Full Conversion Tracking Coverage Is A Critical Success Factor

The majority of search campaigns that we rebuild, initially do not have accurate search ad conversion tracking in place. In the era of automated bidding, full tracking coverage for all types of conversions is crucial to each search campaign’s success.

There is a reason for this – conversion tracking can be difficult to implement and test. At Blastoff Labs we go to great lengths to set up search ad conversion tracking with 100% coverage of all conversion events.

We spider your website to locate exposed email addresses, as they are “conversion tracking leaks”.  We set up call conversion tracking if not present.  Because conversion tracking is so crucial, we go to whatever lengths are necessary to achieve 100% conversion tracking coverage.

Whether the events being tracked are form submissions, phone calls, or other conversion events that in the aggregate, they all are likely to lead to leads and transactions.

Conversion Tracking Metadata Drives Automated Bidding

The obvious reason for having accurate PPC campaign conversion tracking is, you won’t know what the performance of the campaign is without it. So it allows us to see how successful the campaign is. But that’s not the most important reason for it.

Even more importantly, and less obvious, the tracking information provides sends metadata associated with each conversion back into the automated bidding (machine learning) subsystem within the search platform.

Machine learning operating with 100% conversion tracking coverage can take campaigns to new levels of performance. It also reduces account management time which would be spent on manually adjusting bids to respond to changes in auctions.

Search Ad Conversion Tracking Pays Off

Getting 100% conversion tracking in place, and testing it for each type of conversion is worth the effort. The time spent to set it up is paid back in higher levels of campaign performance.

More: See our blog articles on machine learning, conversion tracking, and conversion value modeling.