November 5, 2019
5 Things to do Right Now for a Killer Black Friday/Cyber Monday
Since Google Analytics became a standard web and app analytics platform, there has formed a popular misconception that Google Ads conversion data should match the data reported in Google Analytics. As a matter of fact, one of the most frequently asked data questions from business owners and marketers is:
“Why don’t my conversions align between Google Ads and Google Analytics?”
While both platforms are Google products, their tracking and attribution processes differ significantly. This difference is not necessarily a bad thing — here at Metric Theory, we leverage both reporting systems to gain additional insight that helps power our media mix optimizations and reporting attribution.
Below, we will cover the most common differences between Google Ads and Google Analytics conversion tracking and review why you should learn to be comfortable in using both data sets.
Google Ads date of conversion
Conversion reporting in Google Ads and Microsoft Ads is based on day of click instead of day of conversion. If a visitor clicked on your ad one week ago but converted today, that conversion is still reported and attributed to the click from a week ago. This process is called conversion backfill. It happens all the time, as many people usually need more than one day to finalize their purchase or decide to submit their personal information online.
Google Analytics date of conversion
Google Analytics, on the other hand, reports everything based on the actual date and time the action occurred, including conversions. If a visitor clicked on the ad a week ago and converted today, that conversion will have today’s timestamp.
Because of this behavior, Google Analytics reports should align more closely with the actual business data you are seeing on your end for a specific date range. However, it is still impossible to avoid discrepancies due to tracking limitations, ad blockers, different attribution models, and more.
Google Ads: Single-channel conversion attribution
Google Ads conversion tracking captures just Google Ads activity. It completely ignores every other channel that had a touchpoint during the consumer purchase and conversion journey. If Google Ads had at least one click before the conversion, it will show the whole 100% of conversion value in Google Ads, even if the last click was from email or any other channel. This is simply because Google Ads doesn’t have full visibility into other channels.
Google Analytics: Multichannel reporting and attribution
One of the main advantages of using a web analytics platform such as Google Analytics is the ability to gather insights across all your traffic sources and evaluate their performance accordingly. This is especially true for enterprise customers who can afford Google Analytics 360 (premium paid version) and use cross-channel data-driven attribution modeling.
The default attribution model in standard Google Analytics (free version) is Last Non-Direct Click. This model ignores direct-to-site visits and attributes the full conversion to the last channel that drove the user, as long as that user still has a cookie with the information about that last channel. This means that every single traffic source is included in this model and only the last touchpoint gets full credit.
If the information about a specific channel source doesn’t exist (removed cookies, ad blockers, new user), then Google Analytics attributes that conversion to Direct. Below example shows how it attributes the conversion to a specific channel:
Conversion counting: Single or every
Google allows custom configuration of conversion counts in Google Ads. There are two options that you can select:
Google Analytics tracks one unique conversion per session. Repeated sessions can drive additional conversions for the same channel, so if you’re counting just unique conversions in Google Ads, there can be a pretty significant discrepancy in Google Analytics compared to Google Ads.
Google Ads includes cross-device conversions by default in the Conversions column. As this is based both on the actual measurements plus Google’s estimates, it can look completely different from Google Analytics reported numbers that do not include cross-device conversions.
Cookies and user preferences
Both platforms work based on different tracking processes and tagging. Users might have different privacy settings in their browsers or via browser add-ons that block one tracker but leave another active. This can cause pretty significant discrepancies between both platform reports.
Now that you know these main differences, what can you do with them to better understand the impact your media channels are having on overall business performance?
This data can be utilized to better understand seasonal trends and inform your head of finance about specific dates when marketing budgets should be increased to generate more traffic and exposure. Probably one of the best examples is Black Friday and Cyber Monday.
Retailers often struggle to time their budget increases accurately, which leads to major misses on great opportunities to capture those early researches who eventually convert during the holiday season. The data in the chart below indicates that users who came to the site early in November were converting heavily in December. Google Ads conversions in November were on average +15% higher compared to Google Analytics transactions due to the different attribution models. Without looking at conversion data from both platforms, this insight on purchase behavior would have been lost.
Marketers should feel comfortable working with multiple reporting and attribution platforms as long as they understand the fundamental differences between them. Even if Google Analytics is currently considered your final source of truth, analyzing data directly from ad platforms provides invaluable insights into cross-device and impression-based conversions together with overall conversion backfill.
For more guidance on conversion attribution and business strategy, contact our team.