Our-Hometown launching beta test of Official Ad Network

Our-Hometown launching beta test of Official Ad Network
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At Our-Hometown Inc., we are always looking for new and innovative ways to help our customers generate revenue through their websites. Today, we are pleased to continue that trend with the announcement of our upcoming Official Our-Hometown Ad Network!

Publishers using the Our-Hometown Ad Network will have ads automatically distributed throughout their website, each optimized for desktop or mobile viewing depending on the device the reader is using. All standard ad sizes will be supported and will be featured in high-traffic areas such as the top of the page, in between article sections, and in the sidebar of your website.

Publishers are then compensated for any clicks these ads generate from their website each month.

While “ad networks” are not exactly a new concept, existing options — including the mega-popular Google AdSense network — have left some room for improvement.

For example, some publishers have had trouble even activating Google AdSense on their website, while others have successfully activated AdSense only to have their ads pulled with no explanation several weeks later. Despite efforts to work with Google to resolve these issues, no real solution has been provided. As a result, publishers are missing out on much-needed revenue, prompting us to develop our own solution.

While we are not yet able to provide any guarantee of revenue, we plan to do extensive testing and research to determine what kind of results our customers can expect from using our network. To do so, we’ll need your help!

We are now recruiting volunteers to participate in our initial beta test of the Our-Hometown Ad Network

If you’re interested in helping us test out this major new offering, just fill out the short form below with your newspaper/website information and we’ll reach out to follow up when we begin testing. 

Please note that not all customers will be eligible for the beta test, as we will be reviewing traffic patterns to determine the best candidates. 

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