October 16, 2019
Explaining the Conversion Discrepancies Between Google Ads & Google Analytics
Like any piece of your digital marketing strategy, Remarketing shouldn’t be viewed as a set-it-and-forget-it initiative. Developing and implementing informed tests is an important part of improving overall performance.
Just as we rely on data to conclude tests, advertisers should be using data to develop new tests. Today, we’ll look at three reports in Google Analytics to identify testing opportunities in remarketing.
The All Pages report under Behavior > Site Content > All Pages shows how users have interacted with each page on your website by showing metrics such as pageviews, average time on page, and bounce rate. This report can be incredibly valuable for uncovering what content is driving user engagement as well as conversions.
For advertisers tracking eCommerce Revenue in GA, the Page Value metric within the All Pages report is especially helpful in gauging valuable site content. Page Value is intended to show which pages on your site contribute most to your site’s revenue. It is calculated as the revenue from users who visited a given page divided by the total number of unique pageviews for that same page. A high Page Value is an indicator that something on that page is contributing to a user’s ultimate decision to convert. By identifying these winning pages, we can develop informed tests to be used in our Remarketing messaging.
For example, let’s say we have a page on our site called ‘Compare Us’, which shows a matrix comparing how our software outperforms industry competitors. If this page has a high page value relative to average, this indicates that information on this page may be influential in driving purchase decisions. We can then test this hypothesis in our remarketing efforts by running a similar competitor comparison within our creative or the remarketing landing page itself.
The Behavior Flow report visualizes the path users take from page to page on your website. By filtering this report to include only users from your Remarketing campaign(s), you can see a detailed view of how remarketing users are behaving once they land on your site.
Reviewing this report can help identify gaps between the desired and actual behavior of remarketing visitors once on site. Let’s take, for example, a remarketing campaign aimed at driving free trial signups. The desired behavior that we’d like to see for site visitors from this campaign is to click the “Get a Free Trial” button on the landing page. If, however, the top behavior path shows users navigating to the “Case Studies” section of the website, that shows a gap between desired and actual behavior. Users from this remarketing campaign aren’t ready for a free trial. They need some more information, especially around other companies who’ve benefited from the product being offered.
There’s many ways this advertiser can incorporate these insights into an informed remarketing test. They can test introducing additional information onto the current landing page, such as logos of well-known brands using their product or callouts around past success stories. They can test changing the call-to-action altogether, offering a gated case study rather than a free trial. The findings from the Behavior Flow report can even be used to recommend a test regarding the format of the landing page. Perhaps the advertiser reviews the page and finds that the “Get a Free Trial” button is too far down the page; in this case, the proposed test can be to move the button up above-the-fold.
The Time Lag report in Google Analytics (found under Conversions > Multi-Channel Funnels > Time Lag) shows conversions and revenue based on the number of days between when a user first interacted with the site and when they converted. This allows you to see the impact that both short and long purchase paths are having on your business.
The Time Lag report shows paths up to 90 days, providing a great way to gauge opportunity around introducing longer remarketing audiences into your strategy. Let’s take the data set below as an example:
Say this advertiser is looking to scale their current remarketing efforts and is currently targeting up to a 7 Day Remarketing audience. From the data above, we see that 31% of their conversions have a time lag >7. Based on this, we can clearly see the value in introducing longer time lag remarketing audiences as part of their growth strategy.
If, however, that same advertiser was already targeting up to a 30 day audience, that recommendation would change. Only 1 out of 7,500+ conversions took longer than 30 days, so we wouldn’t anticipate much impact from expanding our remarketing audiences beyond 30 days.
The Time Lag report can also be used to identify AOV trends based on time-to-purchase. Download the report into Excel and add in a column with the formula for AOV (revenue divided by conversions). If any clear AOV trends emerge, this presents an opportunity to test new remarketing audiences.
For example, let’s consider an eCommerce advertiser selling shirts and shoes. Their shirts retail for $10-$15, and their shoes for $60. This advertiser pulled the Time Lag report, and is seeing the trend below:
AOV is substantially higher for users with a longer time lag to purchase, specifically starting at 8 days. This indicates that users who take longer to convert are typically purchasing shoes, whereas the short purchase paths are typically for shirts. We could tie this learning to the remarketing strategy by adding additional segmentation to our remarketing audience structure.
Let’s assume that one audience used within the current remarketing structure is “all visitors (last 8-30 days).” Based on the Time Lag report, it’s fair to assume that visitors who browsed shoes 8-30 days ago are likely to perform differently than visitors who browsed shirts within that same period. However, both sets of users are being targeted at the same bid under the current remarketing structure. By segmenting out separate audiences for 8-30 day site visitors who did and did not browse shoes, this advertiser would now be able to set unique bids based on the intersection of a user’s recency and behavior.
In today’s digital age, consumers have more opportunities than ever to discover, research, and compare brands. A strong remarketing strategy is crucial in order to maintain consumer attention and turn prospects into buyers. By continuing to test, evaluate, and optimize remarketing initiatives, you can stay top of mind and drive more conversions.
If you’re looking for more creative remarketing initiatives, our team is here to help.