Optimizing questions to retain engagement

A method optimizes questions to retain engagement. The method includes generating, using a machine learning model, a churn risk from user interaction data. The method includes selecting, when the churn risk satisfies a threshold, a field, from multiple fields, using multiple prediction confidences c...

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Hauptverfasser:	Scott, Glenn Carter, Mouatadid, Lalla, Furbish, Kevin Michael
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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creator	Scott, Glenn Carter Mouatadid, Lalla Furbish, Kevin Michael
description	A method optimizes questions to retain engagement. The method includes generating, using a machine learning model, a churn risk from user interaction data. The method includes selecting, when the churn risk satisfies a threshold, a field, from multiple fields, using multiple prediction confidences corresponding to multiple prediction values generated for the multiple fields. The method includes obtaining a prediction value for the field and obtaining a question, corresponding to the field, using the prediction value. The method includes presenting the question and receiving a user input in response to the question. GENERATING, USING A MACHINE LEARNING MODEL, A CHURN RISK FROM USER INTERACTION SELECTING, WHEN THE CHURN RISK SATISFIES A THRESHOLD, A FIELD USING PREDICTION CONFIDENCES CORRESPONDING TO PREDICTION VALUES GENERATED FOR MULTIPLE FIELDS OBTAINING A PREDICTION VALUE FOR THE FIELD OBTAINING A QUESTION, CORRESPONDING TO THE FIELD, USING A PREDICTION VALUE PRESENTING THE QUESTION RECEIVING A USER INPUT IN RESPONSE TO THE
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The method includes generating, using a machine learning model, a churn risk from user interaction data. The method includes selecting, when the churn risk satisfies a threshold, a field, from multiple fields, using multiple prediction confidences corresponding to multiple prediction values generated for the multiple fields. The method includes obtaining a prediction value for the field and obtaining a question, corresponding to the field, using the prediction value. The method includes presenting the question and receiving a user input in response to the question. 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GENERATING, USING A MACHINE LEARNING MODEL, A CHURN RISK FROM USER INTERACTION SELECTING, WHEN THE CHURN RISK SATISFIES A THRESHOLD, A FIELD USING PREDICTION CONFIDENCES CORRESPONDING TO PREDICTION VALUES GENERATED FOR MULTIPLE FIELDS OBTAINING A PREDICTION VALUE FOR THE FIELD OBTAINING A QUESTION, CORRESPONDING TO THE FIELD, USING A PREDICTION VALUE PRESENTING THE QUESTION RECEIVING A USER INPUT IN RESPONSE TO THE</abstract><oa>free_for_read</oa></addata></record>
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subjects	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title	Optimizing questions to retain engagement
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