Cohort analysis is a technique used to analyze the behavior of a group of individuals (or "cohorts") over a specific period of time. We leverage OpenAI's NLP and ML capabilities to understand the data associated with your cohorts and build predictive cohort analysis models.
We are leveraging Generative AI to fill in gaps in the data, identify patterns and trends, test new features, and create synthetic data for training cohort analysis models.
ThirdEye Data builds advanced AI-powered systems for enterprises to execute time-based, size-based, and segment-based cohort analysis.
We have prepared advanced Cohort Analysis AI models which are ready to be deployed.
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Before leveraging the cohort analysis models, businesses may have some common asks. We are trying to answer them here.
Generative AI powered cohort analysis systems can be used with a variety of data, including behavioral data, demographic data, and transactional data. The specific type of data that you can use will depend on the specific system that you are using.
The accuracy of generative AI powered cohort analysis systems depends on a number of factors, including the quality of the data that is used, the complexity of the model, and the specific use case. In general, generative AI powered cohort analysis systems are more accurate than traditional cohort analysis methods.
When using generative AI powered cohort analysis systems, it is important to ensure the security of your data. This includes taking steps to protect your data from unauthorized access, use, or disclosure. We consider using a system that offers encryption and all other important security features.
The scalability limitations of these cohort analysis systems depend on the specific system that you are using. In general, generative AI powered cohort analysis systems are more scalable than traditional cohort analysis methods. However, there are some systems that have scalability limitations.
There are a few risks associated with this kind of system: