How does smart bidding work with Google Ads?
Smart bids are automated bidding strategies in Google Ads that integrate advertising metrics such as keywords, target groups or user profiles into campaign planning for greater success. Machine learning is used to set the best bids for your strategies.
- What is smart bidding?
- How does smart bidding in Google Ads work?
- Business goals and bidding strategies for Google Ads
- Google smart bidding strategies in detail
- What are the pros and cons of Google smart bidding?
- Which signals are important in smart bidding?
- How to implement a smart bidding strategy correctly
- Examples of best practices
- Conclusion: smart bidding for cost-efficient ad campaign
What is smart bidding?¶
Smart bidding is considered a subset of automated bidding strategies. Based on machine learning, the algorithm draws on various signals and values to place campaign bids. Instead of costly and time-consuming manual bidding, smart bidding strategies make automated decisions. This results in more successful, cost-efficient campaigns and optimal return on investment (ROI) or return on advertising spend (ROAS).
How does smart bidding in Google Ads work?¶
Without Google smart bidding, you would have to develop your own strategies and analyze target groups, keywords and millions of signals for search engine advertising (SEA) and search engine marketing (SEM). Based on these market and advertising analyses, you would also have to set bids for lucrative advertising positions in auctions within milliseconds which is hardly conceivable without artificial intelligence and automation.
Smart bidding does this by calculating available signals for ad positions and campaign targets. It then bidding for the best ad slots for the keyword or signal on digital ad exchanges such as Ad Exchange, all in a few seconds. Strategies are adapted to your needs by incorporating advertising context and business goals. This means your campaign budget is more effectively implemented, along with automated advert buying and selling through programmatic advertising, programmatic buying and real-time advertising.
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Business goals and bidding strategies for Google Ads¶
Google distinguishes between two smart bidding goals:
- Increase sales/leads: conversions with defined budget or fixed return on investment (ROI)
- Increase profit: conversions with a defined budget or fixed return on advertising spend (ROAS)
The difference between ROI and ROAS is that ROI refers to actual profit after expenses and deductions. ROAS describes total revenue. While ROI is a measure of financial profitability and the revenue-cost ratio of a campaign, ROAS refers to the success and the expense-revenue ratio of individual campaign elements such as display advertising.
Google smart bidding strategies in detail¶
Depending on your business goals, the following smart bidding strategies may be useful:
Conversions refer to specific marketing objectives to increase sales or leads. This includes conversions from visit to lead/purchase interest and conversions from lead/purchase interest to purchase. You need as many prospects, buyers, or clicks as you can get for your set budget to maximize conversions and increase return on investment.
Target CPA/tCPA for optimized conversions¶
tCPA (target Cost per Action) defines the greatest possible conversions at a fixed budget for advertising costs or the conversion value. As the advertiser, you determine the price of a conversion. The algorithm efficiently allocates your advertising budget to selected conversions. One tip is to start with a few conversion types and allow the algorithm approximately 30 days to learn.
Maximize conversion value¶
A value is assigned to each conversion. The strategy sets bids in the budget framework to maximize the overall value, i.e. the return on advertising spend (ROAS) to increase targeted conversions and the overall conversion value. It does this irrespective of the different measurement and conversion values.
Target ROAS/tROAS for optimized conversion value¶
You define the Return on Advertising Spend you want to get your tROAS. Note the ROAS value doesn’t have to be identical to the tROAS value. tROAS is only worthwhile if sufficient data is available, around 50 conversions over the past 30 days should suffice.
Maximize clicks/automate CPC¶
The automated cost per click (CPC) is used when the algorithm sets bids as soon as clicks have a high probability of leading to conversions. If the probability is low, the bid is lowered.
Percentage of potential impressions¶
You define whether ads should be placed above or below the competition. The upper limit for Cost per Click limits high bids.
It is important to try to use bidding strategies when the algorithm can draw on plenty of data. Conversion values or strategies that are changed too often and too quickly during the learning phase can have a negative effect on efficiency.
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What are the pros and cons of Google smart bidding?¶
Automated bidding strategies mean the algorithm sets bids for your campaign in milliseconds and bids for cost-effective, successful advertising positions. Machine learning incorporates a vast number of context signals and creates bids according to predefined goals. Attribution models and business goals are used to train the algorithm on the conversion values that are important to you. Analytics tools and performance reports allow you to see how successful your campaign is.
Overview of the most important pros:
- Cost-efficient, contextual placement of bids and bidding for suitable advertising positions
- Automated bidding strategies based on machine learning
- Predefined performance targets take into account business objectives and signals
- Analytics tools provide transparent evaluations and reports
- Time and cost savings for more successful and efficient campaigns
One con is that the algorithm depends on data. It has a learning phase and needs data to learn from. This can include information from purchases or user behavior, sales, profits and page traffic collected using conversion tracking and data mining tools.
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Which signals are important in smart bidding?¶
Millions of signals and data on usage and purchasing behavior play a role in placing bids. The most important signals and characteristics include:
- Operating system
- Estimated income
- Interests/search behavior
- Purchase behavior
- Click depth/click behavior
- Accessing important pages
- Reaction to CTAs
- Website behavior
- Remarketing lists
How to implement a smart bidding strategy correctly¶
First, ensure prerequisites such as conversion tracking, defined target groups, realistic business goals and advertising budgets are met for an efficient Google Ads bidding strategy. Important questions you should be able to answer include:
- Do you wish to recover maximum advertising costs? In this case, the Google Ads bidding strategy “Maximize conversion value” is recommended.
- Do you want to recover a defined multiple of your advertising costs? In that case, we recommend “Target ROAS” set at “600%” for six times the conversion value.
- Do you want to define the cost of an advertising measure? Use “Target CPA” and set the maximum budget for as many conversions as possible.
- Are you looking to achieve the maximum number of conversions through certain advertising measures and actions? Select “Maximize conversions” to get the maximum number of conversions for the corresponding action/advertising position.
Examples of best practices¶
To use smart bidding more efficiently you can follow the best practices below:
Activate conversion tracking¶
Conversion tracking is at the heart of smart bidding. You need data for a cost-effective campaign with lots of conversions. Enable conversion tracking and collect data that Google smart bidding can work with. The information allows you to more effectively evaluate user signals and place bids based on reliable calculations. It’s important you don’t just track macro conversions like “buy” or “don’t buy”. Micro conversions such as click behavior and dwell time on pages or ads also play an important role.
Consider learning phase and create data master¶
The algorithm undergoes a learning phase to collect data for automated bid placement. One to two weeks are recommended for the AI to collect and evaluate the data. The learning phase should be taken into account when activating smart bidding for the first time and when adjusting your campaign strategy. Data can be increased in a targeted manner by organizing ads into smaller campaigns. This will help you to increase the amount of data.
Set realistic business goals¶
With strategies such as tCPA or tROAS, avoid setting targets that are too high or too low, but rather base them on previously achieved performance targets. It’s best to approach the desired goals in small 10-percent steps.
Success stories take time¶
Try not to get impatient when it comes to evaluating your campaign. Organic conversions take time before they show up in performance analytics.
“Maximize conversions” at the start¶
Begin with maximizing conversion. This strategy allows you to collect important data later used for tCPAs or tROAS.
Address target groups¶
Use remarketing lists and identify your most important target and customer groups. Remarketing lists can be set in Google Ads, for example.
Consider Google Ads recommendations¶
Take a look at the “Google Ads Recommendations” to find important tips for your campaign.
Conclusion: smart bidding for cost-efficient ad campaign¶
It’s hard to imagine online marketing without machine learning, artificial intelligence, data mining and audience targeting. The same applies to smart bidding which is cost-efficient and saves time for advertising campaigns. The algorithm evaluates millions of user signals and data to help boost sales and profit through your Google Ads bidding strategies. Although it requires familiarization and patience, smart bidding should be a feature of your Google Ads campaigns.