Impressions are one of the PRWeb stats that has been around for a long time.  It is a metric that has been traditionally connected to the advertising industry and in fact, PRWeb was the first service to apply it to the distribution of a news release.  In online advertising, an impression happens whenever an ad appears on a page that is loaded.  For example, if I visit CNN.com, the ad on the far right (for Groupon) has just received one impression.

Not only has the Groupon ad just received an impression, but so have all the stories displayed on the CNN home page.  Similarly, if someone visits the PRWeb news center, all the stories that are posted on the news center will receive an impression.

Impressions don’t just happen on the news center but also through the various news feeds that are part of the broader PRWeb distribution network.  In addition to showing up within the various sections on PRWeb.com, News releases on PRWeb also show up in a variety of news feeds and every time a story shows up in a news feed that is viewed, an impression is created.

In general, impressions is a metric that can provide users with a general sense for the distribution their release received on PRWeb.com.  It is worth noting that the impressions we report in our analytics dashboard are not comprehensive.  They do not account for the all the places that the news release shows up outside of our own domain.  Consider the following example from a customer called Lendio who distributed a news release this morning.  A Google News search for “Lendio” reveals the PRWeb story, which should theoretically count as an impression.  Of course, we have no way to count the impressions that the story has received in Google News.

Similarly, a release from Pepperdine University was published on PRWeb this morning and resulted in an article on the Wall Street Journal.  Without a doubt, the story received a wealth of impressions from the placement but once again, this is all activity that we are not able to track and report on.

There are other noted criticisms of the metric.  For one, just because a unit receives an impression doesn’t mean that someone has actually viewed it.  Eye tracking studies have essentially validated that a notable chunk of users filter out the majority of what actually appears on the page.  However, when examined in combination with complimentary metrics (e.g. reads, deliveries, etc.) impressions can provide a general sense of how many times a release appeared on a screen.

Filed under: Analytics by Jiyan