Marketing & Lead Generation

Digital lead ROI for real estate fails when ad platforms count form fills, portals charge per lead, and finance asks for cost per qualified enquiry or per site visit, each from a different export. Real estate marketing analytics need one numerator (fully loaded marketing spend) and one denominator (leads, qualified leads, or visits) that the whole GTM org agrees on.

FireAI ingests media spend, agency fees, and portal invoices where you connect them, maps UTMs and campaign IDs to CRM records, and applies qualification rules you own. You see digital lead ROI for Google Search, Meta, YouTube, display, and each major property portal with optional project and city slices.

How FireAI solves the problem: It keeps spend and lead lineage on a single calendar, flags duplicate and test leads, and supports blended versus channel-only views so you retire channels that look cheap on CPL but never convert to visits.

What FireAI tracks:

• Spend, leads, and qualified leads by channel, week, and campaign
• Cost per lead and cost per qualified lead with consistent definitions
• Downstream site visit and booking rates by channel when CRM ties hold
• Trend after creative, audience, or landing page changes

What you can ask FireAI:

• "What is our digital lead ROI for Meta prospecting versus Google high-intent search last month?"
• "Which portal delivers the best qualified lead to visit ratio for the west zone?"

CPL and CPA by source channel get debated every quarter when each vendor uses a different lead definition. CRM may store broker uploads, walk-ins, and performance marketing in one table without preserving original channel economics, so CPL and CPA numbers by channel never match board-ready math.

FireAI classifies first-touch and paid-touch tags, applies your rules for net-new versus duplicate, and attributes site visits and bookings where you track them. Real estate marketing analytics show CPL, cost per qualified lead, and cost per site visit by channel in one grid so you compare apples to apples before reallocating the next tranche of budget.

How FireAI solves the problem: It versions definitions by RERA phase or project launch, supports regional agency fee allocation, and highlights channels where CPL looks attractive but visit or booking cost is high.

What FireAI tracks:

• Raw and qualified CPL by channel, campaign, and geography
• CPA to site visit and CPA to booking when outcome data is connected
• Channel mix shift week over week and cost per incremental qualified lead
• Broker and digital in the same comparison view where tagging allows

What you can ask FireAI:

• "What is CPL and CPA for paid social versus search for Project Lakeside?"
• "Which three channels missed our target CPA to qualified lead this quarter?"

Site visit conversion analytics and event ROI break when open houses, project launches, and roadshows log attendance in spreadsheets while CRM site visits use different IDs. Marketing celebrates footfall; sales needs scheduled, qualified walkthroughs that tie to inventory shortlists.

FireAI links event registration codes, check-in, counselor assignments, and CRM visit objects with timestamps and project context. You see event and site visit conversion analysis from invite to show rate, to qualified visit, to shortlist, so underperforming formats surface before the next big launch.

How FireAI solves the problem: It de-duplicates walk-ins already in CRM, flags no-shows and rescans, and supports cohort views for expos versus property-specific events.

What FireAI tracks:

• Registrations, attendance, and qualified visit rate by event series
• Time from first digital touch to first site visit for event-tagged leads
• Conversion by counselor, day of week, and project
• Cost per site visit for paid registration drives and partner co-hosted events

What you can ask FireAI:

• "What was the site visit conversion rate from the last three roadshows compared to always-on digital?"
• "Which events drove high walk-ins but low booking follow-through?"

Broker referral ROI stays opaque when incentives accrue on registrations, while finance cares about cost per visit and per booking, and some deals touch multiple channel partners. Without linked outcomes, retainer and performance fees are hard to justify in real estate marketing analytics reviews.

FireAI attributes visits and bookings to broker codes, tracks tiered commission or bonus rules you define, and loads retainer and event sponsorship lines into the same view as digital spend. You see broker referral ROI by network, individual partner, and project, next to cpl cpa by channel for owned media.

How FireAI solves the problem: It reconciles double-attribution cases with a clear business rule, surfaces partners with high visit volume but low conversion, and models incremental bookings versus a baseline to avoid overpaying for deals that would have arrived anyway.

What FireAI tracks:

• Payout, visits, and bookings by broker and tier
• Cost per site visit and cost per booking for broker-sourced demand
• Share of pipeline from broker versus direct digital over time
• Concentration risk when a few partners drive most high-intent traffic

What you can ask FireAI:

• "What is our broker referral ROI for Tier-A partners in the last two quarters?"
• "Which brokers have rising visit share but flat booking conversion?"