lang.ai

Lang.ai automates the tedious tasks involved in data engineering, providing each user with a clear and understandable analysis of the relevant information. By leveraging Snowflake data, it transforms product information, customer interactions, and revenue into actionable insights. Here are some specific examples of how Lang.ai can help you achieve your goals: **User Retention:** - **Reasons for Churn:** 5% of premium users leave due to a lack of customized options. - **Information Overload:** 20% of lost customers mention that they transferred their accounts to another bank because of the company’s closure. **Product Returns:** - **Holiday Sales:** There is a 25% increase in inquiries about product returns from customers during holiday sales periods. **Poor User Experience:** - **Mobile Apps:** 18% of mobile app users find it difficult to locate the option to export data. **Network Security:** - 45% of users express concerns about data security when deciding not to register on a platform. **Health-related Issues:** - 38% of patients who initially expressed discomfort during consultations did not go on to enroll in paid treatment programs. **High Costs:** - 17% of customers who provide negative reviews mention high costs as a major reason for their dissatisfaction. **Application Features:** - Among the key factors that drive users to promote a product, 25% are related to the budget-friendly features of the app. **Analysis:** - 32% of basic plan users inquire about advanced analysis tools. **Credit Rewards:** - 25% of loan customers mention that they received reward credit cards when using certain services.

In just a few minutes, Lang.ai synchronizes with Snowflake, captures relevant information from Snowflake tables based on your objectives (such as customer retention), transforms that data into valuable insights, and ultimately converts those insights into tangible commercial benefits.

AI agents used for customer retention, conversion, NPS measurement, and cross-selling activities.
Correlation discovery
Cultural insights from both top and bottom perspectives
Large-scale data processing
Slack integration