Video sequencing—delivering a series of video ads in a specified order to build a cohesive narrative—is a strategy that has proven effective in guiding users through a structured brand story. While Meta’s Campaign Budget Optimization (CBO) campaigns offer more direct control over the delivery of sequences via budget distribution across ad sets, advertisers have speculated whether video sequencing is implicitly occurring in Ad Set Budget Optimization (ABO) campaigns.
This blog explores whether Meta’s platform naturally sequences video ads in ABO campaigns, how this sequencing may influence reporting, and what criteria should be used to evaluate ads if such sequencing is indeed happening.
The Concept of Implicit Sequencing in ABO Campaigns
In ABO campaigns, budgets are set at the ad set level, giving advertisers granular control over individual ad sets. Unlike CBO, where the algorithm dynamically allocates budgets based on performance, ABO keeps budget allocation static unless manually adjusted. This rigid allocation suggests that Meta’s algorithm wouldn’t explicitly control the order in which users see video ads across different ad sets. However, implicit sequencing can still occur due to several factors:
- User Engagement History: Meta’s machine learning algorithm heavily weighs user engagement signals, such as video views, clicks, and time spent on ads. If a user shows high engagement with one video ad, Meta may prioritize showing subsequent ads from the same campaign.
- Ad Frequency and Rotation: Meta’s delivery algorithm attempts to balance frequency while maintaining freshness in ad delivery. As a result, users may naturally experience a sequence-like progression simply due to how the algorithm paces ad rotations.
- Ad Relevance and Predictive Signals: Ads deemed more relevant to a user are prioritized for delivery. If a user has interacted with a previous ad in a campaign, subsequent ads may be shown in what appears to be a logical sequence.
Influence on Reporting Metrics
If implicit video sequencing is occurring, it can skew reporting in several ways:
- View-Through and Engagement Attribution: Ads appearing later in the sequence may benefit from a “priming effect” where earlier ads have warmed up the audience. This can lead to higher engagement rates and inflated performance metrics for these ads.
- CTR and CPA Variability: Earlier ads in the sequence may have lower click-through rates (CTR) and higher cost-per-acquisition (CPA) because they serve primarily to build awareness rather than drive immediate action. Later ads may show better conversion metrics, potentially misleading advertisers about which ad contributed most to the final outcome.
- Lift Studies and Incrementality Testing: Without controlling for sequencing effects, lift studies may attribute success to individual ads without accounting for the cumulative impact of the sequence.
Criteria for Evaluating Ads in ABO Campaigns with Sequencing
To ensure accurate evaluation of ads within potentially sequenced ABO campaigns, advertisers should consider the following criteria:
- Ad Placement within the Sequence: Evaluate ads based on their position within the presumed sequence. Early-stage ads should be assessed for reach, impressions, and engagement, while later-stage ads should be measured against lower-funnel actions.
- Engagement Metrics over Time: Track how engagement evolves as users are exposed to multiple ads. This helps in identifying whether later ads are benefiting from the groundwork laid by earlier ads.
- Holistic Attribution Models: Use multi-touch attribution models to assign appropriate credit to all ads in the sequence. This approach provides a more accurate picture of each ad’s contribution to overall campaign success.
- A/B Testing of Ad Orders: To confirm whether sequencing is occurring, run split tests with varied ad orders. If different sequences yield significantly different results, it indicates that sequencing is playing a role in campaign outcomes.
Conclusion
While Meta does not explicitly offer video sequencing in ABO campaigns as it does in CBO or with dedicated sequencing tools, implicit sequencing can occur due to how its algorithm prioritizes ad delivery based on user behavior. This sequencing can significantly influence reporting metrics, making it essential for advertisers to adopt nuanced evaluation criteria.
By understanding the potential impact of sequencing, media buyers and strategists can make more informed decisions about budget allocation, creative rotation, and performance analysis, ultimately driving better campaign outcomes.