Using Paid Search Attribution to Maximize Insights, Performance and Marketing ROI

Accurate attribution is likely more important for search advertising than any other marketing initiative. PPC managers target hundreds or thousands of keywords to reach their audience on search engines. Paid search attribution helps them understand the role each keyword plays in driving key performance indicators (KPIs).

Other marketing initiatives simply don’t have the same volume of attributable data points to work with. As a result, even slight changes in your paid search attribution strategy can have a huge impact on the return on investment (ROI). Industry research and the personal experiences of PPC practitioners are more than enough to prove this. Here’s an overview of the different tools and models marketers can use to maximize insights, performance, and marketing ROI from paid search attribution.

Google Ads Attribution Models

Google Ads offers several different attribution models as features advertisers can implement for conversion tracking and bidding insights. Right now, attribution modeling is available for Search Network and Shopping ads, but not Display ads. It can be used for website, Google Analytics, phone call, and import conversion actions (but not for app and in-store conversions).

Google Ads attribution models include:

Last Click – All credit for the conversion goes to the last-clicked ad and corresponding keyword.

First Click – All credit for the conversion goes to the first-clicked ad and corresponding keyword.

Linear – Distributes the credit for the conversion equally across all clicks on the path.

Time Decay – Gives more credit to the clicks that happen closer in time to the conversion.

Position-based – 40% credit to the first and last-clicked ads; 20% spread across other clicks.

Data-driven Attribution – Assigns credit for the conversion based on past data for the conversion action.

You might like to think that any attribution model you use is “data-driven.” But data-driven attribution is actually the name Google gives to a special model reserved for accounts with sufficient data. This model calculates the contribution of each keyword across your conversion path based on previous data, then distributes credit for the conversion action.

If your account has enough data, then the data-driven model is definitely the best choice for paid search attribution. It’s more likely than any other model to reflect the real value of different touch points in your funnel. It considers all clicks from your account (both converting and non-converting) in order to assign value to an ad or keyword.

When using Google Ads to build a paid search attribution strategy, it’s important to compare the different modeling options to determine which one is best for you. Google allows you to easily do this from your AdWords account:

1. Click the “Tools” button from the top menu
2. From the drop-down menu, click Measurement, then Search attribution

Paid Search Attribution Figure 1


3. On the side menu of the next page, click Attribution Modeling
4. From the dropdown menu, select the dimension you want to view attribution models for

Paid Search Attribution Figure 2


5. Then use the other dropdown menus to select which attribution models you want to see and compare

Paid Search Attribution Figure 3


Google Ads attribution models are a great free resource you can use to build your paid search strategy, but it has some limitations compared to more advanced tools out there.

Paid Search Attribution with Search Ads 360

Search Ads 360 is a paid alternative to Google Ads. It has a lot of features that empower improved paid search performance and track your overall marketing efforts. Their advanced attribution models are just one of many reasons you might consider investing in it.

By default, Search Ads 360 uses a last click attribution model. You can, alternatively, import a different attribution model from Campaign Manager or Google Analytics. Search Ads 360 also offers data-driven attribution modeling that can include several different interactions. This is valuable since a great many conversions are driven by a series of clicks on display ads, paid search, shopping campaigns, generic or brand keywords, and other biddable items.

Data-driven attribution can help identify frequent conversion paths within a campaign, then compare these paths with other interaction patterns to accurately assign credit. You can also compare the difference between a model built on data-driven attribution calculations and the traditional last click model

Unlike Google Ads, Search Ads 360 can analyze clicks from a variety of channels, including:

  • Paid search
  • Paid social
  • Google Display Network
  • Display ads
  • Organic search

This data integration is able to paint a more accurate picture of the path to purchase so you can successfully attribute credit to different touch points across paid search and other advertising initiatives.

Google Analytics 360 Integration

If your priority is building a cross-channel attribution model, then Google Analytics 360 is a powerful option for PPC attribution. It’s designed to work together with Search Ads 360 to help you track, optimize, and automate your marketing efforts across varying channels.

Key features of Google Analytics 360 include:

  • Native onboarding integrations with Google Ads, Display & Video 360, Search Ads 360, and more
  • Native remarketing integrations with Google Ads and Display & Video 360
  • Advanced, customizable funnel reporting
  • Advanced attribution modeling (including data-driven model)

You can use performance data from Analytics 360 to drive search campaigns, bid strategies, and rules in Search Ads 360. Analytics 360 gives you a full picture of marketing performance, while Search Ads 360 can help you act on these insights through automated bidding.

Third Party Attribution Tools

Investing in third party attribution technology is a good idea for businesses looking to get more accurate and nuanced results from their attribution strategy. There’s no denying that using a tool like Google Ads for cross-channel attribution could have an inherent bias issue. Marketers who have explored third party attribution tools and compared their results to Google Ads often find Google Analytics shows a larger number of conversions from Google channels than the third party tool.

Third party attribution technologies should (in theory) eliminate this bias and offer more opportunities to customize your attribution model. Some examples of notable third party attribution tools include:

  • VisualIQ
  • Flashtalking
  • Full Circle Insights
  • Facebook Attribution
  • TrackMaven
  • BrightFunnel
  • Convertro
  • And more

Facebook Attribution is a relatively new option and not one that most paid search advertisers consider. It is, though, a compelling option because it integrates with a lot of other tools, including Google Ads, Campaign Manager, and Search Ads 360. It further assigns credit where it’s due for conversions across marketing channels:

Paid Search Attribution Figure 4


VisualIQ is another alternative that offers multi-touch attribution across channels, collecting audience and attribute data to created customized attribution models. Professionals use it to learn which publishers, campaigns, placements, keywords and other tactics drive their KPIs.

Marketers wishing to build a strong paid search attribution strategy should consider the features of third-party tools based on their unique needs. Make sure they have the right integrations as well as sophisticated reporting needed to make bidding decisions. Understanding the role PPC plays in driving conversions only matters if you can also see which dimensions are driving performance (campaigns, ad groups, keywords, etc.).

The Power of PPC Attribution with Automated Bidding

Marketers today dedicate a great deal of time and energy to finding the most accurate PPC attribution model to understand the value of different touchpoints for driving conversions. Attribution is supposed to provide performance insights you can use to further optimize your marketing efforts. In paid search, that means adjusting investment in different keywords, ads, and ad groups based on their conversion value.

So, while it’s important to choose the perfect attribution model, it’s equally imperative to ensure that you use it quickly and efficiently to optimize your campaigns. Google Ads offers a solution for this, helping advertisers automate bidding decisions based on paid search attribution performance. But their solution comes with some inherent limitations that only advanced bid optimization technology can help with.

Unifying Data Sources

The customer journey is complex but largely trackable, thanks to the growth of MarTech. Today, there is an overwhelming amount of relevant data about audience behavior and the factors that impact their purchase decisions. Most marketers are in no position to harness it all to drive performance-enhancing insights. And the popular attribution tools Google offers only paint a partial picture, focusing heavily on data from Google properties.

The solution is a platform flexible enough to capture all relevant brand interactions. Advanced bidding technology does this, factoring in important data types such as:

  • Cost data from publishers
  • Historical revenue and click information
  • Campaign, keyword type, and match type
  • Revenue data (Deep revenue, offline, LTV, in-house metrics, and more)

The more data your attribution technology uses to understand the path to purchase, the more accurately it can attribute conversion value to different marketing assets.

Taking the Guesswork Out of Bidding

Third-party paid search attribution technologies have more data integration options than Google Ads or Google Analytics. They can help you build a more accurate attribution strategy, but lack the features to implement changes to your PPC campaigns based on these insights.

Automated bidding technology uses historical performance data, statistical modeling and artificial intelligence (AI) to accurately estimated the value of each keyword in your campaigns. It’s then able to make necessary changes to your max cost-per-click (CPC) and bid adjustments. By using all relevant performance data and adjusting bids in real time, automated bidding technology can improve campaign efficiency and performance, freeing up marketing managers to explore new growth initiatives.

More Precise Attribution

Top-of-the-line bid automation tools have features that ensure more precise attribution than what basic models and technologies can provide. For example, QuanticMind uses multiple data sources to map location with higher precision (zip codes, cities, metro areas, etc.). This allows the tool to better attribute cost and revenue data to the correct location, improving the efficacy of automated location bid adjustments.

QuanticMind also uses decimal conversion values, attributing a single conversion to multiple clicks throughout the customer journey. This better illustrates the real impact of each keyword on the path to conversion. The algorithm can then use this more accurate data to calculate click value and bid more accurately.

The Bottom Line

Accurate paid search attribution is key for success in today’s competitive PCC world. There are a variety of free and paid tools with different modeling capabilities to choose from. No matter if you’re investing time, money or both in PPC attribution, you must ensure it brings positive ROI for your marketing efforts in the long run.

Advanced automated bidding technology is one solution that offers nuanced insights into what biddable factors drive conversions, and allows you to make changes to your campaigns efficiently and at scale.

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