Marketers are using more ways than ever to reach their audience and drive conversions online.
Today, it goes without saying that customers will undoubtedly visit a site more than once and likely click more than one ad before they complete a purchase. So how do we ensure we’re assigning the right value to each of our individual marketing channels? Enter Google Attribution.
Google Attribution aims to solve three problems for marketers:
In this guide we’ll walk you through the following key tips and tricks to perfecting your attribution strategy:
It is safe to say that the majority of advertisers are most familiar with the “Last Click” model in Google Ads. Using “Last Click” gives all the credit to the last clicked ad and corresponding keyword prior to a conversion.
Whilst this is the easiest model to apply, it ignores all of the other possible interactions a customer may have had with ads – and their contribution to the conversion.
Where “Last Click” credits the very last click, “First Click” attribution gives all the credit to the first clicked and corresponding keyword.
In this model, all ad interactions that lead to the conversion are given the same amount of credit.
Time decay is a weighted attribution model, meaning clicks that happened closer to the conversion are given more value than clicks that happened further away from the conversion.
Google Ads has a 7-day half-life built into this model. If a click happens 8 days before a conversion, it is given half the credit a click would receive if it happened the day before a conversion.
This perspective is particularly useful if your business has a longer conversion cycle.
Position-based attribution gives the first and last clicked ads 40% credit, and any clicks that happened in between 20% credit.
One thing to consider when using this model is that you will begin to see partial credit given to campaigns and keywords. For example, in the screenshot below, the total conversion volume for one non-brand campaign shows 170.43.
Data-driven attribution (DDA) models use past account performance to automatically calculate the distribution of credit for a conversion.
Your account must have enough data accumulated before DDA is available as an option. In that case, you might see a message stating “You currently don’t have enough conversion data to use “Data-driven.”
Using the time decay, position-based and data-driven attribution models will identify if certain keywords, ad groups, or campaigns are contributing to overall revenue even if they’re not bringing in direct conversions.
Understanding your customers’ buying journey is a complex task but identifying how long your customers take to convert will help you verify that you are measuring your conversions properly.
Inside Google Ads, under Tools > Measurement > Attribution > Model Comparison, you can select different attribution models to compare against your existing model. It’s important to note that this doesn’t actually change any of your data, it simply gives you different ways of viewing it.
In the above screenshot, you can see that the DDA model is available and applying it would increase the conversion volume for the campaigns “Search – Brand” and “Shopping Desktop”. The “Shopping Mobile” campaign, however, would lose 21% of its current conversion volume suggesting that customers may be starting their journey elsewhere before converting on their mobile device.
You can also view this report in Google Analytics and expand the model comparison to include all channels.
In this section, we’ll cover two attribution reports in Google Analytics. These reports can be found within the Analytics Conversions menu under Multi-Channel Funnels. Both of these reports are also available in Google Ads, but the Analytics version let’s you understand the bigger picture across all channels.
Reviewing the top conversion paths is a great way to determine the steps customers take to make a decision. In the top paths in the image below, you can see that the path isn’t always a clear one. Over 7k visitors reached the site via paid search and then came back through organic search before converting. 287 users came in via paid search, came back through organic search, and then visited the website three times before converting.
In the account below, we can see more often than not the customers visit the site multiple times before converting. In fact, approximately 76% of the customers placing transactions visited the website more than one time.
One thing to keep in mind is that the reports under the Multi-Channel Funnel (MCF) menu in Analytics credit direct traffic differently compared to other reports in Analytics. In the above example, we can see that direct has been given full credit for several different sessions. In non-MCF reports, the direct visit is dropped and credit is given to the channel preceding that visit.
The Google Ads’s variation of this report shows you the top paths between only your Google Ads campaigns. This is useful if you don’t have Analytics and you’re only interested in seeing paths within Google Ads. This report can also break down paths by ad groups and keywords. This report is found in: Tools & Settings > Measurement > Attribution > Top paths.
How long does it take your customers to complete a purchase or submit a lead? Understanding your customers’ behavior can help you determine which attribution model you should be using for your paid advertising.
In the screenshot below, we can see for this advertiser that only 55.6% of revenue and 68.8% of conversions are attributed to the initial click on day one. The rest is dispersed, with 17.3% of revenue falling into the 12+ days category. This is typical for more expensive purchases.
Time lag data can help you determine if your conversion window is set correctly in Google Ads. In the above example, the credit for most of these conversions would give no credit to the first interaction without this attribution data.
In contrast, in the image above you can see that the customer journey of this lead generation company is much shorter. 99.2% of customers convert immediately and there is very little time lag. If you are tracking more than one type of conversion action, like phone calls and transactions, you might review each conversion action independently because they can vary. It may take customers less time to pick up the phone to ask a question than moving forward to submitting a lead or making a purchase.
The variation of this report in Google Ads shows you the time lag for your Google Ads campaigns. This report is found in: Tools & Settings > Measurement > Attribution > Path metrics.
Attribution allows us to assign value to any campaign and its contribution to the buyer journey.
The typical buyer journey looks different in each industry, but more often than not, the path to purchase has more than one stop and will be influenced by more than one ad.
Social advertising plays a huge part in modern marketing but as these ads are not always the direct driver of sales, and don’t sit within the Google ecosystem, they’re at risk of going uncredited.
Let’s consider we’ve defined our path to purchase, using a combination of internal resources and overlapping the Google buyer-journey. The result is a seven step sequence of micro-moment touch points:
Once we have this journey outlined, how do we ensure it’s reflected in our reporting, in particular, for Social channels like Facebook and Instagram?
Assuming you’ve already educated your team on the value of channels which are indirectly driving sales. First, you should be using platform-specific reporting to show each campaign type’s contribution towards a conversion – it’s about setting the right micro-conversion as the goal. This can be in the form of a lead sign up, share, link clicks, etc.
Then use Analytics to assess both direct and indirect sales attribution from Paid Social using two multi-channel funnels report types:
Once you’re happy with the attribution model you’ve created for your Marketing activity, you should be using the insights to further optimize your channel mix and budget splits.
Google Ads’ Data Driven Attribution Model has been available since May 2016. If you’ve always relied on last click then switching to DDA may feel a little scary but it’s time to move on. The path to purchase is no longer a straight line (if it ever was) and we shouldn’t ignore the valuable insights machine learning is now putting right at our fingertips.
As we continue to mull over the future of PPC we know these three current truths:
Even with the possibility of having perfect cross-channel attribution through Google platforms, there are still other things to consider. If you’re using a CRM, how do we mash that data together with our marketing data? And if a conversion happens and we don’t see the touchpoint, did it really happen?
Even more sophisticated, how do we take into account the lifetime value of our customer?
My point is we can take this step forward with attribution in Google Ads, marry it with multi-channel funnel data in Analytics, and start to fuel our marketing strategy with ideas more sophisticated than “let’s bid up on keywords that have low CPA”!