How we’re using AI to Revolutionize User Segmentation
Calvin Chan and Evan Situ
User segmentation is essential for enhancing the user experience. Personalized calls to action, for instance, can lead to a 202% increase in conversions. At Apply Digital, we’re enhancing user segmentation with cutting-edge AI and cloud tools. This approach unlocks deeply personalized experiences that traditional methods simply can’t achieve.
Our AI-Driven Approach
Traditional user segmentation models have their limits. They rely on rigid rules and complex structures, demanding constant updates to keep up with changing user behavior.
Our approach uses OpenAI and NLP to transform broad cohort-based segments into hyper personalized individual profiles. This approach bypasses the expensive, pre-packaged user segmentation tools in the market. Our model is backed by an architecture that treats user data as dynamic input, feeding into AI systems for real-time segmentation. This architecture enables us to build our own segmentation model, offering the power of 3rd party tools without the premium price. Our results not only enrich our understanding of our users but are also interpretable and actionable.
Architectural Insights
Our exploration of AI segmentation takes two forms. Language-based segmentation and action-based segmentation.
In language segmentation, we use large volumes of chat data to extract specific user attributes. To achieve individual segmentation, our AI model demands extensive user data. We accomplished this by developing chat products that deliver genuine value and utility to end users and seamlessly integrating analytics into these chat experiences and related web properties.
We process chat logs via Cloud Scheduler. ChatGPT and Cloud Functions then extract and map key user attributes. Our model goes beyond surface data, capturing twice as many consumer attributes with a 90% accuracy rate in mapping.
For action-based segmentation, we analyze user interactions with our website. OpenAI uses these behavior details for rapid and accurate user categorization. Dataflow then processes website interactions, creating a rich picture of user behavior that OpenAI leverages for predictive segmentation. This method has accelerated our model training and expanded our understanding of users.
For example, we provided OpenAI with real-time data on our Apply Digital website, including website navigation patterns, time on pages, and visit frequency. We defined segment categories like “Potential Clients,” “Industry Professionals,” or “Job Seekers.” This data stream enriches our consumer profiles within our CDP daily.
Conclusion
Our shift towards AI-driven, individualized segmentation dramatically enhances personalization and enriches user profiles. With our AI-driven approach, we were able to double the number of captured user attributes, and this robust model was built and implemented in mere weeks at a fraction of the cost of third-party tools. Our approach demonstrates the power of AI to transform data into actionable insights, enhancing the user experience.
Curious how AI can revolutionize your processes? Let’s explore solutions together — contact Apply Digital today.
