Blog Top 5 Reasons Automated Bidding Is Not Working For You (Google Ads)

Digital Marketing | Jun 24, 2020

Top 5 Reasons Automated Bidding Is Not Working For You (Google Ads)

Tatjana Sporihina

Google Ads automated bidding is not delivering good results for you? Check some of the most typical reasons why some advertisers may not see the great performance they expected. If you would like to review the basics at first, here’s an overview of 7 automated bidding strategies available in Google Ads.

1. Insufficient amount of data

As we’ve discussed in our previous article on automated bidding, there are 2 automated strategies (Maximize clicks and Target impressions share) that don’t involve smart learning. These strategies don’t need any conversions data from your account to be up and running, and you can start trying them out right away.

However, the other 5 strategies carefully collect all possible data to calculate the probability of conversion in the future: device, location, time of day, language, operating systems, and other information. The more data they have at their disposal, the higher is the probability that these conclusions are correct (you remember what statistical significance is, right?).

In most cases, you should have at least 15 conversions in your campaign within the last 30 days to use smart strategies. However, according to our observations, it’s really the minimum which obviously doesn’t always feed the algorithm with a sufficient amount of data, as the 15 conversions may be too diverse to identify the commonalities. In our daily work, we’ve seen much better results when switching to smart bidding after having acquired 50+ conversions within the last 30 days.

Does it mean that smart bidding is not suitable for small advertisers who don’t have 15 conversions a month even in their entire account, let alone a single campaign? Or B2B companies whose customer journeys may be enormous and they can wait for several months for a visitor arriving from search ads to eventually convert?

In these cases, we’d recommend experimenting with micro-conversions: instead of only tracking your “big deals” like making a payment or submitting an application, you can think of the entire user journey and identify actions that may precede the actual conversion and occur more often.

For example, for online stores, you can track Add to cart button clicks as conversions. It’s not possible to purchase something without adding it to the cart first, hence this micro-conversion will have a certain likelihood of leading to a purchase. This way you will eventually have more conversions to feed the smart algorithms.

2. Switching to Smart strategies too quickly

This is very closely related to the previous issue. When you are just starting out, it’s tempting to leave all the tedious work to machines. However, at this point, you don’t have any data in your campaign and while technically you can set up any of the strategies right from the start, initially your bids might be set up randomly to acquire the necessary data and start optimizing. Although sometimes you may find yourself lucky with accidentally reaching the right people, more often than not this strategy won’t lead to the results you want and you probably wouldn’t want to rely on luck when it comes to your advertising budgets.

At Magebit, we prefer starting off with manual or, sometimes, Enhanced CPC bidding and over time, once we accrue the necessary amount of conversions, play around carefully with smart bidding strategies.

As mentioned, two of the strategies which don’t involve machine learning can also be applied right away, however, we tend to use them when we are really confident about the performance of the campaign (e.g., we are creating a dedicated campaign for our best keywords), or it’s very important to generate as much traffic as possible within the short period of time.

3. Unrealistic expectations

This one is especially common among beginners: when in their campaigns, which are set to manual bidding, they don’t get the results they would be happy with, instead of analyzing the performance and solving problems, they decide to leverage the machine power - after all, aren’t machines often smarter than people when it comes to calculations? In some cases, they would switch their poorly-optimized campaigns to smart bidding strategies, while in others, they also set targets that are objectively impossible to achieve: if your CPA over the last months has been $60, it’s unlikely that you will immediately see good results if you set your target CPA to $10.

As a rule of thumb, you should treat the smart strategies as a way to scale your existing results, and only after the initial learning phase, you can start optimizing by slightly tweaking your targets. Hence, we’d recommend setting up the initial targets for smart bidding close to what you already have in your campaign. This way you’re not limiting the learning process of the algorithm with the unrealistic goals.

And, switching a poor campaign to smart bidding is a big no-no for us: we at Magebit will only set an auto-pilot for the campaigns, that we are sure about in terms of conversions, and just want to spare more time we would otherwise spend on manual bidding.

4. Playing all-in with smart bidding

Even if you have a lot of conversions and your campaign has stable performance over the last few months, switching to smart bidding always involves some risk - what if the algorithms make wrong decisions because of a random unexpected fluctuation that occurs on your market exactly when the algorithm is learning?

If your campaigns are already generating thousands of profit and the only reason you want to switch to smart bidding is to have more free time, you can mitigate the risk by running a Google Ads experiment first: this way, you will only apply the smart bidding strategy to part of your traffic you would be comfortable to not receive conversions from (for example, 30% or 50%). Another portion of your traffic will be still using your initial bidding to ensure you don’t lose the entire revenue if your experiment is not successful. Once you reach statistical significance and the experiment is over, you can compare the results and decide what works best for you before switching your entire campaign to automated bidding.

Since recently, Google Ads discloses the information used for automated learning strategies. In the Bid strategy column of your reports, you can click on the title of your automated strategy which leads you to a report, where you will see if the learning process is over and what signals the strategy has considered as important.

5. Relying on the machine to do all the work

Finally, it’s good to keep in mind that automated strategies were mostly designed to help you out with bidding. Google powerful algorithms help you get as many clicks as possible with high conversion probability (if the right strategy is chosen), however, bidding is only one part of managing PPC campaigns.

Even if you are using automated bidding, all the other activities for improving your performance is still your responsibility: you still need to add negative search terms to prevent spending your money on irrelevant queries, craft compelling messaging in your ads, work on your Quality Score, reallocate budgets from your worst to best campaigns losing impression share etc.

By no means, you should think of automated bidding as of a “set-and-forget” approach to managing your PPC campaigns. The best result is accomplished when you, a human, understand how to leverage the machine computational power to automate the routine tasks while still having a final say in your campaigns with your strategic and creative thinking.

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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