Telegram Bot for Sales and Support Automation
Automated processing of 2000+ requests per month and reduced customer response time from 2 hours to 30 seconds for a service center network.
About the Client
A network of service centers for home appliance and electronics repair with 12 locations in Moscow region. Over 2000 inquiries per month through various channels.
Highly competitive market where response speed directly affects conversion. Customers leave for competitors if they don't receive a response within an hour.
Challenge & Problems
- Managers couldn't process all requests — up to 30% of leads were lost
- Average response time was 2+ hours during business hours
- Night and weekend requests remained unanswered until Monday morning
- No unified inquiry database — history was lost in chat threads
- Impossible to track repair status without calling a manager
- High call center load due to routine questions
Why standard solutions didn't work
Off-the-shelf bot builders didn't provide the needed integration with the client's internal CRM and didn't support complex request routing logic by device type and geolocation.
Project Goals
Reduce first response time
Automate request intake
Reduce call center load
Enable status tracking
Integrate with existing CRM
Our Solution
Developed a Telegram bot with multi-level request processing, intelligent routing, and full integration with the client's CRM. The bot operates 24/7, automatically classifies device type, determines the nearest service center, and creates a request in CRM.
Request Intake Module
Step-by-step form with validation: device type, problem description, photo, contacts
Intelligent Routing
Automatic service center selection based on device type and customer geolocation
CRM Connector
Two-way synchronization with client's internal system via REST API
Notification System
Push notifications about repair status, readiness, pickup reminders
Admin Panel
Web interface for operators with request queue and analytics
Architecture
Microservice architecture on Python with asynchronous message processing. Main bot on aiogram 3.x, separate service for CRM integration, Redis for caching and queues.
Integrations
REST API for CRM communication, webhook for status updates, Yandex.Maps API integration for geolocation.
Security
Personal data encryption, rate limiting for spam protection, audit log of all actions, GDPR compliance.
Scalability
Horizontal scaling through Docker Swarm, ready for loads up to 10,000 messages per minute.
Development Process
Analysis and Design
Studied business processes, interviewed managers and operators, designed user flow and architecture. 1 week.
Analysis and Design
Studied business processes, interviewed managers and operators, designed user flow and architecture. 1 week.
Prototyping
Created clickable dialog prototype, approved all scenarios with client. 3 days.
Prototyping
Created clickable dialog prototype, approved all scenarios with client. 3 days.
MVP Development
Implemented basic functionality: request intake, CRM integration, notifications. 2 weeks.
MVP Development
Implemented basic functionality: request intake, CRM integration, notifications. 2 weeks.
Testing
Functional testing, load testing at 1000 RPS, bug fixes. 1 week.
Testing
Functional testing, load testing at 1000 RPS, bug fixes. 1 week.
Launch
Phased launch at 3 locations, monitoring, feedback collection, adjustments. 3 days.
Launch
Phased launch at 3 locations, monitoring, feedback collection, adjustments. 3 days.
Scaling
Rollout to all 12 locations, staff training, documentation handover. 1 week.
Scaling
Rollout to all 12 locations, staff training, documentation handover. 1 week.
Technology Stack
Backend
Databases
Integrations
Infrastructure
Monitoring
Results
Measurable Results
First response time
was 2+ hours
Request conversion
due to instant response
Call center load reduction
routine questions handled by bot
24/7 request processing
night requests are not lost
Customer satisfaction (NPS)
based on survey results
Qualitative Improvements
- Unified history of each customer's inquiries
- Transparent repair status for customers
- Reduced stress for managers
- Ability to analyze common issues
- Foundation for further automation
Business Value
Bot investment paid off in 2.5 months through conversion growth and call center expansion savings. Monthly savings amount to ~$2,000 on operator payroll.
Current Usage
The bot processes 2500+ requests per month and is the main customer communication channel. 78% of customers prefer the bot over calling.
Scaling Opportunities
WhatsApp and VK integration planned, adding AI classifier for automatic fault type detection from photos.
Challenges & Learnings
Complex Routing Logic
Different service centers specialize in different device types, while customers don't always know exactly what's broken.
Implemented two-level system: bot first clarifies device category through visual menu with icons, then applies routing matrix considering center workload.
Visual selection works better than text — conversion at category selection stage increased by 25%.
Historical Data Migration
Old CRM had 50,000+ records with varying data quality, some without Telegram contacts.
Normalized data, created mechanism for linking customers without Telegram on first bot interaction.
Important to allocate time for data migration in such projects — it took an additional week.
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