Your data source uses your organisation’s own naming. Our platform uses a predetermined set of
columns, and a fixed set of tags and placeholders. Mapping is where the two are connected.
This matters because those tags and placeholders are what make a simulation credible.
Firstname becomes a placeholder inside the email, and Function title becomes a targeting tag
our ethical phishers can aim at. Data we cannot map is data they cannot use.
All tags are anonymised. They let phishers target a group without ever linking back to an
individual.
The two steps
They happen in order, and the difference between them is easy to miss.
Mapping column names
Match the headings in your file to our columns. Your Dept column becomes our
Department Name.See Mapping column names. Mapping column values
Match what is inside those columns to our tags. The value Finance in that column becomes
our Finance tag.See Mapping column values. The import wizard does much of this for you. It recognises common column names, and applies
values it has seen before automatically. What is left is what it could not work out on its
own.
How long it takes
Column names go quickly. Column values are the most time-consuming part of onboarding, at
roughly fifteen to thirty minutes depending on how varied your data is.
You only do it thoroughly once. Mappings are remembered, so later imports and new joiners
reuse what you set up here.
Next
Start with Mapping column names. 
