Adobe Advertising Cloud Search Support for Google’s Exact Match Change

Adobe is continuing to build upon the Advertising Cloud Search technology — with features powered by Adobe Sensei, Adobe’s framework for artificial intelligence and machine learning.

Google recently announced another change that makes exact match a little less exact. Before 2014, the exact match keyword was as it sounds. A search query would trigger an ad for a keyword on exact match only if it matched exactly – no extra letters or words and no variation to the order of the words. In 2014, Google expanded the reach of exact match by allowing for plurals and misspellings to map to the exact match keyword. Then in 2017, Google allowed for function words to be included, excluded or changed, and for words to be reordered.

The most recent change “will begin including close variations that share the same meaning as your keyword,” Google noted in September. Google is calling this exact match “close variants,” with the following examples of new queries that may match with “yosemite camping.”

Since about 15 percent of the searches Google sees each day are queries the company has never seen before, this change will likely be helpful for query-mining and ensuring that advertisers don’t miss a relevant search opportunity — especially those who don’t have the time or resources for extensive keyword builds. But what if you have a team dedicated to mining search query reports and adding every relevant variation you can find on exact match? At Adobe, we recommend continuing to do just that, at least in the short-term.

Google states that if you have the exact variation of the search query live in your account, they will honor it and map to that keyword before mapping to another keyword classified as exact match close variant. At Adobe, we’ve found success separating match types by campaign or ad group and “negative fencing” to direct traffic to exact match keywords that are more efficient. This is accomplished by adding the negative exact variation of a keyword to the respective phrase, broad and/or broad match modified campaign or ad groups and forcing a search query to match to the exact match keyword when one exists. If advertising with all match types, exact negatives are added to the phrase campaign or ad group and phrase negatives are added to the broad campaign or ad group.

One example of success with this type of structure was for an education customer. Looking at performance before and after the restructure, the advertiser achieved a 29 percent decrease in cost per click (CPC) — allowing for increased clicks at a lower cost — and a 36 percent decrease in cost per lead while achieving 38 percent more leads. We’ve seen similar successes when negative fencing queries to exact match keywords. In the short-term, Adobe account teams will continue to structure builds in this way and advise our advertisers to as well. However, we will be keeping a closer eye on search query reports.

In keeping with best practices for phrase, broad and broad match modified keywords, Adobe is extending the recommendation to closely monitor search query reports to exact match keywords. Now that exact match keywords can map to variations they were not able to before, it’s important to regularly review query reports for exact keywords — not only to add new exact match keywords — but to add negative keywords where needed as well.

In addition, it’s key to continue to add new ad variations to ad groups and set ads to optimize rotation, unless actively performing an ad copy test. Based on insights about the searcher and search intent, Google will serve the ad most likely to receive a click or convert. If an ad doesn’t perform well it will be served less and less, and eventually not served at all. There is no longer a need to pause ad variations unless it becomes irrelevant.

If an account is well-built, when a query matches exactly to a keyword the searcher is likely to see a more relevant ad as a result. In addition, you (or your bidding technology) can bid more precisely based on previous performance insights. It is challenging to bid precisely when the query to keyword mapping looks like below, as performance can vary even between singular and plural variations of the same keyword.

Visual of queries (blue) mapping to bidded keywords (green).

However, Adobe is continuing to build upon the Advertising Cloud Search technology — with features powered by Adobe Sensei, Adobe’s framework for artificial intelligence and machine learning. Our goal is, and always has been, to improve customer experience and performance. To that end, we work closely with Google to support product and strategy changes designed to support customer experience — both for searchers and the advertisers. Ultimately, we believe that Adobe’s partners and advertisers will continue to see success in search.