Train AI with ticketing data
1. User authorizes ticketing access
Your users authorize your application to access their Ticketing platform by going through an authorization flow using Merge Link.
2. Retrieve comprehensive ticketing data
Utilize Merge’s API endpoints, such as GET /tickets, GET /teams and GET /collections to retrieve comprehensive ticketing data.
3. Clean and transform data
Clean the data by removing duplicates in your customer data, handling missing values, and filtering out irrelevant fields. Transform data into a format suitable for AI training, possibly involving normalization, encoding, or feature engineering.
4. Model training
Split the preprocessed ticketing data into training and testing sets. Use the training set to train an AI model tailored for issue resolution and support analytics.
5. Validate model performance
Validate the model’s performance using the testing set. Compute relevant metrics to gauge the model’s effectiveness.
6. Monitor and retrain
Continuously monitor ticketing data for updates, changes, and new information and implement a feedback loop for model retraining and improvement to adapt.
7. Surface insights to customers
Build a UI to provide your customers with valuable insights generated by the AI models, such as predictive trends based on historical ticketing data and personalized recommendations for issue resolution.
