FAQ from OpenOs
What is OpenOs?
OpenOs is the ultimate no-code predictive analysis tool that allows users to uncover data insights without coding. It offers a natural language to SQL interface, advanced analytics, and the ability to build predictive models. OpenOs helps teams in marketing, product, and customer success to harness the power of data science for their decision-making process.
How to use OpenOs?
To use OpenOs, simply sign up for an account and connect your data source. Once connected, you can build predictive models by typing natural language queries such as 'Predict user churn & purchases for users from Source A within the next 7 days'. OpenOs delivers real-time predictive insights, provides feature analysis and smart segmentation, and allows for time series analysis to forecast metrics. Additionally, you can integrate OpenOs with your favorite tools like Google Analytics and Mixpanel for real-time ML analysis.
Do you offer a free trial?
Yes, OpenOs offers a generous two-month free trial. Billing only occurs when predictive models reach a prediction accuracy of 75% or more. No card on file or contract is required to get started.
Is the tool similar to Mixpanel or Google Analytics?
OpenOs complements tools like Mixpanel and Google Analytics by providing predictive capabilities on top of their analytical insights. It integrates with Mixpanel and Google Analytics as a data source.
What if my data is unorganized or needs structuring/cleaning?
OpenOs is designed to handle unstructured data. It takes care of all necessary data cleaning and preparation steps to ensure data is ready for predictive modeling.
Do I need any technical knowledge to use the product?
No, OpenOs is specifically designed for non-technical teams. No coding or technical skills are required to use the platform.
How customizable is the product?
OpenOs offers a two-fold approach to customization. During onboarding, tailor-made models are developed to provide automated insights. Afterward, users have the freedom to design their own predictive models using the platform without any coding experience.