Google’s shift to automated ad management continues. Many of my articles explain how advertisers can use this automation while maintaining a level of control. However, what advertisers often overlook is conversion tracking.
Google knows how to show an ad to a searcher who types in the targeted keywords. But Google can only optimize performance if the advertiser has conversion tracking enabled.
Most advertisers did. But most didn’t set it up correctly. Here are four steps to improve Google Ads automation (and machine learning) through conversion tracking.
4 Steps to Improve Google Ads Automation
Configure enhanced conversions. I covered improved conversions last month. It is worth a deeper dive.
Enhanced Conversions tracks performance even when cookies are restricted (an essential feature for cookieless browsers) by matching hashed customer data from an advertiser’s site with that of Google.
A recent Google case study reported that UK retailer ASOS saw an 8.6% increase in sales from search ads after implementing Enhanced Conversions.
Google suggests the “maximize conversion value” bidding strategy for advertisers with at least 50 conversions in 30 days. An advertiser with 40 conversions in 30 days could reach 50 by implementing Enhanced Conversions.
Advertisers set up enhanced conversions through a global site tag or Google Tag Manager. Enhanced conversions only apply when Google Ads is the conversion source, not Google Analytics or offline conversions. To trigger a conversion, consumers must submit data such as an email address on the designated page. Pageviews do not apply.
Choose the right attribution model. Last-click attribution is a common mistake. The model attributes all conversions to the last clicked keyword and ad. This overstates branded campaigns in search because branded keywords tend to be the last click in the buying cycle.
For example, a consumer can click on an ad for a non-branded keyword like “basketball shoes” and go to Nike’s website to do a search. A week later, she can type “nike basketball shoes,” click on the brand ad, and make a purchase. The branded keyword gets all the credit even though the term unbranded plays an important role. Therefore, critical keywords that helped in the conversion process are undervalued.
Google offers six attribution models for conversions:
- Last click,
- First click. The first click that leads to a conversion gets all the credit.
- Linear. All clicks receive equal credit for the conversion.
- Decrease of time. Clicks that occur closer to conversion receive more credit.
- Based on position. Forty percent of the credit goes to each of the first and last clicks, while the remaining clicks share 20%.
- Data driven. Credit is distributed based on past conversions.
Data-driven attribution is ideal because it grants the most accuracy to each click. But to work effectively, it needs at least 300 conversions and 3,000 ad interactions, e.g. clicks, video ad views, calls for call extensions. This template gives proper credit to all keywords and ads.
In the absence of sufficient data, I prefer position-based attribution, as clicks other than last clicks combine to receive 60% of the credit.
Use conversion values. Assign a value (static or dynamic) to all conversion types. By dynamically updating the pixel, you can track revenue from each purchase. You can also assign a static value to non-monetary conversions, such as signing up for a newsletter. Adding value is a requirement of the Maximize Conversion Value bid strategy.
Use campaign-specific objectives. Once you’ve set up Enhanced Conversions, tell Google which bid strategies each campaign should be optimized for. Settings > Goals. The choices are “account” or “campaign specific”. By default, Google optimizes by account, which means your ads will show to anyone who is likely to convert for any objective.
Campaign-specific goals will be optimized for one or more specific conversions, such as purchases, newsletter signups, or form submissions.