The debate between ABO (Ad Set Budget Optimization) and CBO (Campaign Budget Optimization) has shaped Facebook advertising strategies for years. As Meta’s algorithm continues to evolve and automation takes center stage in 2025, advertisers face a crucial decision: retain manual control or trust the machine to allocate budgets intelligently.

While both approaches aim to maximize efficiency and results, they operate differently — and knowing when to use each can make or break your campaign performance. This article breaks down how ABO and CBO work under Meta’s current ad delivery system, compares their strengths and weaknesses, and explores hybrid strategies that today’s top media buyers use to achieve stable and scalable growth.

Understanding ABO and CBO in Meta Ads

Before we build the strategy, let's establish a common ground on what these two budget optimization settings mean in Meta's current, AI-driven ecosystem.

What is ABO (Ad Set Budget Optimization)?

Ad Set Budget Optimization (ABO) is the classic, manual approach to budget management. With ABO, you set a specific daily or lifetime budget for each ad set.

You are explicitly telling Meta: "Spend $50 on Ad Set A (Audience 1) and $30 on Ad Set B (Audience 2), regardless of performance."

• How it Works: The budget is locked at the ad set level. Meta's algorithm will then try to get the most results possible within the confines of that ad set's dedicated budget.

• Benefits:

• Granular Control: You have 100% control over how much budget is allocated to each audience or creative test.

• Isolated Testing: This is the primary benefit. If you want to test Audience A vs. Audience B, ABO ensures each audience gets an equal, pre-defined budget, allowing for a fair, scientific comparison.

• Small Budget Stability: If you have a very small daily budget (e.g., $20/day), ABO allows you to focus that entire budget on a single, high-priority ad set, helping it exit the learning phase.

What is CBO (Campaign Budget Optimization)?

Campaign Budget Optimization (CBO), now integrated as Advantage Campaign Budget, is Meta's automated, AI-driven approach. With CBO, you set a single, unified budget at the campaign level.

Meta’s algorithm then distributes that budget in real-time across all the ad sets within that campaign, automatically allocating more spend to the ad sets it predicts will drive the most results (conversions, leads, etc.) at the lowest cost.

• How it Works: The algorithm analyzes performance data across all ad sets and dynamically shifts the budget. If Ad Set A starts performing better than Ad Set B, CBO will automatically decrease spend on B and increase spend on A to maximize the total number of conversions for the overall campaign budget.

• Benefits:

• Automated Efficiency: It saves an enormous amount of time. The algorithm handles the complex task of budget allocation, 24/7.

• Lower Overall CPA: By prioritizing the lowest-cost opportunities across all audiences, CBO is designed to achieve the lowest possible blended Cost Per Acquisition (CPA) for the campaign.

• Stable Scaling: It's much more stable for scaling. Instead of changing budgets, you can often add new proven ad sets to the campaign, and the CBO will re-optimize the budget distribution.

How Meta’s AI Shift Impacts Both Approaches

Meta has leaned heavily into automation — from Advantage+ placements to Advantage+ audience expansion. According to Meta’s 2024 update, “machine learning models now adjust in real time to find higher-value audiences across placements and signals.”

This evolution benefits CBO, which thrives on algorithmic flexibility. However, it doesn’t make ABO obsolete. Manual control through ABO remains critical for testing, audience segmentation, and performance diagnostics before handing campaigns over to automation.

ABO vs CBO: The Core Differences Explained

The choice between ABO and CBO is a strategic one that impacts everything from testing to scaling. Here’s a direct comparison of their fundamental differences.

Budget Control: Granular vs. Automated

This is the most obvious difference.

• With ABO, you are the fund manager. You dictate a fixed budget for each ad set. This is "human-led" control. If you want to spend $50 on your retargeting audience and $100 on your broad prospecting audience, you set it and Meta executes.

• With CBO, Meta's AI is the fund manager. You give it a total pool of money (the campaign budget) and your objective (e.g., "get conversions"). The AI then makes all allocation decisions, pushing money to the "ad sets" (funds) it believes will yield the highest return.

Learning Phase & Data Aggregation

The learning phase (requiring ~50 conversions per ad set per week) is critical for optimization.

• With ABO, each ad set has its own learning phase and its own data. If you have 5 ad sets at $10/day, each one struggles to get 50 conversions on its tiny budget. This often results in "Learning Limited" status, preventing any ad set from ever fully optimizing.

• With CBO, the campaign aggregates data. While each ad set still technically learns, the budget is flexible. The AI can push $40 to Ad Set A and $10 to Ad Set B on a $50/day campaign budget to get one of them out of learning faster, leading to quicker optimization for the campaign as a whole.

Scaling Methodology: Vertical vs. Horizontal

How you "add more money" is fundamentally different.

• ABO Scaling (Vertical): To scale a winning ad set, you must manually increase its budget (e.g., from $50/day to $60/day). This is "vertical" scaling. It’s risky, as large changes can reset the learning phase and destroy the ad set's performance.

• CBO Scaling (Horizontal): The safer way to scale a CBO is often "horizontally." Instead of touching the budget, you add more proven ad sets (e.g., new winning audiences from your ABO tests) into the CBO campaign. The AI then recalibrates the budget across this larger pool of high-quality ad sets.

Testing Validity: Fair vs. Biased

This is where many advertisers go wrong.

• ABO Testing: ABO is the only way to run a truly fair A/B test. If you want to know if "Audience A: Golf" is better than "Audience B: Tennis," you must use ABO. By setting a $50/day budget for each, you ensure both audiences get an equal chance to perform.

• CBO Testing: Using CBO for this test is invalid. The algorithm might (for various reasons) spend $90 on "Golf" and $10 on "Tennis" on Day 1. You've learned nothing about "Tennis" because it never had a chance. CBO is a performance tool, not a testing tool.

The summary table showing the difference between ABO and CBO is below:

When to Use ABO

ABO isn't "old-school"; it's a precision instrument. Using it correctly is the foundation of any scalable ad account.

Testing (The #1 Use Case):

• Audience Testing: Run a campaign with 3-5 ad sets, each with a different audience but the same winning creative. ABO ensures each audience gets the same budget for a fair comparison.

• Creative Testing: Run a campaign with 3-5 ad sets, each with a different creative (or ad copy) but the same winning audience.

• Geographic Testing: Test performance in a new region by dedicating a specific budget to it.

Campaigns with Very Small Daily Budgets: If your toatal daily budget is $25, don't use CBO across 5 ad sets. It will fragment the budget too much. Use ABO to put all $25 into a single, proven ad set to give it the best possible chance to succeed.

When Isolating Performance Metrics is Non-Negotiable: Sometimes, you must spend a specific amount on a specific audience, even if it's not the top performer.

• Example: A brand awareness campaign that must spend $1,000 in a specific new market.

• Example: A full-funnel strategy where you want to guarantee a fixed budget for your retargeting (BOF) ad set.

When to Use CBO

CBO (Advantage Campaign Budget) is Meta's scaling engine. When fed the right fuel, proven, high-performing assets, it's the most powerful tool you have for growing an account.

Scaling Winners After ABO Testing

This is the primary function. You ran an ABO test and found 3 audiences and 2 creatives that are clear winners. You now create a new CBO campaign, load it with these proven assets, and give it a large budget to scale.

Large Audiences or Global Campaigns

When you're targeting broad audiences (e.g., 20M+ people) or "going broad" with no interest targeting. CBO is exceptional at finding the lowest-cost "pockets" of users within that massive audience pool.

Broad Targeting + AI-Based Creative Optimization

Combine CBO with Dynamic Creative (DCO) or by stacking 5-10 proven creatives in each ad set. This gives the AI maximum flexibility: it can choose which ad set to fund (CBO) and which creative to show (ad-level optimization).

Advanced Optimization Tactics (For Expert Media Buyers)

If you've mastered the hybrid model, you can use these techniques to exert even more influence over the algorithm.

Controlling CBO Delivery with Caps

Instead of using budget limits (min/max), which can be clunky, use Bid Caps or Cost Caps.

• Cost Cap: Tells Meta, "Get me conversions, but do not pay more than $50 on average." This is great for stabilizing costs in a scaling CBO.

• Bid Cap: A more aggressive "hard cap" that tells Meta, "Do not bid more than $X in any auction." This lets you control CPA while still letting CBO manage the budget distribution.

Leveraging Advantage+ Audience with an ABO Structure

This is a modern testing combo. We know ABO is for testing, but what do you test? Create an ABO campaign where each ad set uses Advantage+ Audience. The only variable you change between ad sets is the creative. This pits your creative concepts against Meta's broadest and most powerful AI targeting, giving you a clear signal on which creative resonates most with the algorithm.

Cross-Funnel Strategy (ABO for TOF, CBO for MOF/BOF)

This is an advanced alternative to the hybrid model.

• TOF (Prospecting): Use ABO campaigns. Why? You are always testing new cold audiences, new lookalikes, and new interests. This is your R&D department.

• MOF/BOF (Retargeting): Use a single CBO campaign. Why? You have many small, segmented retargeting audiences (e.g., 3-day visitors, 7-day cart abandoners, 30-day engagers). Putting them all in one CBO lets Meta find the lowest-cost conversion among your entire warm audience pool, rather than you guessing which segment to fund.

Analyzing Results with Breakdowns

In a CBO, don't just look at the ad set level. Use the "Breakdown" tool in Ads Manager to see how CBO distributed the spend (e.g., by "Delivery" -> "Ad Set"). More importantly, use breakdowns by Age, Gender, Region, or Placement. This shows you what the AI learned, which should inform your next ABO test. (e.g., "The CBO is spending 80% on women 25-34... let's make an ABO test creative specifically for them.")

FAQs 

Is ABO still relevant in 2025?

Absolutely. It is, and will remain, the professional standard for isolated testing of creatives, audiences, and offers. Without a strong ABO testing framework, your CBO campaigns are just guessing in the dark.

Can I mix ABO and CBO in the same campaign structure? 

No. The choice (ABO vs. Advantage Campaign Budget) is a setting selected at the campaign level. You cannot have one CBO campaign that also contains ABO ad sets. The "hybrid strategy" refers to using separate ABO campaigns for testing and CBO campaigns for scaling.

Does CBO still respect ad set limits? 

Yes. If you set a minimum or maximum spend limit on an ad set within a CBO campaign, Meta will honor it. However, be cautious. Using these limits too much restricts the algorithm's ability to optimize and effectively turns your CBO into a clunky ABO.

What’s the minimum budget for efficient CBO learning?

There is no magic number. The rule of thumb is that your total campaign budget should be high enough to generate ~50 conversions per week. A better baseline is to set a daily CBO budget that is at least 5x-10x your target CPA, giving the algorithm enough room to test the different ad sets.

How do Advantage+ Campaigns affect my ABO/CBO choice?

Advantage+ Shopping Campaigns (ASC) are a separate, hyper-automated system, primarily for e-commerce. Think of ASC as a CBO that also automates audience (merging prospecting and retargeting) and creative. The ABO/CBO choice remains your primary tool for manual campaigns where you still want to define the audiences.