Ultimate Guide to Conversion Attribution in Google Ads

Do you need help measuring your marketing campaign’s success due to the user journey’s complexity? With numerous touchpoints along the way, it can be challenging to determine which aspects of your campaigns are driving results. Fortunately, conversion attribution can help. By assigning credit to each touchpoint, you can gain valuable insights into what’s working and what’s not, allowing you to optimize your campaigns and improve your ROI. In this guide, I’ll cover everything you need about conversion attribution, including defining it, choosing the suitable attribution model, analyzing conversion data, and implementing advanced strategies and best practices. While Google Ads has recently removed four attribution models, the principles of attribution modeling apply to all marketing channels. Whether you’re a seasoned advertiser or just starting, this guide will equip you with the knowledge and tools to track, analyze, and optimize your marketing campaigns for better ROI. So, let’s dive in and learn about conversion attribution!

Understanding Conversion Attribution in Google Ads

Conversion attribution is a process that involves assigning credit to each touchpoint in a user’s journey toward conversion. It allows you to understand the impact of each marketing channel or ad on the overall success of your campaigns. In the past, Google Ads offered several attribution models, including last-click, first-click, linear, and time-decay. However, as of April 6th, 2023, Google has removed four attribution models for advertisers, including position-based, data-driven, and custom attribution models.

Despite these changes, attribution models are still available, each with strengths and weaknesses. The most commonly used models now include the following:

• Last-click Attribution: This model assigns all the credit for a conversion to the last ad the user clicked before converting. While it’s a simple and easy-to-use model, it doesn’t consider the other touchpoints contributing to the conversion. 
• First-click Attribution: This model assigns all the credit to the first ad that the user clicks on. This model is helpful for understanding which ads are driving initial interest in your products or services. 
• Linear Attribution: This model assigns equal credit to all touchpoints in the user journey. It provides a more balanced view of the impact of each ad or marketing channel. 
• Time-decay Attribution: This model assigns more credit to touchpoints closer to the conversion. It helps understand the impact of ads that helped to nudge the user towards conversion.
• Position-based Attribution: This model assigns a percentage of the credit to the first and last touchpoints, with the remaining percentage divided among the middle touchpoints. It provides a balanced view of the importance of initial and final interactions in the user journey.
• Data-driven Attribution: This model uses advanced algorithms and machine learning techniques to analyze data and determine the credit for each touchpoint based on its actual contribution to the conversion. It considers various factors, such as the type of touchpoint, its position in the user journey, and its historical performance. Data-driven attribution provides a more accurate and data-backed approach to understanding the impact of different touchpoints in driving conversions.

Choosing the Right Attribution Model for Your Campaigns

Choosing the suitable attribution model for your Google Ads campaigns is essential to understanding the impact of each marketing channel or ad on the success of your campaigns. While Google has removed four attribution models, several models still exist, including last-click, first-click, linear, and time-decay attribution models. Each model has its strengths and weaknesses, and the best model for your business will depend on your specific goals and marketing strategies.

It’s essential to consider the pros and cons of each attribution model before selecting one. For example, last-click Attribution is simple and easy to use but may provide a partial picture of the impact of all touchpoints. In contrast, a model like time-decay Attribution can provide a more accurate view of the user journey but may be more complex to implement.

When choosing the suitable attribution model, you should consider your business goals. For instance, a first-click attribution model may be suitable if your goal is to drive initial interest in your products or services. On the other hand, if you want to understand the impact of your ads across the entire user journey, a linear attribution model may be more appropriate.

Additionally, it’s crucial to understand how the attribution model you choose can impact your bidding strategies. For example, a last-click attribution model may result in bids being placed only on keywords that drive immediate conversions. In contrast, a time-decay attribution model may result in bids being placed on keywords that drive initial interest and those that nudge users toward conversion.

Case Studies: Real-World Examples of Conversion Attribution in Action

To better understand how conversion attribution works, let’s look at real-world examples of businesses using different attribution models and the results they achieved through optimized conversion tracking and Attribution.

1. Examples of last-click Attribution: An emergency service with a short sales cycle used a last-click attribution model to allocate its marketing budget to keywords that drove immediate conversions. This led to a high ROI on their ad spend but resulted in missed opportunities to target keywords that drove initial interest in their products. Last-click attribution is great for shorter sales cycle campaigns.
2. Examples of first-click Attribution: A new product or service launch used a first-click attribution model to understand which channels and touchpoints drove initial interest and awareness in their products. Their display ads drove significant initial clicks and data, which helped define potential target audiences and inform their bidding strategy and more conversions. First-click attribution is great for awareness, top of funnel campaigns.
3. Examples of linear Attribution: A travel company used a linear attribution model to gain insights into the impact of their ads across the entire user journey. Their ads drove initial interest, but their retargeting campaigns drove most conversions. This led them to invest more in retargeting campaigns to optimize their ROI. Linear attribution is great for longer sales cycles.
4. Examples of position-based Attribution: A B2B software company used a position-based attribution model to give more credit to touchpoints at the beginning and end of the user journey. They found that their initial ads and their email campaigns were driving the most conversions, which helped them optimize their budget and drive more ROI. Position-based attribution is great for more complex offerings.
5. Examples of time-decay Attribution: A seasonal deals campaign is launched. We learned which keywords are driving conversion closer to the end date. This led to increased ROI and a better understanding of which search terms are more sensitive to use in future campaigns. Time-decay is a suitable attribution for time-sensitive campaigns.
6. Examples of data-driven Attribution: An online retailer used a data-driven attribution model to gain insights into the impact of all touchpoints in the user journey. They found that their ads were driving initial interest, but their email campaigns and social media retargeting were most effective at driving conversions. This led them to optimize their budget and focus more on these channels for better results. Data-driven attribution is great if you are unsure which attribution model to choose.

Best Practices for Conversion Attribution in Google Ads

1. Define clear goals and KPIs: Begin by establishing clear goals and key performance indicators (KPIs) aligned with your business objectives. This will help you choose the suitable attribution model and optimize your campaigns for better results.
2. Choose the most suitable attribution model: There is no one-size-fits-all attribution model. Each model has its pros and cons, and the suitable model for your business depends on your goals and the complexity of your customer journey. Experiment with different models to find the best fit for your business.
3. Implement conversion tracking: To accurately measure the impact of your campaigns, you need to implement conversion tracking. This will help you identify the touchpoints driving conversions and optimize your campaigns accordingly.
4. Analyze data and adjust your strategy: Conversion attribution is an ongoing process that requires continuous data analysis. Use your attribution data to gain insights into what’s working and what’s not, and adjust your strategy accordingly.
5. Make data-driven decisions: Don’t rely on guesswork or assumptions regarding Attribution. Use data to inform your decisions and optimize your campaigns for better results.
6. Avoid common mistakes: Some common mistakes in conversion attribution include focusing too much on last-click Attribution, not considering cross-device behavior, and not configuring conversion tracking correctly. Be aware of these pitfalls and adjust your strategy accordingly.

Analyzing Conversion Data in Google Ads

Analyzing Conversion Data in Google Ads is critical to understanding how your campaigns perform and making informed decisions to optimize your ROI. Google Ads offers a range of data on conversions, such as conversion rate, cost per conversion, and conversion value. Understanding this data is essential to make data-driven decisions that can help improve your campaign’s effectiveness.

Here are some best practices for analyzing your conversion data in Google Ads:

1. Analyze your conversion data over time to identify patterns and trends in customer behavior. By understanding these trends, you can adjust your campaigns to target your audience better and improve your ROI. For instance, you can tweak your bidding strategy, target specific audiences, or refine your ad copy and creative based on your conversion data.
2. Use Google Ads Attribution reports to gain valuable insights into your conversion data. You can access these reports by signing in to your Google Ads account and clicking the tools icon in the upper right corner. Then, select Attribution under the Measurement tab. The reports can be customized using different report controls. You can choose the date range to determine which conversions to include, select which conversion actions to include, and adjust the lookback window to 30, 60, or 90 days.
3. The Overview report provides a high-level view of your conversion paths and helps you identify which campaigns are most effective in assisting conversions. The Conversion paths report shows the most common paths customers take to complete a conversion based on the ads they clicked before a conversion. The Path metrics report shows how long and how many interactions users take to convert, while the Avg. days/hours to conversion view gives insight into the length of your online sales cycle.

Conclusion 

Conversion attribution is a powerful tool that can help you optimize your Google Ads campaigns and improve your ROI. By analyzing your conversion data, understanding attribution models, and taking advantage of cross-device and offline conversions, you can gain valuable insights into customer behavior and make data-driven decisions to drive success for your business.

Remember, the world of digital advertising is constantly evolving, and it’s essential to stay up-to-date with the latest trends and best practices. But with a solid understanding of conversion attribution, you’ll be well on your way to success.

So go ahead and experiment with different attribution models, track your conversion data, and make data-driven decisions. Your wallet will thank you!

Frequently Asked Questions

Q: Which attribution model should I use? 

A: The best attribution model for your business depends on your specific goals and needs. Factors such as your sales cycle, customer journey, and channels should be considered. Standard attribution models include the last click, first click, linear, and data-driven.

Q: What are the different attribution models available? 

A: The attribution models in Google Ads include last click, first click, linear, position-based, time decay, and data-driven.

Q: What is the lookback window in Attribution? 

A: The lookback window is the time between a customer’s ad interaction and conversion. In Google Ads, you can adjust the lookback window for each attribution model to determine how far back you want to track conversions.

Q: What is DDA delay? 

A: DDA delay is when Google’s Data-Driven Attribution model waits before assigning credit to a touchpoint. This delay allows for a more accurate Attribution of conversion credit to the most influential touchpoints.

Q: When should I not use DDA? 

A: DDA requires significant data to be effective, so it may not work well for businesses with low conversion volumes or limited historical data.

Q: Can I use multiple attribution models in one Google Ads account? 

A: Yes, you can use multiple attribution models in one account. Depending on your goals and needs, you can assign different attribution models to different conversion actions or campaigns.

Q: What are the pros and cons of the Data-Driven Attribution model? 

A: The benefits of the Data-Driven Attribution model include more accurate Attribution of conversion credit to the most influential touchpoints and the ability to identify new optimization opportunities. However, it requires a large volume of data to be effective and may not work well for businesses with low conversion volumes or limited historical data.

Q: What is DDA according to Google support? 

A: Google support defines Data-Driven Attribution as a model that uses machine learning to determine the most influential touchpoints in a customer’s journey based on conversion data.

Q: What are the consequences of changing attribution models? 

A: Changing attribution models can affect how credit is assigned to touchpoints and may impact campaign optimization. It’s essential to consider the potential consequences carefully and thoroughly test any changes before making them.