Before we get into multi-channel attributions, let’s first define the analytics term attribution modeling. For companies that have online sales, it can be challenging to determine what marketing channel deserves the credit for a conversion (sale). For instance, let’s say you’re on Facebook one day and you see an advertisement for a pair of sunglasses that you really want. You don’t click on the advertisement, however, and instead, google the company’s name. You find the company’s site at the top of the results and buy the awesome pair of sunglasses you want. What marketing channel deserves the credit?
Does the Facebook advertisement that initially sparked your interest and purchase intentions deserve the credit, or does the paid link you clicked on after googling the company deserve the credit? This is where attribution modeling comes in. The right model will help you (or your company) determine what channel should get the conversion credit. Today, popular data analytics solutions like Adobe Omniture and IBM CoreMetrics assign credit to the channel last used by the customer. So, in our example, those solutions would credit the paid Google search. But, if you think the Facebook advertisement should receive the credit, don’t fret! Not all data analytics solutions provide attribution modeling based on the last channel used, but ours does.
Our solution has what we call multi-touch attribution reporting meaning we empower our clients to hand pick what channels they believe deserve the credit. This ability can be an incredibly powerful marketing tool and can enhance a company’s understanding of its online marketing. In addition to having the reporting, FoxMetrics also allows users to toggle between different attribution models within the reporting, so our clients are not forced to stick with the initial model they chose during implementation. It can be switched at any time.
Our multi-touch attribution modeling gives customers more flexibility, accuracy, and more control of their attributions than most competitors can provide.