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One of the most powerful tools in understanding your data is the contact group. It lets you build almost any cut of data that you want. Most simply, this can be done with simple group overlap rules that show people who are in group A, but not group B for example.
A slightly more advanced technique is to combine groups and filters to perform robust group manipulation to create a combination of activity and data as a driver for a group definition. This process can be further automated using a marketing automation program to dynamically create a dashboard based on group membership.
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One of the most interesting reports in this dashboard is the Contact Field Completeness report. This report shows you, based on a view, how complete the fields are in contacts within that group. Each field is shown as being between 0 and 100% complete, giving you good insight into whether you have data to work with for the set of contacts in your group.
However, more interesting than this, is the results you get by clicking on a field of interest. For example, if we click on the "Title" field (98.2% complete), we can see that the data within that field is from a manual text field as it is obviously free form.
A quick look at this data gives you a good sense of whether it is of sufficient quality to build rules upon.
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Armed with this understanding, you can quickly tune your contact washing machine to best optmize the data that you have and the data that you need. With cleansed and normalized data, building segmentation rules, lead scoring rules, content personalization rules, and marketing analysis becomes significantly easier.
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