The Wise Coyote Method
Why the Coyote?
Coyotes thrive in both the suburbs of DFW, the mountains of Colorado and the desert valleys of Arizona—not through force, but through intimate territorial knowledge, patient pattern observation, and strategic adaptability. They study their terrain, recognize behavioral patterns in their environment, and adjust their approach based on changing conditions. This is how effective market analysis works.
Most real estate agents operate on anecdote and intuition. They'll tell you "the market is hot" based on their last closing or cite city-wide statistics that obscure critical neighborhood-level dynamics. The Wise Coyote Method replaces guesswork with systematic analysis—layering historical depth, micro-market segmentation, and rigorous data interpretation to provide clients with actionable intelligence rather than hopeful projections.
Executive Summary
The Wise Coyote Method is a framework for real estate market analysis built on three foundational pillars:
Territorial Intelligence – Understanding that markets operate at the micro-level, not through city-wide averages
Pattern Observation – Adding temporal depth to inherently flat MLS data through historical context and weekly tracking
Adaptive Strategy – Validating intuition with data while recognizing that individual transactions require both quantitative rigor and qualitative judgment
This methodology is operationalized through proprietary Power BI systems processing daily MLS updates across a 10+ year longitudinal database—enabling identification of market inflection points 60–90 days before they appear in traditional lagging indicators. It draws on analytical frameworks from graduate business education (Cornell MBA), systematic execution principles from military leadership (U.S. Army Captain), and strategic problem-solving approaches from management consulting (Deloitte Strategy & Operations).
The result is a portable, repeatable system for understanding real estate markets regardless of geography—the methodology applies to any market where micro-level dynamics drive outcomes.
Weather vs. Terrain: Macro Trends and Micro-Market Structure
A core distinction in the Wise Coyote Method is between weather and terrain.
Weather represents macro conditions that affect all markets:
Interest rate environments
National economic trends
Demographic migration patterns
Lending policy changes
Terrain represents the structural characteristics of individual micro-markets:
School district quality and reputation
Lot sizes and housing stock characteristics
Proximity to employment centers and amenities
Community prestige and HOA governance
Rising interest rates are "weather"—they impact every market. But two neighborhoods don't experience that weather the same way. Premium areas with superior terrain (top schools, larger lots, established prestige, limited supply) typically weather economic storms better than those without structural advantages.
Most real estate commentary focuses exclusively on weather: "Rates are up, so the market is slowing." The Wise Coyote Method recognizes that terrain determines how each micro-market experiences macro conditions. Understanding your specific terrain matters more than tracking weather patterns everyone already sees.
Pillar 1: Territorial Intelligence
While weather affects all markets, terrain determines outcomes
Real estate operates at the neighborhood level, not the city level. Reporting that "Plano's median price rose 5%" obscures the reality that some ZIP codes appreciated 8% while others declined 2%. Some neighborhoods lead market trends; others lag. Some insulate against downturns; others amplify volatility.
Core practices:
Track performance at ZIP code and neighborhood/subdivision levels, not city-wide aggregates
Identify "bellwether communities" that signal broader market shifts before they become obvious
Map supply/demand imbalances at micro-market scale (where inventory shortages are most acute)
Understand structural characteristics that drive premium resilience (school ratings, lot sizes, HOA quality, proximity to employment centers)
Illustrative example: When interest rates rose sharply in 2022, all markets experienced the same "weather"—but neighborhoods with superior "terrain" (top-rated schools, established prestige, limited supply) maintained buyer activity while areas without structural advantages saw inventory accumulate. The macro trend affected everyone; the micro-market structure determined outcomes.
Why this matters: My experience at Deloitte reinforced that strategy work never analyzes "the industry"—we dissected specific positions within market structures. The same discipline applies here. Clients don't buy "the Plano market." They buy a specific property in a specific neighborhood with specific structural attributes. Analysis must match that granularity.
Pillar 2: Pattern Observation
MLS data is inherently flat—adding temporal depth reveals trajectory, not just position
Most agents work with snapshots: last month's closings, this quarter's inventory. The Wise Coyote Method adds dimensionality through historical context, weekly granularity, and leading indicators.
Core practices:
Maintain 10+ years of transaction history (not just "last quarter")
Track trends on a weekly basis to catch inflection points early (monthly data smooths away critical signals)
Analyze time-decay effects (how Days on Market correlates to negotiability and final price)
Monitor leading vs. lagging indicators (active inventory shifts predict price movements 60-90 days forward)
Illustrative example: In spring 2024, weekly inventory tracking revealed a 22% increase in new listings over a three-week period in the $800K-$1.2M segment—well before monthly aggregates showed the shift. This early signal allowed buyers to adjust offer strategies and sellers to recalibrate pricing expectations before the market "officially" turned.
Why this matters: During my service as a U.S. Army Logistics Officer, I worked as a transportation planner tracking major unit deployments using "glide path" analysis—visualizing progress over time rather than relying on static snapshots. That experience fundamentally shaped how I approach market data: understanding trajectory requires plotting movement across time, not freezing a single moment. A 45-day DOM figure means nothing without knowing whether it was 30 days last month and 60 days last year. Context creates meaning.
Pillar 3: Adaptive Strategy
Data informs intuition, not the other way around
Real estate will always involve human judgment—helping a client choose between two comparable homes requires understanding their lifestyle, priorities, and emotional resonance with a property. But market-level analysis cannot rely on anecdote or gut feeling. The Wise Coyote Method validates intuition with data while recognizing the limits of pure quantification.
Core practices:
Distinguish between individual transactions (often noise) and market trends (signal)
Combine quantitative analysis (pricing, DOM, inventory levels) with qualitative factors (school ratings, development plans, community character)
Apply pattern recognition developed through experience—but verify patterns with data
Reject the "my last buyer paid $X" fallacy (single data points don't constitute market analysis)
Illustrative example: An agent might say "homes are selling over list price" based on their last three closings. The data might reveal that 68% of sales in that price range closed below list price, and the agent's experience represented statistical outliers (likely multiple-offer scenarios on underpriced listings). Individual experience is not market truth.
Why this matters: Strategic thinking—whether developed through business school frameworks or military decision-making processes—requires hypothesis testing. You develop informed perspectives, but you validate them against evidence. Intuition has a role in pattern recognition, especially after a decade of market observation, but it must remain tethered to verifiable data. Otherwise, it's just confirmation bias with a real estate license.
Application: How This Methodology Informs Client Work
For Buyers:
Identify neighborhoods trending upward before they peak (territorial intelligence)
Spot overpriced listings by comparing current DOM and price drops to historical norms (pattern observation)
Time purchases to seasonal inventory patterns and micro-market supply shifts (adaptive strategy)
For Sellers:
Price strategically based on ZIP-code-specific trends, not city-wide averages (territorial intelligence)
Understand realistic timelines using your neighborhood's actual DOM, not Plano-wide statistics (pattern observation)
Decide when to list based on inventory cycle analysis and competitive positioning (adaptive strategy)
For Investors:
Analyze multi-year appreciation trends at the micro-market level (territorial intelligence + pattern observation)
Assess rental yield performance against historical norms and demographic shifts (adaptive strategy)
Time acquisitions and dispositions based on leading indicators, not reactive sentiment (pattern observation)
Verification & Transparency
All analysis produced through the Wise Coyote Method is sourced from North Texas Real Estate Information Systems (NTREIS) MLS data and is verifiable by any licensed agent with MLS access. I don't manipulate datasets to show favorable trends—if a market softens, my reports reflect it.
For clients considering major transactions, I provide custom analyses filtered by specific neighborhoods, price ranges, property characteristics, and historical comparable sales. The goal is not to "prove" a predetermined conclusion but to provide the clearest possible picture of market reality so clients can make informed decisions.
Where This Analysis Is Published
The Wise Coyote Method is applied across multiple formats:
Plano Market Data Archive – 10+ years of historical data, updated weekly
Market Intelligence Blog – Weekly updates and monthly deep-dives
Neighborhood Market Pages – Hyperlocal analysis for West Plano communities
Private Client Reports – Custom analysis for active buyers/sellers → Request Analysis
About the Author
Matt Haistings is a Real Estate Market Analyst and Broker Associate with Compass Real Estate specializing in the Dallas-Fort Worth luxury market. He holds an MBA from Cornell University's SC Johnson College of Business, served as a Captain in the U.S. Army, and worked as a Strategy & Operations consultant at Deloitte before transitioning to real estate. He has maintained proprietary Power BI market analysis systems tracking North Texas residential sales for over a decade.
Next Steps
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