How Long is the Google Ads Learning Phase? (+ Strategies & Insights)

The learning phase is the timeframe when your bid strategy is learning in order to get you optimal results. Ignited when updating an existing campaign or launching a new one, this phase can last anywhere from one week to one month.

Typically, marketers get frustrated when their Google Ads are in the learning phase.

But should that be the case?

We spoke with HawkSEM SEM manager, Abigail Beene, to get the deets. Read on to learn the benefits of and how to speed up your Google Ads learning phase.

(Image: Unsplash)

What is the Google Ads learning phase?

The Google Ads learning phase is a critical period when new and updated campaigns using the automated bidding strategy go through. The learning phase is initiated when advertisers make changes to existing campaigns, or launch new ones, and it only applies to smart bidding strategies.

Have you ever logged into your Google Ads account and seen your campaign or portfolio with a “Learning” status? This indicates your campaign is in the learning phase.

During this phase, the platform’s algorithm adapts to your ad’s performance. It explores the best ways to show your ad to the target audience.

Essentially, it’s the machine learning process that optimizes how your ad is shown.

Understanding this phase of your campaign delivery is critical to managing and improving your ad performance.

Key Influences in Google Ads learning phase:

• Adaptation period: The learning phase is when Google adjusts to the behavior of your ad in real-time auctions.
• Algorithm optimization: It’s an algorithmic process that tailors your ad delivery for better performance.
• Campaign impact: The learning phase directly affects how often and to whom your ad is shown, impacting conversions, costs, and reach.

How long is the learning phase for Google Ads?

The Google Ads learning phase can take just a week, or up to 1 month. The duration of the Google Ads learning phase is flexible. It varies based on several factors and details of your campaign.

Variable time frame

The duration of the learning phase within Google Ads is incredibly dynamic, often influenced by a wide range of elements around the campaign’s structure. The nature of the changes implemented and the platform’s learning algorithm also significantly affect the phase length.

Factors that can influence extended learning phases include:

• Little initial data: New campaigns or those with limited historical data often require an extended learning phase. Since the algorithm relies on data for optimization, it might take longer for it to understand the best approach without a large data set.
• Frequent or numerous changes: Campaigns subject to periodic modifications in the budget, targeting, ad copy, creatives, or bid strategies might need a longer learning phase. Each change resets the learning process, delaying the algorithm’s ability to stabilize.
• Competitive niches: The learning phase may extend in highly competitive industries or densely saturated ad spaces. This is because the system has to compete for visibility and adjust bid strategies to maximize ad performance.

What affects the duration of the learning period?

According to Google, the duration of the learning phase hinges on three primary elements:

1. Conversion quantity

The number of conversions acquired by your campaigns, ad groups, keywords, or products plays a crucial role in the learning phase duration. More conversions typically expedite the learning process.

2. Conversion cycle length

The duration of your conversion cycles, representing the time it takes for a click to culminate in a conversion, significantly impacts the learning phase duration. Shorter cycles often lead to a quicker adaptation.

3. Bid strategy variation

Different bid strategies, such as Maximize Conversions and Maximize Conversion Value, influence the learning phase. Manual CPC does not undergo this learning period.

Understanding the Google Ads learning phase

The Google Ads learning phase will help you understand how your campaigns evolve in the Google Ads platform.

It represents the initial stage where Google’s algorithm assesses and refines the best approach to showcase your ads to your target audience.

Google defines an automated bidding strategy as “a bid strategy that uses Google AI to set bids for your ads based on that ad’s likelihood to result in a click or conversion.”

As part of the automated bidding strategy, the AI needs to learn how to best bid in ad auctions to get the best results for your ads, and that can take a bit of time and testing.

So, how exactly does the process work?

1. Learning phase dynamics

During this phase, the system explores the performance patterns of your ads in live auctions. Based on this data, it looks at user responses, such as clicks or conversions, and refines who your ads are shown to.

2. Algorithmic adaptation

Google’s machine learning algorithm optimizes your ad delivery to enhance performance. It learns which audience, timing, or context works best for your ad. This helps to refine your campaign’s targeting.

3. Impact on ad delivery

The learning phase significantly influences who sees your ads and when. This learning phase period can lead to fluctuations in your performance metrics, impacting your campaign’s initial reach, costs, and efficiency.

4. Real-time adjustments

Throughout this phase, the algorithm makes continuous adjustments based on user behavior. It seeks to improve ad performance. This leads to a more refined, optimized, and effective ad delivery over time.

What triggers the learning phase?

There are several different ways to trigger the learning phase. The first and most obvious is when you first build a campaign. Your campaign starts out in the learning phase before

The other time your campaign can go into “learning phase” is when you make significant changes, similar to what you experience in Facebook ads. These are some of the things Google considers significant changes:

• Updating or changing a bidding strategy: Updating, reactivating, or adding a smart bidding strategy are triggers.

• Changing bid strategy settings: Updating your target CPA, target ROAS, and similar settings will also send you back to learning.

• Changes to your ad structure: Adding or removing keywords, ad groups, and campaigns are a trigger as well.

How do I check the learning phase status of my PPC campaign?

You don’t need an extensive tutorial to determine if your campaigns are in the learning phase; it’s super simple.

You can determine your campaign learning status with bid status indication.

(Image: Google Ads bid status indication)

The bid status clearly shows whether your campaign is in the learning phase. If it shows “Learning,” it implies that Google Ads is in the process of optimizing your bids.

Why is my campaign in the learning phase?

There are a few reasons that your bid status might show as learning.

New strategy

Was your bid strategy recently created or reactivated? If so, the learning status might show while Google Ads adjusts to optimize your bids.

Setting change

Altering your bid strategy settings (such as increasing or decreasing budget) prompts Google Ads to readjust for bid optimization. Hence, the learning phase is triggered.

Composition change

Any additions or removals of campaigns, ad groups, or keywords within the automated bid strategy can prompt the learning phase.

Post-learning phase learning

It’s also good to note that even when the bid status no longer shows “Learning,” Google Ads continues to refine its algorithms.

The platform continuously learns from user behavior and refines ad delivery strategies for ongoing optimization

So, even when your bid status is no longer learning, Google’s algorithm still adjusts and optimizes based on the data it collects.

It’s just that now the data set is more extensive, so the changes won’t be as notable.

Strategies to expedite the learning phase

Now, we know what can trigger a more prolonged learning phase. But is there anything that you can do to speed it up? Luckily, the answer is yes.

Here are some strategies to expedite the Google Ads learning phase.

Minimize frequent changes

Suppose a campaign undergoes multiple budget changes and changes in targeting settings or ad creatives within a short span. Each change resets the learning process, prolonging the phase as the system strives to adapt to these modifications.

The learning process becomes more streamlined by minimizing frequent alterations and allowing the algorithm to accumulate substantial data.

Beene, explains, “There is such a thing as making changes too often using a smart bidding strategy, as the strategy itself needs some time to make adjustments on its own.”

She tells us that making too many changes can have negative impacts, like reducing how often your ads serve, because it throws the bidding strategy back into the learning phase and is a shock to the system.

“Also, regardless of bid strategy, if you make too many changes at once, it’s very difficult to tell what changes actually moved the needle for performance,” she says.

Leverage your historical data

Campaigns with access to extensive historical data offer the algorithm a lot of information to expedite the learning process.

For example, a business that has been running Google Ads campaigns for years possesses a rich dataset.

Leveraging this historical data provides the algorithm with insights into what has previously worked. This will facilitate quicker adjustments and optimizations.

Consistency in your campaign

A campaign that maintains consistency in its elements—such as ad creatives, target audience, and budget allocation—helps the system to accumulate consistent data.

For example, a quality ecommerce campaign with steady and unchanging product lines and audience targeting parameters allows the algorithm to grasp user behavior more swiftly. This shortens the learning phase duration.

Testing phases

If you implement a preliminary testing phase with smaller budgets, it allows you to help with data collection without the need for significant algorithm adjustments.

Let’s say you are about to launch a new product. This might involve a brief test phase with limited budget allocation to gather enough data and optimize the campaign before committing to a substantial budget.

(Image: Unsplash)

Expert strategies to help you navigate the Google Ads learning phase

Effective management of the Google Ads learning phase will help you end up with fully optimized campaigns.

We know it can be frustrating to see your status set to “Learning.” And it can be even more difficult when it’s been that way for a while, and you don’t know when it will change.

These strategies ensure a smoother adaptation of your ads on Google Search.

Exercise patience

Allow automated bid strategies to learn and optimize. Continuous changes disrupt the learning process. Consistency in your campaign settings and accurate conversion tracking allows for gradual adaptation and better performance.

It can be frustrating to hear, but sometimes, the best option is to take a deep breath and wait it out. But in the end, you get a fully optimized campaign that will use all of the algorithm’s immense knowledge to help get you a better return on ad spend (ROAS).

Gradual optimization changes

Make alterations incrementally. Sudden and frequent changes disrupt the learning phase. Implement adjustments slowly, ensuring the system can adapt without resetting the learning process.

Deliberate, gradual alterations ensure that the system assimilates changes seamlessly. Avoid sudden overhauls or frequent modifications so that the learning phase remains uninterrupted. This allows the algorithm to adjust organically and gain insights from the campaign’s performance without resetting its learning progress.

“Deciding how long to wait before making changes after implementing a smart bidding strategy depends on the daily budget of that particular campaign and how quickly data comes in,” Beene tells us.

“However, you do want to make sure adequate time has passed, and enough data has accumulated to start making adjustments.”

She encourages advertisers to check the bid strategy learning status to ensure they’re not jumping the gun on changes.

Harness your data

The emphasis on data accumulation isn’t merely a suggestion but a fundamental strategy. The richness and depth of data directly correlate with the speed and efficacy of optimization.

The more comprehensive the data, the faster and more accurately the system can adapt and fine-tune campaigns.

You can use historical data as suggested above. But you should also look into your conversion data and tracking.

A robust conversion tracking method is worth its weight in gold regarding PPC.

It’s not just about looking at conversion rates. It’s about developing a deep understanding of user behavior. Accurate and detailed conversion tracking can help you feed AI with data to help better implement strategies that align with your goals.

Beene tells us that using a bid strategy on a brand new campaign with no data is also a mistake. “My typical recommendation is to start with a manual bidding strategy, and once adequate data has been collected (around 15-30 conversions in the past 30 days), you can start moving campaigns over to a smart strategy,” she says.

CPA-focused optimization

Strategically align your optimization with cost-per-acquisition (CPA) goals.

You can guide the system towards more effective performance while adapting to the learning phase by fine-tuning bidding and ad content to optimize for CPA.

This approach ensures that your ad spends are directed towards acquiring customers at your set cost target.

Landing page relevance

Before you run a new ad with an automated bidding strategy, you want to consider the landing page deeply.

Landing page relevance enhances user experience and aids in the learning phase.

Align landing pages with ad content and relevant search terms. This will ensure a cohesive user journey and improve ad quality and user engagement, which the algorithm recognizes and adapts to.

The takeaway

When it comes to the learning phase on Google Ads, the importance of gradual optimizations can’t be overstated.

The learning phase is helpful to help get the most out of the algorithm. But you don’t want to reset every time you change your campaign. To avoid this, make small changes over time and leverage all the data you have.

Navigating this phase with strategic finesse not only optimizes ad delivery but also ensures campaigns are aligned with evolving market dynamics. This sets the stage for sustained success and improved performance in your ads.

Need help getting it right? Call in the Hawksand we’ll have your campaigns up and running in no time.