Populations are an important concept in Crossbeam because they are the common language that allows you and your partners to combine and compare your data.
Populations are simply groups of people or companies that have significance to your business. You could think of them as segments of the data from your data source. These populations are most often mapped to key stages in your funnel, so common examples include Leads, Qualified Opportunities, and Customers.
Populations serve two important purposes in Crossbeam:
Data cleansing. Everyone's data is dirty, and populations are a way of cleaning out the mess. Rather than share your entire list of accounts or every lead ever generated, you can use populations to refine your data into the segments that actually matter and reflect the reality of your business.
Standardization. Not all data sources are created equal. If you use Salesforce, your partner uses Hubspot, and a third partner uploads a CSV, it would be extremely impractical to compare all that raw data directly to find overlaps. By having all parties organize their data into populations, Crossbeam's matching algorithm can compare and combine data sets on an apples-to-apples basis with far greater speed and accuracy.
It's important to note that populations are not meant for data analysis or detailed segmentation. Most companies create just a few large, broadly-defined populations. Later on, they segment the results of those comparisons using Reports in order to analyze overlaps in detail.
Ready to build a population? Here's how.