Lytics' Interest Engines allow you to analyze, interpret, and incorporate user interests into your marketing activities. While Lytics Interest Engine is primarily used with webpages, Lytics provides 3 kinds of Interest Engines for various use cases and tactics.
- The Default engine, which examines web data using NLP (Natural language processing) to generate Topics (think keywords, categories, and subjects). This is the standard Interest Engine and requires no out-of-the-box configuration
- Custom Affinity Engines allow you to link custom fields associated with your content to your users. When incorporating data from Shopify, or offline systems that contain product data, Custom Affinity Engines allow you to associate features/attributes from your inventory with your users. For example, consider a database of articles with genre data. With a Custom Affinity Engine, you can track which genres each of your users has interacted with.
- Collaborative Filtersempower you to recommend items based on what other users do. This is analogous to "users also bought", or "users also read" recommendations that are often surfaced on Amazon or other websites. Using a Collaborative Filter algorithm, Lytics analyzes user behavior and exposes Recommendations via the Recommendation API.
Interest Engines are a rather foreign concept and you may be confused about how this can help improve your marketing initiatives. Keep in mind that the end goal is to gain a better understanding of your users. With Lytics' Interest Engine, there are two commonly used techniques to best utilize this powerful data:
Topics & Affinities: With the Default engine and Custom Affinity Engines, you can use the Lytics UI to view the Topic Taxonomy. This visualization displays how your Topics co-occur and relate to each other. The Topic Taxonomy view can be useful to visualize similar Topics, which can be useful in creating Affinities.
User Segmentation: Lytics Interest Engines output a new field on the user profile that captures the interests that a user has exhibited. Using this data, you can create high-powered audiences to target users with specific interests using Lytics Audience Builder.
Recommendations: Using Lytics' Recommendation API, you can enable personalized recommendations for your users based on their activities. For instance, you can recommend URLs based on a user's browsing history, or recommend products based on a user's purchase history. To get started with Recommendations, check out the Recommendation documentation, or navigate to the Experiences tab.
To create a new Interest Engine, navigate to the Engines page in the Content navigation dropdown, and click on the New Interest Engine button. When clicked, this displays a modal that allows you to select between:
- Custom Affinity Engine
- Shopify Engine
- Collaborative Filter
Each option will present you with a wizard to configure the Engine. Please contact Lytics Support if you experience any issues creating your new Interest Engine.
Updated 15 days ago