Case Study
AI Lead Generation That Doubled Monthly Enquiries for a Pest Control Company
How Leadmetrics used AI lead generation to take a South Indian pest control company from 79 to 165 leads a month, nearly double its won customers, and cut Meta cost per lead by 38%.
Challenge
What we were up against
Leads With No Source
In the first month every lead arrived without a channel attached, and two-thirds still had none the month after. Without attribution, budget decisions were guesswork.
Customer and Job-Seeker Leads Mixed Together
Meta lead forms blended service enquiries with job applicants from recruitment campaigns, which made the cost per lead look better than it was and wasted the sales team's calls.
Expensive Paid Search
Google Search conversions averaged around ₹428 each in the last quarter of 2025, and a large share of enquiries were out of scope for the business.
Invisible in AI Answers
When people asked ChatGPT, Gemini or Meta AI for pest control help in the company's market, the brand did not appear in any of the five queries tracked at the start of the engagement.
Solution
How Leadmetrics helped
Leadmetrics treated lead generation as one system instead of a set of separate campaigns. Every enquiry was routed into the Leadmetrics CRM, where AI scoring, stage tracking and source attribution showed which channels produced paying customers. That data then drove where the spend, content and optimisation effort went each month.
Audit & Diagnosis
Reviewed every lead source, form and campaign to find where attribution was being lost Separated customer enquiries from recruitment leads so cost per lead reflected real demand Benchmarked paid-search cost per conversion and out-of-scope enquiry volume Tested five buyer-intent questions across ChatGPT, Gemini and Meta AI to set an AI-search baseline
Strategy & Planning
Made the Leadmetrics CRM the single destination for every web, Meta, Google and WhatsApp enquiry Set qualified leads and won customers, not clicks, as the primary KPIs Planned Meta lead-form and WhatsApp campaigns alongside Google Search and branded-search campaigns Built a monthly content and AI-search plan around the questions homeowners and facility managers actually ask
Execution
Shipped 340 deliverables between February and September 2026: 156 backlinks, 104 social posts, 33 blogs and 23 Google Business Profile updates Ran Meta lead-form, WhatsApp and seasonal festival-offer campaigns; one festival offer delivered 96 leads at ₹76 each Restructured Google Search campaigns around high-intent treatment terms Added schema markup and question-led content so AI assistants could cite the business
Monitoring & Optimization
AI lead scoring on every enquiry, with each lead moved through CRM stages to won or lost Weekly and monthly reports tying spend to leads and won customers by channel Monthly AI-search visibility checks across ChatGPT, Gemini and Meta AI Budget moved each month towards the campaigns with the lowest cost per qualified lead
Results
The impact delivered
- Monthly CRM leads averaged 79 in October–December 2025 and 165 in June–August 2026, with August 2026 peaking at 244. Across the full engagement (August 2025 to September 2026), the company logged 1,217 leads after spam and deleted records were removed.
- Leads marked won in the CRM rose from an average of 7.7 a month in October–December 2025 to 14.7 a month in June–August 2026, and 128 customers have been won across the engagement so far. The growth is in paying customers, not only enquiries.
- Meta cost per lead fell from ₹281 in January 2026 to ₹173 in August 2026, while monthly Meta conversions grew from 33 to 126. On Google Search, 106 conversions in August 2026 came in at about ₹298 each, against about ₹428 in the last quarter of 2025.
- Before the engagement, the company did not appear in ChatGPT, Gemini or Meta AI for any of its five tracked buyer queries. In September 2026, ChatGPT ranked it first for all five, Gemini listed it for four and Meta AI for all five. Every lead now carries a source, down from 100% unattributed in the first month.
Takeaways
Key lessons learned
Doubling lead volume was only possible once every enquiry had a source. Fix attribution first, then spend more.
Recruitment leads and out-of-scope enquiries flatter the cost per lead. Separate them and optimise for won customers instead.
Homeowners now ask AI assistants for service providers. Schema and question-led content can earn a first-place answer inside a single engagement.