Customer success optimization via mixed integer programming

Abstract

A method includes obtaining an expert availability forecasting model including at least a first time slot, a multitude of available experts corresponding to the at least first time slot, and a predicted customer demand corresponding to the at least first time slot. An expert allocation model is generated, including a first set of available experts allocated to the at least first time slot based on the expert availability forecasting model. A first set of customers is selected, corresponding to the predicted customer demand. The first set of customers is matched to the corresponding first set of available experts in the at least first time slot, based on the expert allocation model, to obtain a customer-expert allocation schedule. The method further includes transmitting the customer-expert allocation schedule to a performance analytics dashboard. The method further includes monitoring at least one data source for at least one expert availability event. PATENT APPLICATION 43 20 25 27 14 33 27 N ov 2 02 5 P A T E N T A P P L I C A T I O N 2 0 2 5 2 7 1 4 3 3 2 7 N o v 2 0 2 5 4 3 F IG . 1 1 / 6 D A T A R E P O S IT O R Y 1 20 10 0 S Y S TE M C U S T O M E R M A N A G E M E N T A P P LI C A TI O N 1 02 D E M A N D P R E D IC T O R 10 4 R E S O U R C E A LL O C A T IO N E N G IN E 1 05 A D JU S T M E N T T O O L 1 07 P E R F O R M A N C E A N A LY T IC S D A S H B O A R D 10 3 S E C U R IT Y A N D C O M P LI A N C E L A Y E R 1 08 C U S T O M E R M A N A G E M E N T H IS TO R Y 1 22 C U S T O M E R D E M A N D D A T A 1 23 E X P E R T U S A G E D A T A 1 24 E V E N T S T O R E 1 26 C U S T O M E R D A T A 1 27 E X P E R T D A T A 1 28 P E R F O R M A N C E M E T R IC S D A T A 12 5 S E R V E R C O M P U T IN G S Y S T E M 1 10 M IX E D IN TE G E R L IN E A R P R O G R A M M IN G ( M IL P ) S O LV E R 1 06 E X T E R N A L D A TA S O U R C E (S ) 13 0 1 0 0 S Y S T E M SERVER COMPUTING SYSTEM 110 P E R F O R M A N C E CUSTOMER MANAGEMENT ANALYTICS DASHBOARD A P P L I C A T I O N 1 0 21 0 3 RESOURCE ALLOCATION E N G I N E 1 0 5 MIXED INTEGER LINEAR D E M A N D P R E D I C T O R P R O G R A M M I N G ( M I L P ) ADJUSTMENT TOOL 107 1 0 4 S O L V E R 1 0 6 E X T E R N A L D A T A 1 / 6 SECURITY AND COMPLIANCE LAYER 108 S O U R C E ( S ) 1 3 0 DATA REPOSITORY 120 CUSTOMER MANAGEMENT HISTORY 122 E V E N T S T O R E 1 2 6 CUSTOMER DEMAND DATA 123 EXPERT USAGE DATA 124 C U S T O M E R D A T A 1 2 7 PERFORMANCE METRICS DATA 1 2 5E X P E R T D A T A 1 2 8 F I G . 1 20 25 27 14 33 27 N ov 2 02 5 2 0 2 5 2 7 1 4 3 3 2 7 N o v 2 0 2 5 SERVER COMPUTING SYSTEM 110 CUSTOMER MANAGEMENT A P P L I C A T I O N 1 0 21 0 3 RESOURCE ALLOCATION E N G I N E 1 0 5 MIXED INTEGER LINEAR D E M A N D P R E D I C T O R P R O G R A M M I N G ( M I L P ) 1 0 4 S O L V E R 1 0 6 1 / 6 SECURITY AND COMPLIANCE LAYER 108 DATA REPOSITORY 120 CUSTOMER MANAGEMENT HISTORY 122 CUSTOMER DEMAND DATA 123 EXPERT USAGE DATA 124 PERFORMANCE METRICS DATA 1 2 5 F I G . 1

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