Understanding audience discovery
Learn about audience discovery and how you can use it to to improve your email marketing campaigns with personalized content.
With audience discovery, Moosend automatically detects information such as purchase probability and interest for product category and applies it to your email lists. You can use this to help manage your audience and, for example, send a relevant campaign to interested customers.
Audience discovery uses a tracking mechanism that tracks certain actions of your customers on your website, such as product views, add to cart, and purchase, and analyzes this information using filtering and AI-based machine learning models. The results of the analysis of these actions, also known as events, are stored as tags in the customers' accounts in the email list that is created when you connect a website to your Moosend account.
This means that all you have to do before you can start creating your segments is to enable audience discovery.
The audience discovery algorithms use data from the last 3 months and run daily to process new data collected from your website.
Filtering using audience discovery tags
When you enable audience discovery, Moosend adds audience discovery tags to the members on your email list. You can filter using these tags to see the members that have a certain tag. Audience discovery tags are colored and can easily be distinguished from member tags, which are white.
For further information, see Filter the members of your email list using audience discovery tags.
Creating segments
turns the audience discovery tags into segmentation criteria so that you can create advanced real time segments based on combinations of your users’ interest and intent to purchase a certain product or from a specific brand, as well as where they are in the sales funnel. You can then address these segments through email campaigns or other actions.
For further information, see Create custom segments.
Built-in segmentation criteria
When visitors interact with products on your website, audience discovery processes the data using a sequence of data-driven models and creates segmentation criteria based on website data. The segments fall within the following three categories:
Interest in product category or brand
The Moosend machine learning algorithm predicts each customer’s interest in a product category or brand from your website. It creates clusters of contacts with common interest in certain product categories and identifies the categories that contacts are most interested in.
Interest in brand
Interest in category
Tip
To get the best results from your campaign using audience discovery, we recommend a narrow product category focus.
Purchase intent for product category or brand
The Moosend machine learning algorithm predicts each customer’s probability to purchase a product from your website. It creates clusters of contacts with common interest in certain product categories and identifies the categories that contacts are most likely to purchase from, based on:
Purchase intent
Purchase intent for a product category
Purchase intent for a brand
Funnel stage
The funnel stage is a filtering model that identifies in which level of the sales funnel contacts are, based on their interactions with the website. The model is based on the assumptions that View or Add to Cart show intent, Purchase a product makes you an active customer, and Purchase more than once in 3 months interval makes you a loyal customer.
Audience discovery uses the following funnel stages: Low Intent, Mid Intent, Mid-High Intent, High Intent, Active Customer, Loyal Customer, and Very Loyal Customer.