Your Online Strategy Could Fail Over These Analytics Errors
Did you know that violent crime rates surge as ice cream sales increase? This is called a correlation, but it certainly does not imply that ice cream causes violence. The two increases are instead caused by warmer weather. Even though the traffic to your website changes while running a new campaign does not necessarily mean the two are connected. Investigate your data further to ensure they are actually related.
Thinking Correlation Means Causation
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 website traffic increasing or decreasing is unquestionably related to a concurrently running marketing strategy. Explore deeper into the analytics to find out if they are really related.
Failing to Filter Out Internal Traffic
Analytics tools will record the quantity of people visit your website on any given day. Unless you have set everything up perfectly, though, this will include internal traffic. This is traffic coming from your own company, and since personnel may need to visit the site multiple times a day, it can really alter the results. Fortunately, you can exclude your company’s IP address from the results, but if you choose not to, understand that internal traffic is not necessarily indicative of a great campaign.
Counting Views as if they are Visits
It cannot be understated that webpage visits are different than website views. If a shopper is doing research and visits 12 of your pages, that is still only one customer. If you mistakenly believe that 12 page views are unique visitors, the analysis of your current online strategy will be far from accurate.
Effectively using analytics can be complicated, and this is why many firms hire third parties to handle it for them. Whether you are handling analytics by yourself or simply want to see your numbers, avoiding the aforementioned mistakes can go quite a distance in better understanding the data.
