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Forecasting applications enable businesses to look into the future based on past data. This typically includes using time series data with one or more features (variables) to predict future values of the target. Weav AI have several forecasting recipes that can be used to build forecasting applications that use one or multiple variables as features to forecast the future values. Forecasting models on Weav AI take into consideration the effects of seasonality and trends.

• Revenue forecasting based on product usage, number of users or sales
• Capacity or resources forecasting
• Stock Price forecasting
• Supply Chain forecasting
• Demand Forecasting

Churn prediction applications enable businesses to get insights into future customer or user behavior based on multiple factors and events as they happen. Using insights from churn prediction applications, businesses can proactively take actions to prevent churn and increase customer or user satisfaction. Churn prediction recipes on Weav AI enable insights into future periods of churn probability (eg. churn probability in the next day, week, month etc.).

• User churn from free trial
• Customer churn prediction based in product usage, number of issues and customer support
• Predict user churn at different stages of user onboarding
• Sales pipeline conversion
• Customer Lifetime Value

Marketing Spend Optimization applications on Weav AI enable marketing organizations to allocate the optimal amount of spend budget on the appropriate marketing channel. The recipes on Weav AI first recommend the optimal campaign to run based on seasonality and events, and then use the Marketing Mix Model to recommend the optimized spend per marketing channel. On Weav AI, this application is usually powered by a series of ML models working together to produce the best recommendation.

• Campaign recommendation
• Ad Spend Optimization
• Per channel ROI and Revenue prediction

Named Entity Recognition applications allow extraction of standard and custom entities from plain text. On Weav AI, the NER recipes can be used to train models to extract custom entities from plain text. Weav AI also provides a fully integrated annotation and labeling tool to allow users to label text data seamlessly.

• Extract medications, procedures or diagnosis information from doctors’ notes
• Extract product names from user comments
• Extract ingredients from recipe text

Text Classification applications enable businesses to classify plain text into meaningful labels. These labels can then be used to drive actions or decisions that help other business use cases. Text Classification recipes on Weav AI support multi-label classification and also provides a fully integrated annotation and labeling tool to allow users to label text data seamlessly.

• Sentiment analysis on user comments
• Topic Modeling
• Content moderation
• User Intent comprehension