【PatientsForce Technical Topic】
In the pharmaceutical industry, telephone customer service systems face challenges such as large amounts of information, high process repetition, and real-time requirements. By integrating AI speech recognition, natural language understanding (NLU), and database integration technology, “Pharmaceutical Communication” provides pharmacies, clinics, societies, and hospitals with an efficient voice customer service solution to automate the structured voice data query process
Core technology and operating process
The core technology of “Yaoxuntong” is a multi-level processing architecture designed to convert voice input into accurate data output:
- Voice Input and Recognition (ASR): The system automatically answers incoming calls and uses AI Speech Recognition technology to convert the user’s spoken content into text. This process is optimized for proper nouns in the pharmaceutical field, ensuring high accuracy.
- Natural Language Understanding (NLU): The converted text is parsed by the NLU module. The module can identify intent (e.g., “check business hours” or “availability”), entities (e.g., “Daan District, Taipei City” or “name of a drug”), and keywords in statements.
- Database Connection and Query: Based on the intent and entity parsed by the NLU module, “Yaoxuntong” automatically connects with the back-end database in real time. This database can include structured data such as pharmacy hours, clinic outpatient tables, calendars of society events, or hospital department information.
- Intelligent logic judgment: The system has a built-in logic engine that makes judgments based on query results and default rules. For example, if the pharmacy you are looking for is currently closed, the system will prioritize the opening hours or provide other options that are nearby and still open.
- Voice Response Generation (TTS): The query results are converted into standardized text, which is then used to generate clear, standard voice responses to users through text-to-speech (TTS).
- Human Transfer Mechanism: For complex statements that cannot be accurately judged by NLU, or when a user explicitly requests to transfer a human service, the system will activate a human callback service to ensure that the service process is not interrupted and record any unresolved queries for subsequent analysis.
Data value and business applications
Every call made through “Yaoxuntong” will be recorded and analyzed. The backend system will automatically generate multi-dimensional data reports, such as:
- Query pattern analysis: Statistics on popular queries in different time periods or regions to gain insight into user needs.
- Hotspot Distribution: Analyze market activity and demand intensity in different regions through regional data queried by callers.
- Problem Type Classification: Categorize incoming call intent to understand common issues from most users, allowing organizations to optimize public information or service processes.
This data can help organizations shift from reactive response to proactive decision-making, elevating phone customer service from a mere service channel to a data source with market intelligence value.
With its automated, standardized, and data-based technical architecture, “Yaoxuntong” provides an efficient, scalable, and high-value solution in the field of pharmaceutical customer service.
