimize more effectively for your business goals, like conversions, revenue, or ROAS.
Understanding Meta's Learning Phase
Meta's learning phase begins when a new campaign is launched or significant changes are made to an existing campaign. During this time, Meta's algorithm collects data to better understand which audiences and placements yield the best results. While the learning phase is active, the campaign's performance may fluctuate as the algorithm tests different variables. It is important to note that the learning label itself is not necessarily a blocker, and well-performing ads can continue to deliver results even while in this phase.
Factors Affecting the Learning Phase
Several factors can influence the duration and effectiveness of the learning phase:
Conversion Volume: Low conversion volume can prolong the learning phase, as the algorithm requires sufficient data to optimize effectively.
Audience Size: Small retargeting audiences may limit the algorithm's ability to gather diverse data, slowing optimization.
Budget Allocation: Budgets spread across multiple ad groups can dilute the data collected, making it harder for the algorithm to identify successful patterns.
Strategies for Optimization and Scaling
To optimize ad performance and help the algorithm learn faster, consider the following strategies:
Consolidate Ad Groups: Combining multiple ad groups into one main ad group with a higher, unified budget allows the algorithm to focus on a single data set, improving learning efficiency and scaling potential.
Focus on High-Impact Metrics: Prioritize metrics that align with your campaign goals, such as conversions or click-through rates, to guide the algorithm's optimization process.
👀 Troubleshooting Visibility Issues
If your ads aren’t showing on Meta or Google, the issue may be linked to integration settings or platform approval. Here’s what to check:
For Google:
Go to Settings → Integrations → Google
Ensure your accounts are verified and all business info is complete.
Make sure your billing method is valid.
For Meta:
Go to Settings → Integrations → Facebook
Check that your ad account and business manager are fully connected.
Confirm you've granted full access to AdScale so campaigns can sync correctly.
Look for a confirmation message in AdScale indicating successful integration.
Verify that campaigns appear in your Meta account matching those created in AdScale.
If your campaigns are set up but still not showing, check if they're under review or in the learning phase—this can temporarily delay visibility. Additionally, if your dashboard is empty, verify that you've created budget groups and received integration confirmation notifications from AdScale.
🧠 Final Tips
Let the AI learn: Both platforms benefit from consistency. Let campaigns run without major interruptions for better data and smarter optimizations.
Check Ad Assets: Low-quality creative or missing ad copy can limit performance. Make sure all required assets are in place, especially for PMAX.
Review Audience Targeting: If your audiences are too broad or too narrow, both Meta and Google may struggle to allocate spend effectively.
Understand Learning Phase Misconceptions: The learning label does not necessarily indicate poor performance. Ads can still deliver results during this phase, and patience is key as the algorithm gathers sufficient data to optimize effectively.
Need More Help?
If your campaigns still aren’t performing or showing as expected, feel free to reach out to our support team or check our guides for asset setup, audience strategies, and platform best practices.