Audience Discovery is an algorithm for automatically classifying a client's customers into audiences. This grouping occurs according to the categories of the products that those customers view.
For example, Audience Discovery might find a set of customers for a clothing retailer interested in women's jeans, women's dresses, boys clothing, and girls clothing, and that audience might represent "Moms." Or for a ticket resale site, it might find an audience of customers interested in Dear Evan Hansen, Come from Away, and The Lion King—a musical theater audience. The UI then presents those audiences alongside Web behavior metrics as well as demographic and technographic data. While Audience Explorer is used to create new audiences based on conditions and criteria, Audience Discovery creates audiences for you based on machine learning.
The goal is to solve some of the "cold-start problem," when marketers don't always know what to do to better personalize, by providing marketers with a data-driven understanding of who their customers are. From speaking to clients, Monetate has found that the algorithm is great for revealing data in these circumstances, among others:
- The client knows the audience exists but doesn't know how to target that audience on-site
- The client knows the audience exists but doesn't know how that audience behaves on-site
- The client doesn't know an audience exists and is surprised to find out about it
How Data Is Collected
Audience Discovery is built only on the first-party, account-specific data that's already being sent to Monetate.
It looks only at product view facts, tied to an uploaded product catalog, to categorize shoppers. Pulling in technographic, demographic, and Web behavior statistics that are already being provided to Monetate allows Audience Discover to layer in additional analytics and context. As a result, it uses no more data than what's already typically sent and served by the platform.