The most common forms of relational data are event history and purchase history. These are very common data points to have on your prospects, and they are very useful for decision making. However, with relational data, filter rules can get more complex that with simple data like the contact table. Let’s say, for example, that you have a set of data on the event attendance history of your prospects.
You have been running events in cities worldwide, and in each city, you have a business track and a technical track. The data is stored within custom data objects (data cards) as event history. As you have the contact’s email address as part of the registration, you are able to easily connect the event attendance history with the contact record – via email address.
To build a list, you want to find the contacts who attended the technical track of the event in Barcelona. The first step is to build a contact filter to search for the contacts you are interested in. Select “linked data cards” as a criteria type, and by selecting our event series, we’ll have access to the data we need.
Obviously one criteria will be “Event Location = Barcelona” and another criteria will be “Event Track = Technical”. However, here is where things get tricky. If you have these as two separate criteria, and use an “And” operator between them, then this filter will return contacts who attended the business track in Barcelona, but then attended the technical track in Munich. Not exactly what we were looking for.
The way to solve this is the “Plus” operator. At the end of the filter criteria row, where you would select “And” or “Or” for normal querying, you will have a new option of “Plus” for data card queries. By selecting this, a new criteria row is added right underneath your current row. This second condition will act only on the same data that the first condition found.
So, in our original example, “Event Location = Barcelona” PLUS “Event Track = Technical” will only return contact who attended the Technical track in Barcelona.
When you are using relational data, you will often find that the “Plus” operator is extremely useful for querying that data.