How Raya Homes LLC Gained a Competitive Edge with AI-Driven Analytics
Raya Homes LLC partnered with DataToInsights to unify scattered data—from MLS and ad platforms to call logs and spreadsheets—into a single analytics layer. Within 90 days, they automated lead qualification, surfaced hyper-local pricing signals, and transformed their marketing operations across Morrisville, Cary, and nearby neighborhoods. The result: faster decisions, smarter pricing, and measurable growth in both speed-to-lead and marketing ROI.
Client: Raya Homes LLC
Owner: Sanju Rayamajhi
Address: 1403 Grace Point Rd, Morrisville, NC 27560
Industry: Residential Real Estate (Triangle, NC)
Data silos slowed decisions and obscured ROI. MLS exports were manual, ad performance inconsistent, and call summaries trapped in spreadsheets. Pricing relied on limited comps instead of live market signals.
Impact: Missed hot leads, slower pricing cycles, and lower campaign efficiency.
Sources: MLS, Zillow/Realtor.com, website forms, Google/Meta Ads, GA4, call logs, Sheets
Platform: Snowflake, dbt, Fivetran/Airbyte, Airflow
AI Layer: RAG, lead scoring, summarization
Governance: Role-based access, lineage, cost controls
“With DataToInsights, we stopped guessing. Our agents start each morning with the hottest leads, our pricing reflects real micro-market dynamics, and our ads finally earn their keep.”
— Sanju Rayamajhi, Owner, Raya Homes LLC
Truth over opinions through a unified data model. AI nudges for real-time actions. Weekly experiments built a tight feedback loop. Early wins secured long-term adoption.
Want the same edge in your market? DataToInsights can deploy a pilot in 2–4 weeks with your MLS, ad accounts, and CRM.
Contact: hello@cloudpro.ai | datatoinsights.ai | cloudpro.ai
Connected MLS (TMLS), Zillow/Realtor.com leads, Meta/Google Ads, GA4, call logs, and spreadsheets into a single semantic model. Validated with data quality checks for completeness, duplicates, and schema drift.
Automated lead scoring based on behavior, sentiment, and engagement. Smart routing and AI copilot suggested replies and next best actions for faster follow-ups.
Micro-market insights using hyper-local comps, school zones, commute times, and seasonality. Scenario testing revealed optimal price bands and renovation ROI.
Unified ROI across Meta, Google, and Zillow ads. Automated weekly experiments and budget reallocations based on predicted CPA improvements.
Role-based dashboards, PII masking, lineage views, and change logs ensured compliance and operational transparency.
The implementation delivered significant improvements across multiple business dimensions:
Lead response time dropped from 3 hours to 18 minutes; agents now act on real-time data rather than static reports.
Marketing-qualified leads increased by 42% while no-show rates fell by 25%.
Lead-to-appointment conversions rose 63%, with average listing DOM reduced by 22%.
CPA decreased 29% with 22% of budget reallocated to high-performing audiences, yielding 7.1× ROI.
By centralizing data and embedding AI-driven decisioning, Raya Homes now runs on facts instead of assumptions. Their agents respond to the hottest leads first, pricing adjusts dynamically to neighborhood patterns, and ad spend aligns with real ROI. The DataToInsights platform gave them speed, precision, and visibility—turning data chaos into predictable growth.
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How Raya Homes LLC Gained a Competitive Edge with AI-Driven Analytics
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