You can use your analytics software to see how many people have visited your page during any period. Most often, though, this number will have internal traffic counted as well. Internal traffic is that which derives from your own employees, and your results can be seriously skewed if they visit the page numerous times a day. Generally, it is possible to exclude your own IP address, but if not, keep in mind that internal traffic means nothing to your overall numbers.
Statistics indicate that violent crime rates go up as ice cream sales increase. This is a correlation, but it does not mean ice cream causes violent crime. In fact, the two actually rise as the weather gets warmer. Never think that your internet site traffic increasing or decreasing is definitely related to a concurrently running web marketing strategy. Delve deeper into the analytics to find out if they are really related.
Failing to Weed Out Internal Traffic
Analytics tools will record the number of people visit your website on any given day. Unless you have set everything up correctly, though, this will include internal traffic. This is traffic coming from your own business, and since staff members may need to visit the site multiple times a day, it can really throw off the results. Fortunately, you can rule out your company’s IP address from the results, but if you choose not to, keep in mind that internal traffic is not really indicative of a great campaign.
Counting Views as if they are Visits
It cannot be understated that webpage visits are different than webpage views. If a purchaser is doing research and visits 12 of your pages, that is still only one customer. If you foolishly believe that 12 page views are unique visitors, the analysis of your current online marketing strategy will be far from accurate.
Correctly using analytics can be puzzling, and this is why many businesses hire third parties to handle it for them. Whether you are handling analytics by yourself or simply want to see your numbers, avoiding the previously mentioned mistakes can go quite a distance in better understanding the data.
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