Google Analytics’ Attribution Modeling Tool Explained

August 5, 2013 2:53 pm Published by

According to one online marketer’s definition, the Attribution Modeling Tool is used to determine the value of each visitor’s lead source path to conversion. It is meant to help you gauge the performance of multiple marketing campaigns and improve conversions with better budget allocation strategies. These are the facts you should understand before using the attribution modeling tool:

  1. Multi-channel funnel visualizer shows which channels or lead source led to conversions
  2. Google Analytics only counts the last non-direct click as the channel source under non-attribution reporting areas
  3. Attribution modeling should be leveraged when there is a lead source tracking issue which results from a substantial overlap of channel sources

Element 360 Online Lead Generation

Although the multi-channel funnel on Google Analytics displays the channel source that led to each conversion on the site, it does not do a sufficient job in showing Analytics users what happens during beginning and middle of their path to conversion, because it only indicates where the last non-direct click came from. The lack of differentiation is a flaw in the current multi-channel funnel. However, with the new attribution modeling tool, Analytics users are now able to choose from a list of seven attribution models and compare as many as three of them side by side to gain further understanding of how channels interact to bring about conversions. The seven models include first interaction, last interaction, last non-direct click, last Adwords click, linear, time decay, and position-based. Here is a brief break-down of each model: (1) First Interaction model: gives attribution to the first interaction in the path (2) Last Interaction model: gives attribution to the last interaction in the path (3) Last Non-Direct Click model: default model used for comparison (4) Last Adwords Click model: gives attribution to last Adwords that was clicked before conversion (5) Linear Model: gives equal attribution to all interactions during the path (6)Time Decay model: gives relatively more attribution to most recent interactions than those further back (7)Position-based model: gives more attribution to the first and last interaction It is also possible to customize the channels and attribution models if you would like to be more specific about the comparisons. For example, some custom channels created may include “specific search engines”, “Facebook and Twitter”, “branded keywords”, etc. To customize attribution models, you can simply use the currently available attribution models as base and adjust their different features from the options provided. Perhaps you would like to extend the Look-back Window to 90 days or adjust the amount of credit given to middle interaction in the Position based model; however you’d like to edit the models is up to your decision. keywords: attribution modeling for real estate;

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