Malika Gibbs
Senior Analytics & Pricing Strategy Leader
[email protected] | linkedin.com/in/gibbsma
CASE STUDY 03

Integrated Analytics System: Automating Market Intelligence & Pricing Operations

80%
Reduction in Manual Work
62%
Faster Decision Speed
96%+
Data Accuracy Rate
28
Active Users Across Teams

Project Context

A growing real estate development firm was managing market intelligence and pricing analysis across multiple South Florida projects using disconnected spreadsheets and manual processes. Weekly reporting consumed 18-22 hours of analyst time, with data inconsistencies creating confusion in leadership meetings and delaying critical pricing decisions.

Challenge

The analytics team was spending the majority of their time on data collection and formatting rather than analysis and strategy. Five separate data sources (MLS, CoStar, internal CRM, market reports, sales tracking) required manual reconciliation each week. Data accuracy issues led to mistrust in reports, with executives frequently questioning numbers rather than focusing on strategic implications. Decision cycles averaged 5+ days as teams waited for custom analyses.

Solution Architecture

Before: Manual Process (18-22 hours/week)
Pull Data from 5 Sources
Clean & Standardize
Manual Calculations
Format for Presentation
Update Reports
Email Stakeholders
After: Automated System (3-4 hours/week)
Automated Data Pull
Live Dashboard
Self-Service Access
80% Time Savings
Data Sources
MLS Data
CoStar API
Internal CRM
Market Reports
Sales Tracking
Processing
Automated ETL Pipeline
Data Cleaning • Standardization • Enrichment
Storage
Centralized Data Warehouse
Outputs
Tableau Dashboard
Pricing Calculator
Weekly Reports

Implementation Approach

Measured Impact

Weekly Time Investment
Data Collection
8h
1h
Analysis
6h
1.5h
Reporting
4h
0.5h
Distribution
2h
0.5h
Decision Speed Improvement
62%
Faster Decisions

Average time-to-decision dropped from 5+ days to under 2 days

Data Accuracy
98%
Price Data
97%
Inventory
96%
Absorption
99%
PPSF Calcs

All metrics exceed 95% target threshold

User Adoption
28
Active Users

Across sales, development, finance, and executive teams within 3 months

Business Impact

Operational Efficiency Reduced weekly manual work by 80% (from 18-22 hours to 3-4 hours), allowing analytics team to focus on strategic analysis and business partnership
Decision Velocity Accelerated decision-making by 62%, with average time-to-decision dropping from 5+ days to under 2 days through self-service access to data
Data Quality & Trust Improved data accuracy to 96%+ across all metrics, eliminating skepticism in leadership meetings and building confidence in analytics
Broad Adoption System reached 28 active users across sales, development, finance, and executive teams within 3 months of launch
Scalability Framework enabled expansion to additional markets and projects without proportional increase in analyst workload

Key Deliverables

Key Insight: The system's success wasn't just technical—it was about understanding user workflows and designing outputs that fit naturally into existing decision processes. By focusing on adoption alongside functionality, the system achieved 80%+ engagement within the first quarter.

Technical Stack

Tools & Technologies:
Python Pandas SQLAlchemy PostgreSQL Tableau Excel / VBA Git REST APIs Task Scheduler
Malika Gibbs | Senior Analytics & Pricing Strategy Leader
hello@malikaasgibbs.com | linkedin.com/in/gibbsma
© 2025 Malika Gibbs. Confidential - For Review Purposes Only
No real client data was used in this case study.