Smart Bidding is a subset of automated bid strategies in Google Ads that uses machine learning to optimize for conversions or conversion value in each and every auction. This feature is also known as auction-time bidding, which means that bids are adjusted in real-time based on a wide range of contextual signals present at the moment of the auction. These signals include device type, location, time of day, remarketing lists, browser, language, and operating system, among many others. Smart Bidding strategies include Target CPA (Cost Per Acquisition), which sets bids to help get as many conversions as possible at your target cost per acquisition. Target ROAS (Return On Ad Spend) sets bids to maximize conversion value while trying to achieve your target return on ad spend. Maximize Conversions automatically sets bids to help you get the most conversions within your budget. Maximize Conversion Value focuses on getting the highest total conversion value within your specified budget. Enhanced CPC adjusts your manual bids up or down based on the likelihood of a conversion. The key benefits of Smart Bidding include time savings through automation, advanced machine learning algorithms that process vast amounts of data, and auction-time bidding that considers unique context for each search. Smart Bidding also offers flexible performance controls, allowing advertisers to set performance targets and customize settings based on their business goals. Transparent performance reporting provides insights into bidding performance through detailed status updates and reports. For Smart Bidding to work effectively, advertisers need sufficient conversion data, proper conversion tracking setup, and realistic targets based on historical performance. Google recommends allowing adequate time for the algorithms to learn and optimize, typically a few weeks, before evaluating results and making adjustments to targets or strategies.

Smart Bidding is Google Ads' automated bid strategy system that uses machine learning to optimize for conversions or conversion value in each auction. This technology analyzes millions of signals in real-time to set the most appropriate bid for every single auction, a process known as auction-time bidding.

The system considers a wide range of contextual signals when determining bids. These include device type, location, time of day, day of week, browser, operating system, and remarketing list membership. Additionally, Smart Bidding evaluates user behavior patterns, search query characteristics, and historical performance data to make informed bidding decisions.

There are several Smart Bidding strategies available to advertisers. Target CPA (Cost Per Acquisition) aims to get as many conversions as possible at your specified target cost per action. Target ROAS (Return on Ad Spend) focuses on maximizing conversion value while achieving your desired return. Maximize Conversions automatically sets bids to help you get the most conversions within your budget. Maximize Conversion Value optimizes for the highest total conversion value. Enhanced CPC adjusts your manual bids to help maximize conversions.

For Smart Bidding to perform effectively, your account needs sufficient conversion data. Google recommends having at least 15-30 conversions over a 30-day period for Target CPA strategies, while Target ROAS typically requires more conversion volume for optimal performance.

The learning period is an important aspect of Smart Bidding. When you implement a new strategy, the system requires time to gather data and calibrate its algorithms. During this phase, which usually lasts one to two weeks, performance may fluctuate as the system learns.

Smart Bidding also provides reporting features that offer transparency into how the automated system is performing, including bid strategy status updates and performance insights to help advertisers understand and optimize their campaigns effectively.

Machine Learning in Bidding refers to the sophisticated technology that powers Google Ads Smart Bidding strategies. This automated approach uses advanced algorithms to analyze vast amounts of data and make real-time bid adjustments for each auction, a process known as auction-time bidding.

At its core, machine learning in bidding examines numerous contextual signals to predict the likelihood of a conversion or valuable action. These signals include device type, location, time of day, day of week, browser, operating system, demographics, ad characteristics, and actual search queries. The system processes millions of data points that would be impossible for humans to analyze manually.

Smart Bidding strategies powered by machine learning include Target CPA (Cost Per Acquisition), Target ROAS (Return On Ad Spend), Maximize Conversions, Maximize Conversion Value, and Enhanced CPC. Each strategy optimizes bids based on specific business goals while leveraging the same underlying machine learning technology.

The system continuously learns and improves over time. As more conversion data is collected, the algorithms become better at predicting which auctions are most likely to result in valuable outcomes for your business. This learning period typically requires sufficient conversion volume to establish reliable patterns.

Key benefits of machine learning in bidding include time savings, improved performance, and the ability to factor in a wider range of signals than manual bidding allows. The technology adapts to changing market conditions and user behavior patterns automatically.

For optimal results, advertisers should ensure accurate conversion tracking is implemented, provide sufficient budget for the system to learn, and allow adequate time for the learning period before making significant changes. Combining machine learning bidding with strong creative assets and relevant landing pages creates a comprehensive approach to campaign optimization that drives better results across Google Ads campaigns.

Target CPA (Cost Per Acquisition) Bidding is a Smart Bidding strategy in Google Ads that uses machine learning to automatically set bids for each auction, aiming to get as many conversions as possible at or below your specified target cost per acquisition. This automated bidding approach leverages Google's advanced algorithms to optimize your campaign performance based on historical data and contextual signals. When you set a Target CPA, you're telling Google Ads how much you're willing to pay on average for each conversion, whether that's a purchase, sign-up, or other valuable action. The system then analyzes numerous factors in real-time, including device type, location, time of day, browser, operating system, and user behavior patterns to determine the optimal bid for each individual auction. This strategy is particularly effective for advertisers who have clear conversion goals and want to maintain predictable acquisition costs while scaling their campaigns. To use Target CPA bidding effectively, your campaign should have a sufficient conversion history, typically at least 30 conversions in the past 30 days, allowing the algorithm to learn and make accurate predictions. It's important to set a realistic target CPA based on your historical conversion data and business margins. Setting the target too low may limit your reach and volume, while setting it too high could result in overspending. Google recommends starting with a target that aligns with your current average CPA and adjusting based on performance over time. The algorithm requires a learning period to optimize effectively, during which performance may fluctuate. Patience during this phase is essential for achieving optimal results. Target CPA bidding removes the manual effort of bid adjustments and allows you to focus on strategic decisions while the system handles tactical optimization across thousands of daily auction opportunities.

Target ROAS (Return on Ad Spend) Bidding is a Smart Bidding strategy in Google Ads that automatically sets bids to help you achieve your desired return on ad spend. This powerful automation tool uses machine learning to optimize your bids in real-time, analyzing numerous signals to predict which clicks are most likely to generate valuable conversions for your business.

When you set a Target ROAS, you specify the average conversion value you want to receive for every dollar spent on ads. For example, if you set a Target ROAS of 400%, Google Ads will aim to generate $4 in conversion value for every $1 you spend on advertising.

The algorithm considers multiple factors when determining bid amounts, including device type, location, time of day, remarketing lists, browser, operating system, and actual search queries. This comprehensive analysis happens at auction time, allowing for precise bid adjustments that manual bidding simply cannot match at scale.

To use Target ROAS effectively, you need to have conversion tracking properly configured and assign values to your conversions. Google recommends having at least 15 conversions in the past 30 days before implementing this strategy, though more data generally leads to better performance.

Target ROAS works well for businesses that track revenue or assign specific values to different conversion actions. E-commerce advertisers particularly benefit from this strategy since they can track actual purchase values.

The system may adjust individual bids above or below your target to maximize overall returns, meaning some conversions might come at a higher or lower ROAS than your target. However, the goal is to achieve your specified ROAS on average across all conversions.

This bidding strategy saves significant time compared to manual bid management while leveraging sophisticated machine learning capabilities that continuously improve as more data becomes available. It represents a shift toward value-based optimization rather than focusing solely on clicks or conversion volume.

Maximize Conversions is a Smart Bidding strategy in Google Ads that uses machine learning to automatically optimize bids and help advertisers get the most conversions within their specified budget. This automated bidding approach leverages Google's advanced algorithms to analyze vast amounts of data and make real-time bid adjustments for each auction.

When you implement Maximize Conversions, Google's system evaluates numerous signals including device type, location, time of day, browser, operating system, and user behavior patterns. The algorithm processes these contextual signals to determine the optimal bid amount that will likely result in a conversion for each individual search query.

This strategy works by spending your entire daily budget while focusing on generating the highest possible number of conversions. It's particularly effective for advertisers who have a fixed budget and want to drive as many valuable actions as possible, whether those are purchases, sign-ups, form submissions, or other defined conversion goals.

To use Maximize Conversions effectively, you should have conversion tracking properly configured in your Google Ads account. The system requires historical conversion data to learn and optimize performance over time. Generally, having at least 15-30 conversions in the past 30 days helps the algorithm perform more efficiently.

Key benefits of this strategy include reduced manual bid management, improved efficiency through automation, and the ability to capitalize on real-time auction dynamics. The machine learning model continuously adapts to changing market conditions and user behaviors.

Advertisers should monitor performance regularly and ensure their daily budget aligns with their goals. Some may choose to add a target cost-per-acquisition (CPA) to this strategy, creating what's known as Target CPA bidding, which provides additional control over how much you're willing to pay per conversion while still leveraging automation.

Maximize Conversion Value is a Smart Bidding strategy in Google Ads that uses machine learning to automatically optimize bids in real-time auctions. The primary goal of this strategy is to help advertisers get the highest total conversion value within their specified budget.

Unlike Maximize Conversions, which focuses on generating the highest number of conversions, Maximize Conversion Value prioritizes the quality and monetary worth of each conversion. This makes it particularly valuable for businesses where different conversions have varying values, such as e-commerce stores where purchases range from small to large amounts.

The algorithm analyzes numerous signals at auction time, including device type, location, time of day, browser, operating system, and user behavior patterns. By processing these contextual signals, the system determines the optimal bid for each individual auction to maximize the overall value returned from your advertising spend.

To use this strategy effectively, you must have conversion tracking properly configured with assigned values for each conversion action. These values can be static (fixed amounts assigned to specific actions) or dynamic (variable values passed through your website, typically representing actual transaction amounts).

You can also add an optional target Return on Ad Spend (tROAS) constraint to this strategy. When tROAS is set, the system will attempt to achieve your desired return while still maximizing conversion value. This provides additional control over efficiency while maintaining the value-focused optimization approach.

Maximize Conversion Value works best for advertisers who have sufficient conversion data and understand the relative worth of their various conversion actions. It requires at least a few weeks of learning period for the algorithm to optimize effectively. During this time, performance may fluctuate as the system gathers data and refines its bidding approach to deliver the best possible results for your campaigns.

Enhanced CPC (eCPC) is a semi-automated bidding strategy in Google Ads that combines manual bidding with machine learning to help advertisers optimize their conversions. This strategy allows you to set your own maximum cost-per-click bids while Google's algorithm automatically adjusts those bids in real-time based on the likelihood of a click leading to a conversion.<br><br>When you enable eCPC, Google analyzes various signals at auction time, including device type, browser, location, time of day, and remarketing lists. Based on this analysis, the system will increase your bid when it detects a higher probability of conversion, and decrease it when the conversion likelihood appears lower. This dynamic adjustment happens for each individual auction.<br><br>One key advantage of eCPC is that it serves as a bridge between fully manual bidding and fully automated strategies like Target CPA or Maximize Conversions. It gives advertisers who prefer maintaining some control over their bids the ability to benefit from machine learning optimization simultaneously.<br><br>For eCPC to work effectively, conversion tracking must be properly set up in your Google Ads account. The system relies on historical conversion data to make informed bid adjustments. Accounts with more conversion data typically see better performance from this strategy.<br><br>It is important to note that eCPC works within the bounds of your manual bids. While Google may raise bids above your maximum CPC for promising opportunities, the system aims to keep your average CPC at or below your max bid over time.<br><br>eCPC is particularly useful for advertisers who are transitioning from manual bidding to automated strategies, as it provides a comfortable middle ground. It allows marketers to maintain oversight of their campaigns while still leveraging Google's powerful machine learning capabilities to improve conversion rates and overall campaign performance.

Maximize Clicks is an automated bidding strategy within Google Ads that focuses on generating the highest possible number of clicks for your advertising budget. This Smart Bidding option is particularly useful for advertisers who want to drive traffic to their website and increase visibility.

When you select Maximize Clicks, Google's machine learning algorithms automatically set your bids to help you receive as many clicks as possible within your specified daily budget. The system analyzes various signals and auction-time data to determine the optimal bid for each auction, adjusting in real-time to capture click opportunities.

Key features of Maximize Clicks include:

1. Budget Optimization: The strategy works to spend your entire daily budget efficiently across all eligible auctions, ensuring you get maximum value from your investment.

2. Optional Bid Cap: You can set a maximum cost-per-click (CPC) limit to maintain control over how much you pay for individual clicks. This prevents unexpectedly high bids on competitive keywords.

3. Time-Saving Automation: Instead of manually adjusting bids for each keyword, the automated system handles bid management, freeing up time for other campaign optimizations.

4. Ideal Use Cases: This strategy works well for brand awareness campaigns, driving website traffic, building remarketing lists, or when you have limited conversion data to use value-based bidding strategies.

5. Learning Period: Like other Smart Bidding strategies, Maximize Clicks requires time to learn and optimize performance based on your campaign data.

Considerations when using Maximize Clicks: While this strategy excels at generating traffic, it does not optimize for conversions or conversion value. Advertisers primarily focused on leads, sales, or specific actions may benefit more from conversion-based strategies like Maximize Conversions or Target CPA. Maximize Clicks serves as an excellent starting point for new campaigns or when building initial traffic data before transitioning to more sophisticated bidding approaches.

Manual CPC (Cost-Per-Click) Bidding is a bid strategy in Google Ads where advertisers maintain complete control over their maximum cost-per-click bids for individual keywords, ad groups, or campaigns. This approach allows marketers to set specific bid amounts based on their own analysis and business objectives rather than relying on automated systems to adjust bids.

With Manual CPC Bidding, advertisers determine the maximum amount they are willing to pay each time a user clicks on their advertisement. This level of control is particularly valuable for businesses that have deep knowledge of their customer acquisition costs, profit margins, and the relative value of different keywords to their operations.

Key characteristics of Manual CPC Bidding include the ability to prioritize high-performing keywords by allocating higher bids to terms that consistently drive conversions. Advertisers can also reduce bids on underperforming keywords to minimize wasted spend. This granular control enables precise budget allocation across campaigns.

The strategy is well-suited for advertisers who are new to Google Ads and want to understand how different bid levels affect their ad performance before transitioning to automated strategies. It also benefits those with smaller accounts where the data volume may not be sufficient for machine learning algorithms to optimize effectively.

However, Manual CPC Bidding requires significant time investment for monitoring and adjustments. Advertisers must regularly analyze performance data, competitive landscapes, and market conditions to make informed bidding decisions. This can become challenging as account complexity grows.

Google also offers Enhanced CPC as an optional feature within manual bidding, which allows the system to adjust your manual bids slightly to help maximize conversions while still maintaining overall control. This serves as a middle ground between fully manual and fully automated bidding approaches, providing some optimization assistance while keeping the advertiser in the decision-making seat.

Portfolio Bid Strategies in Google Ads are automated bid strategies that can be applied across multiple campaigns, ad groups, and keywords simultaneously, allowing advertisers to manage and optimize their bidding at scale from a single location. Unlike standard bid strategies that operate at the individual campaign level, portfolio strategies bundle multiple campaigns together under one unified bidding approach. This centralized management system enables Google's machine learning algorithms to optimize bids based on collective performance data from all included campaigns, potentially leading to better overall results. When you create a portfolio bid strategy, you can choose from various automated bidding options such as Target CPA (Cost Per Acquisition), Target ROAS (Return on Ad Spend), Maximize Conversions, Maximize Conversion Value, or Target Impression Share. The key advantage is that the system learns faster because it draws insights from a larger pool of data across all campaigns in the portfolio. Portfolio bid strategies are particularly beneficial for advertisers managing numerous campaigns with similar goals or performance targets. For example, if you have ten campaigns all aiming for a $50 cost per acquisition, grouping them into a portfolio strategy allows the algorithm to balance spending and bidding decisions holistically. Some campaigns might temporarily exceed the target while others stay below, but the overall portfolio maintains the desired CPA. You can access and create portfolio bid strategies through the Shared Library in your Google Ads account under Bid Strategies. From there, you can monitor performance, make adjustments to targets, and add or remove campaigns as needed. This approach simplifies account management, saves time, and leverages the full power of Google's Smart Bidding technology by providing more data signals for the machine learning models to work with, ultimately helping achieve your advertising objectives more efficiently.

The Bid Strategy Learning Period is a critical phase in Google Ads Smart Bidding where the automated system gathers data and optimizes performance for your campaigns. When you implement a new Smart Bidding strategy or make significant changes to an existing one, Google's machine learning algorithms require time to analyze patterns and understand how various factors influence conversions and campaign performance.

During this learning period, which typically lasts about seven days, the system collects information about user behavior, conversion patterns, auction dynamics, and other relevant signals. The algorithm tests different bid amounts across various auctions to determine the optimal bidding approach for achieving your specified goals, whether that's maximizing conversions, targeting a specific cost per acquisition (CPA), or achieving a desired return on ad spend (ROAS).

You'll notice a "Learning" status indicator in your Google Ads account during this phase. Performance during the learning period may fluctuate more than usual as the system experiments with different strategies. It's important to allow the algorithm sufficient time to complete this process before making judgments about effectiveness or implementing additional changes.

Making frequent modifications to your bid strategy, budget, or conversion actions can restart the learning period, prolonging the optimization process. Best practices suggest maintaining stability during this time and avoiding major campaign adjustments. Google recommends having at least 30 conversions in the past 30 days before implementing certain Smart Bidding strategies to provide adequate data for the learning process.

Once the learning period concludes, your bid strategy enters an "Eligible" or "Active" status, indicating that the system has gathered enough information to bid effectively. At this point, performance typically stabilizes, and the algorithm continues to refine its approach based on ongoing data collection. Understanding and respecting the learning period is essential for maximizing the effectiveness of Smart Bidding automation in your Google Ads campaigns.

Smart Bidding Signals are the contextual data points that Google's machine learning algorithms analyze in real-time to optimize your bids for each auction. These signals help determine the likelihood of a conversion and adjust bids accordingly to maximize your campaign performance.

There are numerous signals that Smart Bidding evaluates during every auction. Device type is one key signal, as user behavior varies between mobile, desktop, and tablet. Location signals consider where the user is physically located and their location of interest. Time-based signals include day of week and time of day, recognizing that conversion rates fluctuate throughout different periods.

Audience signals examine remarketing lists, allowing the system to bid differently for users who have previously interacted with your website versus new visitors. The actual search query itself serves as a powerful signal, going beyond just the keyword match to understand user intent more precisely.

Browser and operating system data help identify patterns in how different technology users convert. Language settings provide context about the user's preferences. Ad characteristics, including which creative elements are being shown, factor into bid decisions.

For Search campaigns specifically, Smart Bidding also considers search partner data and interface differences across various Google properties. Price competitiveness signals in Shopping campaigns help understand how your pricing compares to competitors.

The power of Smart Bidding lies in its ability to process these signals simultaneously in milliseconds, something impossible for manual bidding. The system learns from historical conversion data and continuously improves its predictions. Cross-signal combinations reveal patterns that individual signal analysis would miss.

By leveraging these comprehensive signals, Smart Bidding strategies like Target CPA, Target ROAS, Maximize Conversions, and Maximize Conversion Value can make informed bid adjustments for every single auction, ensuring your budget is allocated toward the opportunities most likely to achieve your advertising goals.

Bid adjustments in Google Ads are percentage-based modifications that allow advertisers to increase or decrease their bids based on specific criteria and contexts. These adjustments help optimize campaign performance by allocating more or less budget to situations that are more or less valuable to your business.

There are several types of bid adjustments available:

**Device Adjustments**: You can modify bids for mobile, desktop, or tablet devices. For example, if mobile users convert at a higher rate, you might increase mobile bids by 20%.

**Location Adjustments**: Target geographic areas with different bid levels. If customers in certain cities generate more revenue, you can bid more aggressively for those locations.

**Ad Schedule Adjustments**: Modify bids based on time of day or day of week. If your business sees better conversion rates during business hours, you can increase bids during those periods.

**Audience Adjustments**: Bid differently for specific audience segments like remarketing lists or demographic groups.

**When Using Smart Bidding**: Its important to understand that Smart Bidding strategies like Target CPA, Target ROAS, and Maximize Conversions use machine learning to automatically set optimal bids at auction time. When Smart Bidding is enabled, most manual bid adjustments become unnecessary or are handled differently.

With Smart Bidding, device bid adjustments are typically set to 0% because the algorithm accounts for device performance automatically. However, you can still use device adjustments to exclude certain devices entirely by setting a -100% adjustment.

Location and ad schedule adjustments may still be applied in some Smart Bidding scenarios, but the algorithm already considers these signals when determining bids.

The key benefit of combining bid adjustments with automation is letting machine learning handle the complex, real-time optimization while you provide strategic direction through your targets and any exclusions you want to enforce.

Device bid adjustments in Google Ads allow advertisers to modify their bids based on the type of device a user is searching from - desktop computers, mobile phones, or tablets. This feature gives you granular control over how much you're willing to pay for clicks depending on which device delivers the best results for your business.

When setting device bid adjustments, you can increase or decrease your base bid by a percentage ranging from -100% to +900%. For example, if your base bid is $1.00 and you set a +50% mobile bid adjustment, your effective bid on mobile devices becomes $1.50. Conversely, setting a -100% adjustment essentially removes your ads from appearing on that specific device type.

The strategic importance of device bid adjustments lies in recognizing that user behavior varies significantly across devices. Mobile users might be searching on-the-go with different intent than desktop users who may be conducting more detailed research. Your conversion rates, cost-per-acquisition, and return on ad spend often differ substantially between devices.

However, it's crucial to understand how device bid adjustments interact with Smart Bidding strategies. When you use automated bidding strategies like Target CPA, Target ROAS, Maximize Conversions, or Maximize Conversion Value, Google's machine learning algorithms automatically optimize bids in real-time based on numerous signals, including device type. In these cases, manual device bid adjustments become less relevant because the system already accounts for device performance.

For Smart Bidding campaigns, Google recommends against layering manual device adjustments on top of automated strategies, as this can interfere with the algorithm's optimization capabilities. The exception is setting a -100% adjustment to completely exclude a device type if you have a specific business reason.

To determine appropriate device bid adjustments for manual bidding strategies, analyze your campaign performance data segmented by device in Google Ads reports, then adjust bids accordingly to maximize your advertising efficiency.

Location Bid Adjustments in Google Ads allow advertisers to increase or decrease their bids based on the geographic location of potential customers. This powerful feature enables businesses to optimize their advertising spend by focusing more resources on areas that generate better results while reducing investment in underperforming regions.<br><br>With location bid adjustments, you can modify your bids by percentages ranging from -90% (reducing your bid significantly) to +900% (dramatically increasing your bid). For example, if you notice that customers in a particular city convert at a higher rate, you might set a +20% bid adjustment for that location, meaning your bids will be 20% higher when users from that area search for your keywords.<br><br>When using Smart Bidding strategies like Target CPA, Target ROAS, or Maximize Conversions, the relationship with location bid adjustments changes. Smart Bidding algorithms automatically factor in location signals as part of their machine learning process. The system analyzes historical performance data across different geographic areas and adjusts bids in real-time to achieve your specified goals.<br><br>For Smart Bidding campaigns, Google recommends setting location targeting preferences rather than manual bid adjustments, as the automated system already accounts for geographic performance variations. The algorithm considers numerous signals simultaneously, including device, time of day, audience characteristics, and location, making manual adjustments potentially redundant or even counterproductive.<br><br>However, advertisers using manual bidding or enhanced CPC can benefit significantly from location bid adjustments. To implement them effectively, analyze your geographic performance reports regularly, identify high-value and low-value regions, and adjust bids accordingly. Consider factors like local competition, seasonal trends, and regional purchasing behavior.<br><br>Best practices include starting with modest adjustments, monitoring performance over sufficient time periods, and avoiding extreme modifications that could limit your reach. Location bid adjustments remain a valuable tool for maximizing ROI when used strategically within your broader campaign optimization approach.

Audience Bid Adjustments in Google Ads allow advertisers to modify their bids based on specific audience segments, enabling more precise control over how much they are willing to pay for clicks from different user groups. This feature is particularly valuable when combined with Smart Bidding strategies, though it functions differently depending on the bidding approach selected.

When using manual bidding strategies, audience bid adjustments let you increase or decrease your bids by a percentage for specific audience lists. For example, if you have identified that users who previously visited your website are more likely to convert, you can set a positive bid adjustment of 20% to 50% for your remarketing audience. Conversely, you might reduce bids for audiences that historically show lower conversion rates.

Audience segments can include remarketing lists, customer match lists, similar audiences, in-market audiences, affinity audiences, and detailed demographics. Each segment can receive its own bid adjustment ranging from -90% to +900%, giving advertisers significant flexibility in targeting.

However, when Smart Bidding strategies like Target CPA, Target ROAS, or Maximize Conversions are employed, the relationship with audience bid adjustments changes. Smart Bidding algorithms automatically analyze audience signals as part of their machine learning process. They consider user characteristics, browsing behavior, and historical performance data to optimize bids in real-time during each auction.

In Smart Bidding scenarios, manual audience bid adjustments are typically overridden because the algorithm makes its own calculations. The exception is setting a -100% bid adjustment, which completely excludes an audience from seeing your ads.

Best practices suggest layering audiences in observation mode when using Smart Bidding, allowing you to gather performance data across different segments. This data helps inform future campaign strategies and provides insights into which audiences deliver the strongest results for your advertising goals.

Seasonality Adjustments in Google Ads are an advanced Smart Bidding feature that allows advertisers to inform Google's automated bidding algorithms about expected short-term changes in conversion rates. This tool is particularly valuable during promotional events, sales periods, holidays, or any predictable fluctuations in consumer behavior that might temporarily affect campaign performance.

When you anticipate a significant change in conversion rates for a specific time period, such as a Black Friday sale or a limited-time promotion, you can apply a seasonality adjustment to help Smart Bidding strategies respond more effectively. The algorithm typically learns from historical data, but sudden changes can take time for the system to recognize and adapt to. Seasonality adjustments bridge this gap by providing the bidding system with advance notice of expected performance shifts.

To implement a seasonality adjustment, advertisers specify the date range, the campaigns or devices affected, and the expected percentage change in conversion rate. For example, if you expect conversion rates to increase by 50% during a weekend flash sale, you would input this information so the bidding algorithm can adjust bids accordingly during that specific period.

Best practices for using seasonality adjustments include reserving them for short-term events lasting one to seven days, as Smart Bidding can typically adapt to longer-term trends on its own. Advertisers should also ensure they have accurate historical data to estimate expected conversion rate changes. After the event concludes, reviewing actual performance against predictions helps refine future adjustments.

Seasonality adjustments work with various Smart Bidding strategies including Target CPA, Target ROAS, Maximize Conversions, and Maximize Conversion Value. This feature gives advertisers more control over automated bidding while still benefiting from machine learning optimization, making it an essential tool for managing campaigns during predictable periods of unusual activity.