107. Inquiry Automatic Classification AI Design
The quickest way to speed up inquiry responses is "routing." AI automatically classifies inquiries, determining the responsible party, priority, and next action immediately.
The reason for the delay in responding to inquiries is not the content of the replies, but rather the "slowness of sorting." When inquiries with diverse content arrive in the same inbox, time is consumed in assigning responsibilities, prioritizing, and confirming necessary information. As a result, there are delays in hot leads, technical questions remain unresolved, and support-related issues are more likely to escalate. In this service, we will design a system that automatically classifies received inquiries using AI, assigning responsibility, priority, identifying missing information, providing expected response templates, and determining the next actions. Once the process of **"immediate sorting → immediate response"** begins, both response speed and conversion rates will increase simultaneously. ■ Provided Content (3 Points) 1. Classification design (categories, priority, assignment rules, exceptions) 2. Automatic judgment logic design (AI judgment + rule combination, reliability) 3. Operational design (human verification, improvement of misjudgments, KPIs) *First, please tell us the "types of inquiries (quotes/technical/agency/recruitment/complaints, etc.)." We will create a classification system from there.*
basic information
■Concerns like these - Delays in initial responses to inquiries, leading to missed opportunities - Assignment of responsibilities becoming overly dependent on individuals, resulting in unstable handovers - Mixing of technical questions and estimates, causing delayed responses - English support for overseas inquiries often being inconsistent - Time wasted on spam and sales emails ■Provided Content (Details) - 1) Classification design (deciding on the "box" first) - 2) Priority design (shaping response speed into KPIs) - 3) Handover output design (ensuring sales can "respond immediately") - 4) AI judgment + rule combination (ensuring operational sustainability) - 5) Operational design (addressing misjudgments through "improvement" rather than "learning") ■Deliverables - Classification system (category list, definitions, examples, exceptions) - Priority rules (Hot/Warm/Cold judgment criteria) - Assignment rules (by department/product/country, etc.) - Output format (summary, missing information, recommended actions) - Template response set (optional: by category) - Operational rules (human verification, misjudgment improvement, audits, SLA) - KPI design (first response time, assignment accuracy, conversion rate to business discussions)
Price information
■2.5 million yen to 12 million yen (varies based on scope of collaboration and classification depth) - Light (classification design + basic judgment + ledger output): 2.5 to 4.5 million yen - Standard (priority/assignment of responsibilities/extraction of missing information/operational design): 4.5 to 7.5 million yen - Extended (multilingual, CRM/MA integration, template auto-generation, audit enhancement): 7.5 to 12 million yen *Estimate required
Delivery Time
Applications/Examples of results
■Purpose - Speeding up initial response (immediate categorization) - Reducing missed hot leads (prioritization) - Optimizing division of labor among technical, sales, and support teams - Standardizing response quality (extracting missing information and templating) - Initial organization of multilingual inquiries (resolving delays in English responses) ■Examples of Achievements - Mixed inquiries from estimates, technical, and agents → Improved initial response speed through automatic classification - Insufficient inquiry information → Reduced back-and-forth by extracting missing items - Overseas inquiries → Resolved delays through language determination and assignment of responsibility ■Approach 1. Inventory of inquiries: Classifying past emails/forms 2. Classification and prioritization design: Confirming categories and criteria 3. Output design: Formatting for use by sales and technical teams 4. Implementation/integration: Connecting to email/forms/CRM/ledgers (depending on the environment) 5. Testing: Verifying accuracy and exception handling with representative inquiries 6. Operation: Monthly improvement of dictionaries and criteria (increasing accuracy)
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