Personalized IVR Menu Adaptation via User Profile Retrieval
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Solution Overview
Problem
Conventional customer support systems, such as IVR, fail to provide personalized experiences as they do not consider user preferences or requirements, presenting the same options to all customers without differentiation.
Innovation Solution
A method and apparatus that apply user profile information to customize the call processing application by identifying and authorizing users, retrieving their preferences, and transmitting tailored menu options based on these preferences, allowing for personalized interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional customer support systems present the same options to all customers, then system simplicity is maintained, but user personalization and satisfaction are reduced
Solution Approach 1:
The system performs preliminary actions by collecting user preferences, behavioral patterns, and environmental factors before the customer support interaction begins. User profiles are pre-built and stored, allowing the system to quickly retrieve and apply personalized settings during the interaction without adding complexity to the real-time processing
Solution Approach 2:
The system creates simplified copies of user profiles containing essential personalization data (preferences, behavioral patterns, environmental factors) that can be quickly applied during customer interactions. This allows personalization without requiring complex real-time analysis of all user data
2Ease of operation
If user profile information is retrieved and applied to customize call processing, then user satisfaction and relevance are improved, but processing time and system complexity increase
Solution Approach 1:
User profiles containing preferences, behavioral patterns, and environmental factors are created and stored in advance before any customer support interaction occurs. This preliminary preparation allows the system to quickly retrieve and apply personalization data during calls without adding significant processing time
Solution Approach 2:
The system applies personalization selectively by retrieving only the specific profile elements relevant to each user's needs and the current interaction context. Rather than processing all possible personalization data, the system focuses on applying only the necessary local qualities (preferences, patterns, factors) to each specific customer interaction
3Productivity
If the system presents standardized menu options to all users, then system complexity is reduced, but interaction efficiency and user needs alignment deteriorate
Solution Approach 1:
The system prepares personalized menu options in advance by analyzing user profiles before the interaction begins. This preliminary customization allows efficiently presented menus to be tailored to each user's preferences and needs without requiring complex real-time decision-making during the interaction
Solution Approach 2:
The menu options dynamically adapt to each user based on their stored profile information. The system adjusts the presentation, ordering, and content of menu options according to individual user preferences, behavioral patterns, and environmental factors, allowing the interface to be flexible and adaptive rather than static and standardized
Data Source
AI summary
A method and apparatus of applying user profile information to a customized application are disclosed. One example method of operation may include receiving an inquiry message or call from a user device, identifying and authorizing the user from inquiry message information received from the inquiry message, retrieving a user profile comprising at least one user preference, applying the at least one user preference to a user call processing application, and transmitting menu options to the user device based on the applied at least user preference.