Blog Which Google Ads Automated Bidding Strategies You Should Use

Which Google Ads Automated Bidding Strategies You Should Use

Tatjana Sporihina

According to numerous studies, Google Ads stays among the most frequent tools businesses use for advertising, which is understandable: it’s one of the rare platforms, where we mainly deal with the warm audience, who’s explicitly indicating their interest by entering their search query in Google and hitting the search button.

However, as everyone is doing Google Ads, ever-growing competition increases the average cost per click in almost all niches. For many marketers, that means more time than ever spent on bidding decisions. This is tricky: if your cost per click (CPC) is too low, your ads might not win the auction to be seen frequently enough or may end up in lower positions, where no one could see them and eventually make a click. On the other hand, with high CPC you’re at risk of not even reaching your break-even point for specific keywords and you might lose money.

That’s exactly when automated bidding strategies come in handy. On your behalf, according to your chosen strategy, they will evaluate the competitive landscape, in certain occasions assess the probability of conversion and set your bids accordingly, all this within a fraction of a second.

To make the most out of the automated bidding, you should understand how the strategies are different and how they work, so that you can make the best choice relevant to your specific needs.

Overall, Google Ads now offers 7 automated bidding strategies for Search campaigns, but it’s important to realize that some of them are using machine learning algorithms for predicting the conversion probability, whereas others are designed to purely automate the bidding process without considering potential results.

Automated bidding strategies for Search campaigns include Maximize clicks and Target impression share. The smart machine learning algorithms are powering Target CPA (CPA = Cost per Action), Target ROAS (ROAS = Return on Ads Spend), Maximize conversions and Maximize conversions value strategy. And finally, there’s Enhanced CPC strategy which uses smart learning while still leaving control in the advertiser’s hands.

Automated bidding

When we choose Maximize clicks strategy, Google will try to get us as many clicks as possible within our budget. In this case, it doesn’t make any projections on whether the click might result in a conversion or not. The only goal of this strategy is to get as many clicks as possible without having to bother about manual bidding.

We can also set maximum CPC bid limits to ensure that the system only buys out cheaper clicks. For example, if we have any target CPA value in mind (how much we can afford to pay for a customer) and can make some assumptions on the expected conversion rate (for example, look at how other channels converted or use our industry benchmarks), we can calculate the break-even CPC (equal to our target CPA * expected conversion rate), and set it as the limit.

Choosing Target impression share strategy is somewhat similar, however here we can ask Google to automatically set the bids so that our keywords get our target impression share, be it an overall search impression share, impression share in top results (when we are shown above organic search results) or absolute top impression share (when we are at the first position in paid results).

From practical experience, often the strategy considers the rules set as the necessary minimum. For example, if we configure the strategy to reach 30% of absolute top impressions, the system might exceed it - for example, reach 40% of absolute top impressions, if our budget allows that. This may result in a higher cost per click then you’d be happy with.

To have more control over how the strategy works, we can also set maximum bid limits. However, it’s important to have a balance here between our target impression share and our desired CPC. The common observation is that all other things being equal, the higher our keyword is seen, the more we will pay for each additional click. Hence, if we set maximum bid limits too low, the algorithm will be unable to deliver the results we expect.

Tip: if you have some data in your campaign, before experimenting with Target impression share, you can look at your current impression share and your average CPC, so that you can make realistic assumptions on what your maximum bid limit should be.

The Target impression share strategy might not get you cheaper clicks than you otherwise would, its primary advantage is that it makes your life easier as you don’t need to think about individual bids anymore.

All in all, both Maximize clicks and Target impression share strategies are a good alternative to setting manual bids. Besides, these are among the few reasonable automation possibilities when you just start with your campaigns - this way, you can quickly gain a lot of traffic for further analysis. Also, they might be useful when you don’t have lots of data for machine learning-based strategies but still want to avoid the hassle of manual bidding.

However, both of the previously mentioned strategies don’t care about the quality of traffic. If you use them, it’s even more important to revise your search terms regularly to ensure you only attract relevant users to your website and keep an eye on your conversion rates.

At Magebit we normally use these strategies with very stable campaigns - for example, for our top converting keywords that we are sure about and we want to get the maximum exposure for if it is reasonable from the business point of view.

Enhanced CPC strategy

Enhanced CPC strategy is sort of semi-smart bidding strategy: while you still have to set your bids manually for each keyword, Google Ads will have the freedom of increasing your bids when it feels there’s a higher probability of conversion or decrease them if the conversion is unlikely to happen. This probability is calculated based on the data about your past conversions, hence it’s important to have conversion tracking up and running in your Google Ads account and, ideally, have collected some historical data.

When setting up the strategy, you can define, which focus you want the algorithm to have at the time of bidding - conversion per se or conversion value. This will basically inform the system which of your past conversions data it should look at first to define your probable customer - treat all converters equally or prioritize those with higher transaction value.

Initially, the strategy was designed in the way that the system could increase/decrease your bids up to 30%, but some years ago this cap was removed, and sometimes you may see that you end up paying more for some of your clicks than you have manually set up as Max CPC. Still, according to Google, in the long run, this strategy will try to keep your average CPC below the max you set - this is how you control it.

For us, Enhanced CPC is one of the most frequently used bidding strategies. Although it really becomes more powerful over time as you collect more data about conversions, sometimes we may use it right from the start to ensure that our bids are competitive enough to create traction and generate a sufficient amount of traffic to start analyzing without excessive risk of unreasonably high CPCs.

Smart bidding

The rest 4 strategies are based on machine learning algorithms, and that’s where the real machine power comes in. The algorithms analyze your conversions, identify their common trends in terms of a wide range of auction-time data, like device, location, time of day, language, operating systems, and others, and then use the accrued information in real-time, adjusting your bids accordingly each time you compete with other advertisers. Each of the 4 strategies has a slightly different focus though, regarding what data they rely more upon - conversions or conversion value.

Conversion-based strategies

Maximize conversions strategy will make automated bid adjustment decisions while trying to spend your entire daily budget. Its goal is to get as many conversions as possible, and while cheaper conversions may be prioritized so that your budget can deliver as many of them as possible, the system will not really care about how much each of them will cost.

Target CPA strategy, however, is focused on achieving your target value at the time of an auction, when adjusting the bids. For example, if you decide that you can’t afford to pay more than $10 for a transaction then Google will adjust your bids so that your conversion if it occurs, doesn’t cost you not more than $10. Eventually, the task of this strategy is to get as many conversions as possible at the price you are ready to pay.

Conversion value-based strategies

Maximize conversions value and Target ROAS strategies function very similarly to the conversion-based strategies mentioned above, however, these 2, in addition, will prioritize conversions with a higher value. Maximize conversions value strategy will try to spend your entire budget to deliver as many conversions as needed to ensure you get the maximum overall value or revenue, whereas Target ROAS will set the bids so that at the end of the day you get as many conversions with high value as possible while maintaining your target return on investments. The budget considerations with Target ROAS are secondary - sometimes your daily budget may be exceeded or the system will ask you to increase the budget to deliver better results.

Now, when you understand how each of the strategies works, let’s dig even deeper: read our article on the typical mistakes Google Ads users sometimes make while playing around with automated strategies.

If you want us to make an audit of your PPC campaigns or are looking for an experienced partner who’d overtake the daily management of your Google Ads, just let us know by emailing to info@magebit.com.

Magebit is a full service eCommerce agency specialized in Magento. At Magebit we create the wonders of eCommerce and support small sites as well as large enterprises.

You can contact us at info@magebit.com or through the contact us page.

Tatjana Sporihina
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