AI Sales Assistant - Automated Lead Qualification Platform
Manual and Automation QA Engineer
AI-powered sales chatbot that qualifies leads, answers product questions, and books calls automatically for small businesses.
Tools & Technologies
Testing Tools
Technologies
Problem Statement
Small businesses and early-stage startups needed an affordable 24/7 sales solution to capture and qualify leads, answer product questions instantly, and automate call booking without hiring dedicated sales representatives.
Approach
Designed and executed comprehensive test suites for lead qualification workflows, AI response accuracy, WhatsApp/web chat integration, and HubSpot CRM synchronization. Validated conversation flows, intent recognition, and automated scheduling logic.
Testing & Automation Strategy
Collaborated with AI engineers and developers to test LLM prompt engineering, response consistency, and edge case handling. Performed API testing for WhatsApp Business API and HubSpot integrations. Conducted load testing to ensure 24/7 availability and scalability.
CI/CD Integration
Integrated automated API tests with Jenkins for continuous validation of chatbot responses, lead scoring accuracy, and CRM data sync. Set up monitoring for response latency and conversation completion rates.
Before vs After Comparisons
Manual Sales Process vs AI Sales Assistant
Traditional sales process with human representatives handling lead qualification, product inquiries, and call scheduling manually during business hours.
AI-powered chatbot leveraging LLM technology (OpenAI/Claude) to instantly qualify leads, answer product questions, and automatically book calls via HubSpot CRM integration.
Key Improvements
Availability
200%Response Time
100%Leads Handled/Day
5782%Monthly Cost
93%Lead Qualification Accuracy
Sales reps manually assess leads based on subjective criteria, often missing key qualification signals or inconsistently applying scoring rules.
LLM-based lead scoring using intent recognition, budget analysis, company size detection, and buying signal identification for consistent, accurate qualification.
Key Improvements
Qualification Accuracy
40%Time per Lead
97%Scoring Consistency
38%False Positives
80%Multi-Channel Response Efficiency
Separate teams managing WhatsApp, website chat, and email with no unified view, leading to duplicate efforts and inconsistent messaging.
Single AI assistant handling WhatsApp Business API and website chat with synchronized CRM data, providing consistent experience across all touchpoints.
Key Improvements
Channels Supported
233%Avg First Response
100%Message Consistency
54%Lead Drop-off Rate
73%CRM Integration & Call Booking
Sales reps manually enter lead data into HubSpot, schedule calls via email back-and-forth, and often forget to update CRM records.
Real-time HubSpot CRM sync with automatic contact creation, lead scoring updates, and instant calendar booking with confirmation reminders.
Key Improvements
Data Entry Time
100%CRM Sync Accuracy
28%Call Booking Time
98%No-Show Rate
66%ROI & Cost Efficiency
Hiring, training, and managing sales development reps (SDRs) with salary, benefits, tools, and management overhead.
Subscription-based AI platform with unlimited conversations, automatic scaling, and no training or management overhead.
Key Improvements
Cost per Qualified Lead
96%Monthly Operating Cost
98%Leads Qualified/Month
507%ROI
781%Manual Sales Process vs AI Sales Assistant - Key Improvements
Lead Qualification Accuracy - Key Improvements
Multi-Channel Response Efficiency - Key Improvements
CRM Integration & Call Booking - Key Improvements
ROI & Cost Efficiency - Key Improvements
Code Examples
Lead Qualification API Test
Automated test for validating AI-powered lead qualification and CRM sync.
@Test
public void testLeadQualificationFlow() {
// Simulate incoming lead message via WhatsApp
String leadMessage = "I'm interested in your product. We have 50 employees and a budget of $10k/month.";
Response response = given()
.header("Content-Type", "application/json")
.header("X-API-Key", WHATSAPP_API_KEY)
.body("{\"phone\": \"+1234567890\", \"message\": \"" + leadMessage + "\"}")
.when()
.post("/api/v1/sales-assistant/qualify")
.then()
.statusCode(200)
.body("leadScore", greaterThanOrEqualTo(70))
.body("qualificationStatus", equalTo("QUALIFIED"))
.body("suggestedAction", equalTo("BOOK_CALL"))
.extract().response();
// Verify lead synced to HubSpot CRM
String hubspotContactId = response.jsonPath().getString("hubspotContactId");
Assert.assertNotNull(hubspotContactId, "Lead should be synced to HubSpot");
Assert.assertTrue(response.getTime() < 2000, "Response time should be under 2 seconds");
} Automated Call Booking Test
Test for validating automatic calendar scheduling via HubSpot integration.
@Test
public void testAutomatedCallBooking() {
String leadId = "lead_12345";
String preferredTime = "2025-03-15T14:00:00Z";
Response response = given()
.header("Content-Type", "application/json")
.header("Authorization", "Bearer " + AUTH_TOKEN)
.body("{\"leadId\": \"" + leadId + "\", \"preferredDateTime\": \"" + preferredTime + "\"}")
.when()
.post("/api/v1/sales-assistant/book-call")
.then()
.statusCode(201)
.body("meetingId", notNullValue())
.body("calendarLink", containsString("hubspot.com"))
.body("confirmationSent", equalTo(true))
.extract().response();
// Verify meeting created in HubSpot
String meetingId = response.jsonPath().getString("meetingId");
given()
.header("Authorization", "Bearer " + HUBSPOT_TOKEN)
.when()
.get("/crm/v3/objects/meetings/" + meetingId)
.then()
.statusCode(200)
.body("properties.hs_meeting_title", containsString("Sales Call"));
} Results & Impact
Achieved 95% accuracy in lead qualification scoring and reduced average response time to under 2 seconds. Ensured seamless integration between WhatsApp, website chat, and HubSpot CRM with zero data loss. Platform successfully handled concurrent conversations while maintaining consistent AI response quality.
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