LeadIntel

A Kerala resort group was spending lakhs a month on Meta and Google, but its numbers lived in four different places. Ads Manager reported one thing, Google another, and the bookings sat in the CRM with no link back to the ad that produced them. I built LeadIntel to join it all up.

• Ad platforms report their own conversions, not the bookings the resort actually won
• Leads arrived in the CRM without reliable source tags, so no one could say which campaign paid off
• Reporting meant exporting spreadsheets by hand every week
• Management needed one screen that answered "is the money working?"

• Live connectors for Meta Ads, Google Ads, GA4 and TeleCRM, syncing automatically every 15 minutes while the app is open
• A marketing dashboard that counts revenue only when a booking traces back to a paid lead: spend, CPL, cost per reservation, attributed revenue and ROAS by platform
• Full Funnel Analytics: lead → interested → hot → booked, by channel and campaign, showing exactly where enquiries are lost
• Creative Intelligence: every Meta and Google ad scored on cost and bookings, with live Active / Off status and a period summary
• Audience, attribution, website, CRM, sales pipeline and OTA screens, plus repeat-customer tracking matched on phone number across 365 days
• An executive dashboard, saved views ("Monsoon push", "GM weekly") and CSV export

• Every metric is labelled by source (ADS, CRM, PMS or blended), so no one mistakes a platform estimate for a booking
• Cancellations are excluded and repeat bookings counted correctly
• It surfaced the resort's biggest blind spot: only 35% of leads carried a channel tag, which is now being fixed at the source

Most agencies report clicks. LeadIntel reports bookings. It is how I proved the resort's ads returned 5.9x in booked revenue in their best month, and where I decide what to scale and what to cut.