Overview
The rules of the Google Ads bidding system have evolved considerably and go beyond simple manual adjustments: traders can now use predictive models capable of improving bids in real time and thus boosting return on investment.
We have summarised the basics of SEA bidding strategies for you and explored the new innovations available. The aim is to help you get the most out of Smart Bidding and, more broadly, AI in your Google Ads campaigns.
1.Understanding how SEA auctions work
As with any discipline, it is not advisable to rush things. You must first master the fundamentals of the Google Ads auction system and its foundations before you can take advantage of advanced bidding strategies.
When a user enters a query into the Google search engine, an automatic auction is launched to determine which adverts will be displayed in the search results and in what order they will appear.
Basic principle of Google Ads auctions
The Google Ads auction system is not based on the highest bidder rule. The aim is to develop an environment with more opportunities for brands and, above all, greater relevance for users.
Several factors influence the ranking of adverts, also known as Ad Rank:
- The maximum cost of the bid per click
- The Quality Score based on the relevance of the ads, the expected click-through rate and the quality of the landing page;
- Ad extensions and other contextual signals (device, location, time, performance history, etc.).
With this system, the relevance of the ad can take precedence over the bid level. It is therefore important in your strategy to find the right balance between creative and technical optimisation and bid level.
The key role of Quality Score
Quality Score will directly impact the price and visibility of your campaigns. The higher your score, the more you can:
- Pay for good positioning at a lower cost
- Optimise your click-through rate
- Improve your Ad Rank while maintaining the same level of investment
The Quality Score is therefore a real performance booster in your SEA bidding strategies.
2.Categorisation of bidding strategies
When creating a campaign, the Google Ads platform now allows you to choose between two bidding strategy options: manual bidding and automated bidding. To ensure that your campaigns are in line with your marketing objectives, it is essential to understand the distinctive features of each.
Manual strategies: total control over distribution but time-consuming
With a manual bidding strategy, you can set your own CPC (cost per click) for your various keywords and ad groups.
Advantages:
- Total control over your bids;
- Ability to change settings at any time based on performance;
- Best option for low-budget or highly segmented campaigns.
The limitations:
- Tedious and time-consuming management;
- Advanced expertise required to optimise budget investment;
- Greater vulnerability to market fluctuations.
Automated strategies: AI at the service of performance
The automated bidding system relies on Google algorithms that adjust bids in real time based on conversion probabilities. Several automated strategies are available depending on your objectives:
- Maximise clicks: to generate maximum traffic within a defined budget;
- Maximise conversions: boost conversion volume by tracking performance signals.
- Target CPA (Cost Per Acquisition): determine an average acquisition cost to achieve/not exceed.
- Target ROAS (Return on Advertising Spend): optimise bids to achieve a specific return on investment.
3. Smart Bidding: when Artificial Intelligence optimises your bids
Smart Bidding is currently the most advanced feature of Google Ads bidding. It uses automated learning models called machine learning to adapt bids in real time at the moment of competition and according to the chances of conversion of an impression.
How does Smart Bidding work?
Data from previous campaigns, such as clicks or conversions, will help the algorithm to learn and better identify the potential value of a user.
For each bid, the algorithm will optimise the cost per click to increase the probability of achieving objectives, whether it be conversion volume, a defined CPA or a positive ROAS.
The AI evaluates a large number of signals simultaneously:
- The device used (mobile, desktop, tablet);
- The time and day of the week;
- Geolocation;
- The type of browser;
- Previous behaviour on the site.
The advantages of Smart Bidding
- Smart Bidding really saves time by reducing operational workload.
- It also ensures continuous performance improvement by enriching itself with new user data in real time.
- Bids are adjusted more accurately based on context and user behaviour.
To get the most out of this system, it is essential to have large volumes of data and, above all, to rely on reliable and robust tracking to avoid any bias in the learning system.
4. Advanced Google Ads bidding strategies
Google has also developed advanced bidding strategies that combine automation with a strategic approach to campaign delivery. These strategies are based on detailed segmentation of audiences, products and objectives.
a) Layered bidding strategy
With this method, your campaigns will be divided according to their performance or value:
- Top performers: highly profitable products or keywords, with an aggressive target ROAS;
- Middle performers: campaigns with potential, to be nurtured with an optimised CPA or CPC;
- Low performers: segments being tested or with low volume.
- This allows investments to be better prioritised according to their value, enabling smarter budget management.
b) Retargeting based on engagement signals
Retargeting is a strategy that aims to re-engage users who have previously interacted with your brand. By applying rules based on specific signals to this strategy, you can:
- Choose to target a higher CPA for visitors to the shopping basket;
- Lower bids on less qualified audiences;
- Combine intent signals with dynamic remarketing lists.
With good interconnectivity with your Google Analytics 4 or CRM account, you can go to very granular levels such as defining bid levels based on customer value or their position in the conversion funnel.
c) Leveraging specific KPIs
Regardless of the bidding strategy, it is essential to define and monitor a specific indicator:
- CPA to measure the cost of a conversion;
- ROAS to evaluate advertising profitability;
- CLV (Customer Lifetime Value) to estimate the long-term value of the customer.
The aim is to go beyond simple conversion logic and manage campaigns according to the real economic value of the customer.
5. Optimising campaigns according to objectives
Your objectives are a determining factor in the successful optimisation of SEA bids. We will define a specific strategy for each objective.
Traffic generation
If your primary objective is to increase visits to your website:
- Opt for the Maximise clicks strategy;
- Set up A/B testing on your adverts to improve the CTR;
- Target high-volume, low-competition keywords.
For this objective, effective Quality Score optimisation is essential for better cost control.
Maximise conversions
If you are more performance-oriented or if you have an e-commerce site:
- Select the Maximise conversions or Target CPA option;
- Set up separate campaigns for each stage of the funnel;
- Use Dynamic Search Ads (DSA) to capture uncovered intentions.
If possible, it can be very useful to integrate first-party data signals (CRM, customer audiences, frequent visitors) to enrich the algorithm and enable more relevant bids.
Increase revenue
For e-commerce businesses or profit-oriented companies:
- Set up a target ROAS to ensure a balance between volume and profitability.
- Focus on medium- and high-margin products.
- Connect product feeds to Google Merchant Centre for automatic price and availability updates.
This will allow you to manage bids based on actual ROI rather than sales volume.
6.Tools and technologies for advanced bidding
SEA bidding is so powerful thanks to tools that allow you to centralise, analyse and automate bids.
a)Bid managers and automation platforms
To manage your various accounts and communication channels simultaneously, you can rely on tools such as Search Ads 360, Skai (formerly Kenshoo) or Optmyzr.
What they offer:
- Centralisation of multi-platform data (Google, Bing, Meta);
- Advanced reporting;
- Automation of adjustments according to predefined rules.
The use of these platforms will prove particularly useful for large accounts, but also for international campaigns, which often involve more complex management.
B)Artificial Intelligence and machine learning
The rise of AI is affecting all areas, and paid search tools are no exception, with AI technologies playing a major role in advanced bidding. They will enable the analysis of very large amounts of data in order to determine the bid combinations likely to perform best:
- Real-time bid correction based on different conversion signals
- Anticipation of changing trends based on seasonality
- Management of budget fluctuations through automated scripts
- Predictive models anticipate seasonal trends
c) Data as a foundation
For your Smart Bidding strategy to work, one key element is essential: reliable, high-volume data.
To guarantee this, you need to rely on:
- Comprehensive tracking via GA4, Google Tag Manager and Consent Mode v2
- CRM integration to link online/offline data
- Importing offline conversions to refine the performance model
Comprehensive and robust data governance guarantees greater accuracy for your Smart Bidding model and more relevant bidding decisions.
Conclusion
Google Ads bidding systems have become a real pillar of digital performance strategies. Manual, automated or Smart Bidding strategies... the platform offers you multiple options depending on your objectives, available data and human capabilities. For maximum performance, the most advanced advertisers combine technology, analysis and human expertise.
At Eminence, our team of paid media experts supports companies in creating and deploying advanced bidding strategies aligned with their needs and capabilities. Using AI and data, we guarantee that media budgets are transformed into real growth drivers.
FAQ
How does Smart Bidding work?
Smart Bidding uses machine learning to automatically adjust your bids for each query. This system analyses millions of contextual signals, such as device, location and past behaviour, to predict which clicks are most likely to lead to a conversion.
What are the advantages of Smart Bidding?
Smart Bidding saves time, increases accuracy, and improves performance by continuously learning from campaign data. This allows marketers to focus on strategy rather than manual bid management.
What are the most commonly used Smart Bidding strategies?
The main Smart Bidding strategies are:
- Maximise conversions
- Target CPA (Cost Per Acquisition)
- Target ROAS (Return on Advertising Spend)
- Maximise conversion value
Each of these strategies is designed to align bidding decisions with specific marketing objectives, from generating traffic to generating value.
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