What Is a Bidding Strategy? A Marketer’s Guide to Smarter Ad Spend

Writer: Luis Reyes
Date: November 18, 2025

We all start the morning with our routines—stretch, deep breath, phone in hand. You scan the inbox, scroll socials to catch up with people, then check the weather app to decide if it’s a jacket or t-shirt kind of day.

On the surface, it all feels like nothing more than habit. However, behind each digital action which took place, your morning was part of multiple bidding strategies as advertisers compete for placements within every app you open, hoping to earn not just an impression, but influence.

That’s the reality of our industry: every ad dollar counts. And success depends on more than simply “setting and forgetting” a campaign. A well-defined bidding strategy can be the difference between wasted spend and measurable ROI. The key is to evaluate the full landscape, from CTV and display to mobile and video and understand where manual control or automated optimization will have the greatest impact.

In this guide, we’ll walk you through your options, weigh the pros and cons, and outline practical tips to help you select and optimize the right bidding strategy for your business.

 

WHAT IS A BID STRATEGY IN ADVERTISING?

A bid strategy is what advertisers use to determine the value of the bids they make in real-time auctions. In the modern-day landscape where omnichannel programmatic advertising has become the norm, making smart, data-driven bidding decisions is crucial. With campaigns running simultaneously across multiple channels, your bid strategy determines how effectively you compete for impressions while still aligning with broader goals for driving traffic, generating conversions, or boosting brand awareness.

Depending on your objectives and budget, your bidding strategy might be:

• Manual: You control the maximum amount for each bid.
• Automated: Machine learning algorithms optimize bids based on performance data.
• Rule-based or hybrid: Manual oversight and automation are combined for added flexibility.

The right approach is the one that helps you balance control, efficiency, and performance, ensuring your ad spend works harder across every channel.

Want to Learn More? Check out Real-Time Bidding Explained: How RTB Works & Why It Matters to Digital Advertisers

 

CAMPAIGN BIDDING STRATEGIES & GOAL STRUCTURES

The bid strategy type you choose can make or break campaign performance. Below, we’ve broken down the most common models, along with guidance on when to use them and an overview of advantages and limitations.

Let’s look at how different bidding approaches stack up, starting with the most hands-on option.

 

Manual Bidding

Manual bidding is the most precise way to manage spend, letting you decide exactly what each click or impression is worth.

Typical Use Cases:

• Budget Management: Smaller campaigns with fixed budgets, where controlling spend on a granular level is essential for success.
• Audience Testing: A/B testing of creative, messaging, or audience segments with tightly controlled variables.

 
Advantages:

• Optimum control: You decide exactly how much to bid for each ad placement.
• Flexibility: It’s easy to prioritize high-value keywords, audiences, or geographies.

 
Disadvantages:

• Time-intensive: Requires daily monitoring and adjustments to stay competitive.
• Limited scalability: Manual processes become difficult to manage as campaigns expand across multiple platforms or larger audiences.

Because of these disadvantages, manual bidding is often best reserved for smaller-scale campaigns with tight budgets or specific testing scenarios.

 

Automated Bidding

An automated bidding strategy leverages AI-powered machine learning algorithms to evaluate millions of data points spanning user behavior, device type, location, time of day, and more. The resulting data is used to dynamically adjust bids in real time based on your campaign goals.

The biggest appeal here is scale, with automation allowing campaigns to react in ways a human simply couldn’t in real time.

Typical Use Cases:

• Goal Focused: Conversion or click-focused campaigns where your primary goal is maximizing ROI with minimal manual input.
• Reach: Scaling campaigns running across multiple channels for consistent performance.

 
Advantages:

• Time savings: Automation reduces manual workload and accelerates decision-making, helping you reach peak performance faster.
• Data-driven precision: Algorithms use real-time signals to improve performance.

 
Disadvantages:

• Visibility In Bidding Path: You don’t always see the logic that determines how individual bids are calculated.
• Risk of overspending: Algorithms can prioritize conversions over cost-efficiency when not closely monitored.

In other words, automation can save you time, but it requires trust and regular check-ins to avoid runaway spend.

 

Enhanced CPC (Cost-Per-Click)

An enhanced CPC bidding strategy blends the control of manual bidding with the power of automation. Think of it as a middle ground for advertisers not ready to fully let go of the reins. You set a base for bids, but the platform makes adjustments to improve conversion potential (reducing bids for clicks likely to convert and reducing them for less promising opportunities).

Typical Use Cases:

• Performance Focus: Campaigns with limited oversight where your main objective is to improve conversion rates without sacrificing control.
• Search/ lower-funnel display: Campaigns where users are already demonstrating purchase intent.

 
Advantages:

• Best of both worlds: You maintain manual control while benefiting from AI-powered optimizations.
• More conversions: Adjusting bids intelligently captures more valuable clicks.

 
Disadvantages:

• Limited positioning: Adjustments are incremental, meaning you might miss out on higher-value opportunities where a more assertive bid could have secured better placements.
• Less visibility: Since changes are made behind the scenes, it’s harder to determine why certain bids were adjusted, making deep performance analysis challenging.

Ultimately, enhanced CPC is a useful stepping stone between full manual bidding and more advanced automated strategies.

 

Target CPA (Cost-Per-Acquisition)

This ad bidding strategy focuses on efficiency. It utilizes historical data to predict the likelihood of conversion for each impression, then automatically sets bids to achieve as many conversions as possible at or below a specific acquisition cost.

A target CPA strategy works especially well when you have enough historical data to give the algorithm a strong foundation.

Typical Use Cases:

• Direct-response: Campaigns where every conversion has a measurable value.
• Lead Breakdown: Situations where you already have clearly defined acquisition costs for every lead or sale.

 
Advantages:

• Automated performance optimization: Simplifies campaign management while still prioritizing your CPA goal.
• Scales efficiently: Once configured, a target CPA strategy can handle large, multi-channel campaigns with minimal manual oversight.

 
Disadvantages:

• Learning curve: Bid strategy learning models require time to analyze and “remember” performance signal patterns, which can temporarily increase spend.
• Less flexibility: Overly aggressive CPA targets may limit reach, reduce impression volume, and stall overall campaign performance.

In practice, target CPA is often most effective once a campaign has matured past the testing stage.

 

Target ROAS (Return on Ad Spend)

This bid strategy type focuses on maximizing revenue rather than just conversions. Using historical conversion data, the platform predicts the potential return from each impression and automatically adjusts bids to achieve your desired ROAS target.

Where CPA looks at efficiency per acquisition, ROAS zooms out to focus on the bigger financial picture.

Typical Use Cases:

• E-commerce: Campaigns where tracking revenue per product or transaction is essential for success.
• Cost Gain Analysis: Campaigns where you have already established accurate revenue attribution.

 
Advantages:

• Revenue-driven: Prioritizes bids where the potential for generating higher revenue is strongest.
• Supports long-term scaling: Great for growing high-performing campaigns based on proven ROI data.

 
Disadvantages:

• Data dependency: Requires accurate conversion value tracking to make informed adjustments. Inaccurate data often leads to suboptimal optimization.
• Potential under-delivery: Setting unrealistically high ROAS goals may limit impressions and restrict campaign reach.

Target ROAS can be a powerful growth driver, but only if your tracking is airtight and revenue attribution is accurate.

 

CPM (Cost Per Mille)

With a CPM bidding strategy, you pay a fixed cost for every 1,000 impressions. This model prioritizes visibility and reach over direct engagement, making it ideal for brand-building campaigns at the top of the funnel.

With CPM, it’s less about who clicks and more about making sure your brand is seen.

Typical Use Cases:

• CTV and video: Campaigns where maximizing audience reach is the ultimate goal.
• Awareness based: Initiatives focused on awareness rather than immediate conversions.

 
Advantages:

• Massive reach potential: It’s the perfect fit for campaigns prioritizing brand visibility and exposure.
• Predictable pricing: Bids are based on impression volume, not conversions, making it easier to forecast costs.

 
Disadvantages:

• Engagement isn’t a given: Paying for impressions doesn’t guarantee that users will interact with your ad.
• Wasted spend risk: Without precise targeting, you may end up paying for impressions from audiences unlikely to convert.

To avoid such waste, CPM is usually paired with strong creative and precise audience targeting.

 

CPV (Cost Per View)

This type of ad bidding strategy is primarily used for video campaigns, where you only pay when someone watches a specific portion of the video. CPV is a smart option if you want to pay only for meaningful attention rather than fleeting impressions.

Typical Use Cases:

• OTT and streaming: Campaigns where video completion signals strong audience intent.
• Narrative-driven: Campaigns designed to connect with viewers through compelling creatives.

 
Advantages:

• Value: You only spend on viewers who actually engage.
• High-quality signals: Ideal for accurately measuring audience interest.

 
Disadvantages:

• Premium pricing: Can be expensive in competitive video markets with high-demand placements.
• Creative dependency: Performance relies heavily on video quality and effective audience targeting.

CPV works best when video is central to your campaign strategy, making it a strong fit for brands that prioritize storytelling and deeper audience engagement.

 

vCPM (Viewable CPM)

Unlike standard cost-per-mille bidding strategies, you only pay for impressions considered “viewable” according to platform standards. For example, platforms may only charge when at least 50% of the ad is visible on-screen for one continuous second. This ensures you’re paying for impact, not just presence.

Typical Use Cases:

• Branding: Campaigns where measuring the visual impact of ads is more important than driving direct clicks.
• Display or mobile: Campaigns that prioritize brand safety and premium ad placements.

 
Advantages:

• Optimum visibility: Ensures that spend is focused on ads that are most likely to be seen.
• Boosted brand awareness: Helps you achieve stronger top-of-funnel exposure in high-value placements.

 
Disadvantages:

• Engagement isn’t guaranteed: Viewable ads don’t necessarily drive action or conversions.
• Higher costs: Premium inventory often comes with a higher price tag, especially in competitive markets.

vCPM is often the go-to choice for premium branding campaigns that want to balance visibility with accountability. It’s especially useful for advertisers who want the certainty that their spend is going toward ads people actually see, rather than impressions lost to poor placements.

 

PROS AND CONS OF MANUAL VS AUTOMATED BIDDING

When it comes to managing ad spend, the biggest decision is often how much control you want versus how much efficiency you need. The table below highlights the key differences between manual and automated bid strategies.

Feature	Manual Bidding	Automated Bidding
Control	Complete control over individual bid amounts.	Relinquishes control to algorithms.
Optimization	Relies on human decisions and manual adjustments.	Driven by AI and machine learning for real-time optimization.
Setup Time	Slower to configure and maintain.	Faster to launch and manage.
Performance Tracking	Highly customizable, with deeper insights into why bids perform the way they do.	Limited visibility into decision-making. Relies on predictive analytics.
Ideal For	Small campaigns, fixed budgets, or precise A/B testing.	Larger campaigns focused on scalability, efficiency, and maximizing ROI.

 
In summary, a manual bidding strategy is best suited for smaller, highly controlled campaigns where you want to manage every detail. Conversely, an automated bid strategy is more effective for scaling performance efficiently, but it requires trust in algorithms and regular monitoring to prevent overspending.

 

CHOOSING THE RIGHT AD BIDDING STRATEGY FOR YOUR CAMPAIGN

The right strategy ensures ad spends that drive measurable impact. Here’s a helpful framework to help you decide on the best fit:

1. Define your primary objective. Are you focused on driving clicks, maximizing conversions, increasing views, or boosting brand awareness?
2. Decide how much control you want. Do you prefer manual management or are you comfortable letting an algorithm make adjustments in real time?
3. Assess your budget flexibility. Automated models often require a broader budget range to allow for algorithm learning periods.
4. Consider performance data availability and quality. Strategies like Target CPA and Target ROAS work best when you have reliable historical conversion data.
5. Match your strategy to your channels. Display, CTV, and video campaigns often perform better with models such as CPM, vCPM, or CPV, while search campaigns may favor Enhanced CPC or manual bidding.

Of course, you’ll also need to evaluate each approach in relation to your campaign goals. Here’s an overview of how different bidding models align with common objectives:

Compaign Goal	Recommended Strategies
Maximize website traffic	Manual CPC, Enhanced CPC
Drive conversions	Target CPA, Maximize Conversions
Increase return on ad spend (ROAS)	Target ROAS
Boost brand awareness	CPM, vCPM
Maximize video engagement	CPV, Target CPM (for video)

 

OPTIMIZE YOUR BID STRATEGIES OVER TIME

No single bidding strategy will provide a set-and-forget solution. Here are a few practical tips to help you monitor performance, refine your approach, and maximize ROI over time.

• Set clear benchmarks by establishing KPIs for clicks, conversions, ROI, and engagement before launching any campaign.
• Monitor performance using real-time reporting tools to track what’s working and where adjustments are needed.
• Test and compare by running A/B tests to evaluate the effectiveness of different bidding strategies for your goals and budget.
• Reassess performance as data accumulates to ensure your chosen strategy remains aligned with business priorities.

Pro Tip: Begin with a single bidding model and closely monitor the results. As your campaigns grow, experiment with more advanced strategies that combine automation and manual oversight to unlock long-term performance gains.

 

STAY COMPETITIVE WITH A SMARTER BIDDING STRATEGY

A well-optimized bidding strategy can be the difference between meeting your goals and missing opportunities. But success isn’t just about choosing the right model. Continuously refining your approach based on performance, channels, and audience behavior is equally essential. That’s where Simpli.fi comes in.
Our suite of media planning tools helps agencies, brands, and media companies unlock smarter bidding strategies across every channel, including:

• CTV advertising
• Mobile programmatic advertising
• Programmatic display advertising
• Programmatic video advertising

With granular reporting, real-time optimization, and cross-channel capabilities, Simpli.fi empowers marketers to set dynamic, data-driven bids, scale campaigns efficiently, and maximize ROI while maintaining visibility and control.

 
Ready to improve your bidding performance? Contact us today for a personalized demo to discover how we can help you spend smarter, compete harder, and drive better results.

 

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