Case study
TeacherTee AI Inbound Lead Qualification System
An AI-powered inbound qualification workflow built with Make.com, LeadConnector, and Claude to enrich lead context, prioritise enquiries, and support better sales conversations.
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A full walkthrough of the TeacherTee AI Inbound Lead Qualification System is currently being finalised and will be published shortly.
The complete architecture, implementation details, screenshots, outcomes, and technical documentation remain available throughout this case study.
V1
Workflow Status
Supported
3
Integrated Platforms
Supported
TBC
Measured ROI
Pending Data
5x
Lead Context
Supported
Business context
Why the project mattered
Inbound sales workflows become harder to scale when qualification depends on manual review and fragmented lead information.
TeacherTee needed a practical system capable of capturing enquiries, enriching context, applying qualification logic, and supporting better sales conversations.
The project focused on improving operational efficiency while creating a more structured and repeatable qualification process.
Problem statement
What had to improve
Design an inbound lead qualification system that reduces manual triage, improves lead prioritisation, and gives the sales team actionable context before first contact.
Manual triage
Inbound enquiries required manual review before the team could determine priority, ownership, and next actions.
Limited lead context
Sales conversations often began with incomplete information, requiring additional research before meaningful qualification could take place.
Inconsistent prioritisation
Lead quality and urgency were assessed manually, making qualification and routing difficult to standardise.
Operational handoff friction
Information was fragmented across forms, CRM records, and booking systems, creating unnecessary coordination overhead.
Discovery & analysis
How the workflow was understood
Before designing the solution, the focus was understanding how enquiries entered the business, how qualification decisions were made, and where operational bottlenecks existed.
- The sales process required a clearer intake structure before automation could deliver meaningful value.
- The team needed lead information consolidated and enriched before discovery conversations occurred.
- Qualification decisions needed greater consistency across multiple inbound channels.
- The workflow also needed to fit naturally into existing CRM and sales operations processes.
Analysis method
The review translated operational observations into workflow requirements, automation logic, routing decisions, and CRM implementation rules.
Solution overview
What was built and why
Built an AI-powered inbound qualification and sales operations workflow using Make.com, LeadConnector, and Claude.
The system captures inbound enquiries, enriches lead information, generates sales intelligence, and routes opportunities automatically.
The objective was to reduce manual qualification effort while improving sales readiness and lead visibility.
Architecture
Architecture and workflow diagram
The workflow combines lead capture, AI qualification, CRM enrichment, opportunity management, and sales enablement into a connected operating system.
High-level system diagram showing how inbound enquiries progress from initial submission through AI qualification, CRM enrichment, opportunity creation, and discovery call booking within the TeacherTee sales process.
Implementation
Implementation Journey
Tools used
Make.com, LeadConnector, Claude
Step 1
Workflow review
Mapped inbound enquiry journeys, qualification requirements, and sales process dependencies.
Step 2
Automation design
Designed lead capture, enrichment, scoring, routing, and CRM update logic.
Step 3
AI qualification setup
Configured Claude to generate lead scores, summaries, risks, recommendations, and discovery questions.
Step 4
CRM and pipeline integration
Connected workflow outputs into LeadConnector to automate contact enrichment and opportunity creation.
Step 5
Testing and refinement
Validated workflow behaviour, eliminated duplicate actions, and improved reliability across all scenarios.
Evidence
Evidence Gallery
The screenshots below demonstrate the operational workflow, AI qualification outputs, CRM updates, opportunity management, and appointment automation.
Communication Snapshot Qualification Workflow
High-level architecture showing how diagnostic assessment submissions are transformed into AI-qualified opportunities through Make.com, Claude AI, and LeadConnector.
Make.com Automation Scenario
The core automation responsible for receiving submissions, checking existing records, triggering AI analysis, updating CRM fields, creating notes, and generating opportunities.
Communication Snapshot Assessment
The diagnostic assessment used to capture communication performance data from inbound prospects before qualification begins.
AI Lead Qualification Analysis
Claude AI generates an executive summary, lead score, priority rating, and business risk assessment based on submitted assessment responses.
AI Recommended Next Action
AI-generated follow-up guidance designed to support sales readiness with recommended qualification and discovery actions.
AI Qualification Fields Populated
Custom CRM fields are automatically updated with AI-generated lead intelligence, ensuring qualification data becomes part of the permanent contact record.
AI Business Risk Assessment
The CRM stores structured risk assessments covering budget, authority, timing, and implementation considerations to improve qualification consistency.
AI Discovery Preparation Note
An SDR-ready briefing note is automatically added to the contact record, providing discovery questions, qualification insights, and recommended discussion points.
Qualified Opportunity Created
The workflow automatically creates and routes a qualified opportunity into the appropriate LeadConnector pipeline stage for sales follow-up.
Pilot Call Form Qualification Workflow
High-level architecture showing how pilot call requests are enriched with AI sales intelligence and converted into qualified CRM opportunities.
Make.com Pilot Call Qualification Automation
The automation responsible for receiving pilot call submissions, checking existing records, triggering AI analysis, updating CRM fields, creating qualification notes, and generating opportunities.
Pilot Call Qualification Form
The pilot call request form used to collect company information, team size, learner volume, communication challenges, and business context before discovery.
AI Lead Qualification Output
Claude AI analyses the pilot call submission and generates an executive summary, lead score, priority rating, and business risk assessment.
AI Discovery Recommendations
AI-generated discovery questions and recommended next actions designed to support qualification and preparation before the discovery conversation.
AI Qualification Data Stored in CRM
LeadConnector contact fields are automatically updated with AI-generated qualification intelligence including executive summary, lead score, priority, and risk assessment.
AI Discovery Questions Stored in CRM
AI-generated discovery questions are stored directly within the contact record, providing structured guidance for the first sales conversation.
AI Qualification Summary Note
An automatically generated qualification note summarising lead score, priority, executive summary, and recommended sales actions.
Full Qualification Briefing Note
The CRM note combines AI-generated qualification insights with the original pilot call submission, creating a complete sales briefing in a single location.
Opportunity Created in Lead Pipeline
The workflow automatically creates a new sales opportunity and routes the prospect into the appropriate pipeline stage for follow-up.
Workflow Diagram
High-level workflow diagram showing how LeadConnector manages appointment booking, pipeline progression, internal notifications, and reminder communications after a prospect schedules a discovery call.
Full Automation Workflow
Native LeadConnector automation responsible for handling post-booking operations including opportunity stage updates, contact record updates, internal notifications, waiting logic, and reminder emails.
Discovery Call Booking Form
LeadConnector booking page used by qualified prospects to select an available discovery call slot directly from the TeacherTee calendar.
Booking Confirmation Screen
Confirmation page shown immediately after a prospect schedules a discovery call, providing appointment details and calendar integration options.
Contact Activity Log
LeadConnector contact timeline showing successful appointment creation and automated activity logging against the prospect record.
Opportunity Stage Updated
Opportunity automatically moved into the Discovery Call Booked pipeline stage following successful appointment scheduling.
Contact Created or Updated
LeadConnector contact evidence showing the prospect record created or updated as part of the inbound lead and booking workflow.
Confirmation Email Sent
Automated confirmation email delivered to the prospect containing appointment details, meeting information, and calendar links.
Outcomes
Outcomes and impact
The workflow replaced manual lead review with an automated qualification and routing process that prepares the sales team before first contact.
Before
- Manual review required before qualification.
- Limited visibility into lead quality and urgency.
- Discovery preparation relied on manual research.
- Routing decisions varied between enquiries.
After
- AI-generated qualification completed automatically.
- Discovery calls begin with structured lead intelligence.
- Manual research effort significantly reduced.
- Lead routing and prioritisation standardised.
Metrics
V1
Workflow Status
Supported
3
Integrated Platforms
Supported
5x
Lead Context
Supported
TBC
Measured ROI
Pending Production Data
Outcomes
Discovery conversations are now supported by AI-generated business context, risk analysis, recommendations, and qualification insights before the first call.
Lead records contain significantly more actionable information than standard form submissions, reducing preparation effort and improving sales readiness.
Manual qualification tasks have been reduced through automated enrichment, scoring, and opportunity creation.
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Lessons learned
Sales automation requires clear qualification rules
Automation delivers the greatest value when qualification criteria are structured and consistently applied.
Better context creates better conversations
Providing summaries, risks, and recommendations before first contact improves preparation and confidence.
Adoption is more important than complexity
The workflow was designed around existing sales processes to maximise practical day-to-day usage.
Future
Future enhancements
The documented roadmap identifies practical ways the workflow could be extended once production data is available.
ROI and conversion reporting
Lead quality analytics dashboard
Automated follow-up sequences
Discovery call outcome tracking
Additional AI qualification models
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