Summary
Highlights
Many advertisers in 2025 still focus on incorrect metrics like CTR or CPM. This video provides a comprehensive guide on analyzing Facebook Ads data from beginner to expert levels, enabling smarter scaling and avoiding wasted ad spend. The agenda includes an updated column setup, tools for data-driven decisions such as Motion and Triple Whale, and advanced data analysis often overlooked by experts. A free creative reporting checklist is also available.
The video outlines the essential metrics to track in Ads Manager. It starts with delivery columns, bid strategy (recommending 'highest volume' for beginners), and attribution settings (suggesting '7-day click and 1-day view'). Budget allocation is also discussed, advising a minimum of $100 for ASC campaigns. The crucial primary metrics are 'Amount Spent,' 'Purchases' (or 'Leads'), 'Cost Per Purchase,' and 'ROAS,' which indicate if a campaign is working. Sorting by 'Amount Spent' (highest to lowest) helps prioritize optimization.
The next five metrics focus on audience reach: 'Frequency' (how often people see ads, with concerns if above 5 over a few weeks), 'Reach' (unique individuals), 'Impressions' (total ad views), 'Cost Per Reach,' and 'CPM' (cost per 1,000 impressions). CPM's average varies by industry, and tools like Varos can provide benchmarking data. Following these are six metrics related to ad engagement: 'Unique Outbound Click-Through Rate' (the most accurate CTR), 'CPC' (Cost Per Link Click), and custom metrics like 'Hook Rate' (percentage of people watching the first 3 seconds of video) and 'Hold Rate' (percentage watching the first 15 seconds or the entire ad if shorter). 'Post Shares' track organic ad shares, indicating content virality.
The speaker extensively uses Motion, a creative strategy tool, for in-depth creative analysis and reporting. Motion helps identify top-performing creatives weekly and monthly, facilitates individual creative test reports, and enables format analysis to assess creative diversity (images, videos, carousels). It also helps categorize and analyze creative strategies like testimonials or 'before and after' for both static and video ads. For large brands, Motion is crucial for comparing the performance of different agency partners and individual creators (celebrities, influencers, UGC creators) to inform future investment decisions.
Effective data analysis requires a mind shift: analyze first, then optimize. The goal is to answer two questions: 'What is working?' and 'Why is it working?' All metrics fall into two categories: 'Primary Metrics' (Amount Spent, Purchases, Cost Per Purchase, ROAS) that dictate what to optimize, and 'Storytelling Metrics' (Frequency, CPM, Hook Rate, Hold Rate) that explain why something works or doesn't. Video creative metrics (Hook Rate, Hold Rate, average play time) are especially insightful. Custom metrics for Hook and Hold Rate with their formulas are provided, though these are only for video creatives.
An example ASC campaign is analyzed, emphasizing that more ad creatives (minimum 20 suggested) lead to better performance. The analysis starts by sorting by 'Amount Spent' to identify top performers. The overall campaign showed strong performance with an 11k spend, 525 purchases, $21.9 cost per purchase, and 2.77 ROAS. A single ad creative accounted for 75% of the spend, exhibiting excellent ROAS and cost per purchase. While its click-through rate was average, its hook and hold rates were double the account average, indicating strong creative. The speaker notes that the 'Breakdown Effect' explains why Meta might not push more spend to seemingly more profitable smaller ads, as their algorithm determines the optimal spend.
Advanced creative analysis goes beyond basic metrics by incorporating qualitative and additional data. Qualitative data includes: 'Format' (e.g., UGC Creator Testimonial), 'Creator' (impact of specific talent), 'Messaging' (value-based, competitor comparison, negative marketing, problem/solution, trigger words like 'hate'), and 'Imagery' (production quality, setting like being in a car). Messaging analysis helps understand which stage of the marketing journey an ad targets and its scalability. For instance, 'negative marketing' and 'question' format messaging might appeal to a wider problem-aware/unaware audience, leading to longer-term success, even if other ads have quicker initial conversions.
Additional data for advanced creative analysis includes 'Breakdown Data' (age, placements, gender) from Ads Manager, which helps identify specific audience performance. For example, a creative performing well with the 50+ age range might prompt more creative development for that demographic. Analyzing placements (Instagram vs. Facebook, Feed vs. Stories/Reels) can reveal platform-specific creative effectiveness. Finally, 'Comparative Data' is crucial. This includes comparing current creative performance to your own top performers and active tests, and also analyzing competitor ad creatives to observe trends in formats, messaging strategies, and scalability. This comprehensive approach helps uncover deeper insights into what makes an ad successful and how to replicate it.