Which method should you use to implement and test broad match successfully on broad match campaigns to help analyze conversion data?
Correct Answer
You can implement broad match keywords by setting up a One-Click Experiment Apply. This creates an experiment automatically, following all experiment best practices.
Why is this the correct answer?
To implement and test broad match successfully and analyse conversion data, you should use One-Click Experiment Apply, which creates an experiment automatically following all experiment best practices. This method sets up a properly controlled A/B experiment — splitting traffic between your current keyword setup and a broad match version — so you can measure the actual impact on conversions with statistical confidence. Running an experiment ensures you see real conversion data from broad match without risking your entire campaign's performance.
Why are the other options incorrect?
You can use the Conversion Tracking feature in Google Ads to track the number of conversions that are generated by your broad match keywords.
Conversion Tracking records conversions but is not a testing methodology — it tracks results but does not structure the experiment needed to isolate the impact of broad match.
You can use the Keyword Planner to find new keywords that are relevant to your business and your target audience.
Keyword Planner finds new keyword ideas — it is a discovery tool, not a method for testing broad match implementation on existing campaigns.
You can use the Keyword Match Types feature in Google Ads to see how your broad match keywords are being matched.
Keyword Match Types feature shows how keywords are matching but is a reporting view, not a testing mechanism for implementing broad match.
Real-World Example
A retailer wants to test broad match on their exact match campaign. Using One-Click Experiment Apply, Google automatically sets up a 50/50 experiment splitting traffic. After 4 weeks, the broad match variant shows 34% more conversions at a similar CPA — conversion data the advertiser could measure with confidence because the experiment controlled for all other variables.