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Building CMAs with the Repliers API: Complete Implementation Guide

Introduction

This guide walks you through building a Comparative Market Analysis (CMA) tool using the Repliers API. CMAs are essential for real estate professionals to help clients understand property values and market conditions. By the end of this guide, you'll have a complete understanding of how to create professional, data-driven CMAs.

What Makes a Good CMA?

A comprehensive CMA should include the following components:

1. Estimated Property Value

Current estimated value with high-low range
Historical value trends (typically 24 months)
Confidence indicator to set proper expectations

2. Sold Comparables

Recent nearby properties that have sold (typically within 90 days)
Ability to exclude irrelevant comparables from the report

3. Active Listings

Nearby properties currently for sale
Ability to exclude listings as needed

4. Market Statistics

Median/average sold prices over time
Days on market trends
Month-over-month analysis to identify market direction

Implementation Guide

Step 1: Collect Property Address

Start by prompting the user to input the subject property's address. You'll need to collect:

Street number
Street name
Postal/ZIP code

Example address: 30 South Belair Dr, Vaughan, L4H2R5

Step 2: Check for MLS History

Before asking users to manually enter property details, check if the property has MLS history. This saves time and ensures accuracy.

Endpoint: GET https://api.repliers.io/listings

Example Request:

GET https://api.repliers.io/listings?streetNumber=30&streetName=South%20Belair&zip=L4H2R5&status=U&status=A&fields=details.propertyType,details.style,details.numBedrooms,details.numBathrooms,details.basement1,details.numGarageSpaces,lot.depth,lot.width,condominium.fees.maintenance,taxes.annualAmount,details.sqft,details.yearBuilt,address,soldDate,map

Why these fields? These are the essential attributes needed to:

Request an estimate from Repliers
Find comparable listings
Display property information

Response When History Exists:

{
  "apiVersion": "1",
  "page": 1,
  "numPages": 1,
  "pageSize": 100,
  "count": 3,
  "statistics": {
    "listPrice": {
      "min": 419900,
      "max": 788800
    }
  },
  "listings": [
    {
      "soldDate": "2015-08-17T12:00:00.000Z",
      "address": {
        "area": "York",
        "city": "Vaughan",
        "streetName": "South Belair",
        "streetNumber": "30",
        "streetSuffix": "Dr",
        "zip": "L4H2R5",
        "state": "Ontario"
      },
      "details": {
        "basement1": "Unfinished",
        "numBathrooms": "3",
        "numBedrooms": "4",
        "numGarageSpaces": "2.0",
        "propertyType": "Detached",
        "style": "2-Storey"
      },
      "lot": {
        "depth": "111.58",
        "width": "38.98"
      },
      "taxes": {
        "annualAmount": "4929.26"
      }
    }
  ]
}

Response When No History Exists:

{
  "apiVersion": "1",
  "page": 1,
  "numPages": 0,
  "pageSize": 100,
  "count": 0,
  "statistics": {
    "listPrice": {
      "min": null,
      "max": null
    }
  },
  "listings": []
}

UX Best Practices:

1. Select the Most Recent Listing

When multiple listings are returned, use the one with the most recent soldDate as it likely has the most accurate and up-to-date property attributes.

2. Display Editable Property Details

Show the property attributes in a form that allows users to update values. For example:

Property taxes may have increased since the last transaction
Renovations may have changed bathrooms, square footage, or quality
Basement finishing status may have changed

3. Handle Missing History Gracefully

If no history exists (count: 0), prompt the user to manually enter property details.

Step 3: Generate Property Estimate

Once property details are confirmed, request an estimate from Repliers.

Prerequisites: Your account needs access to the Repliers estimates add-on. See the AI-Powered Property Estimates Guide for more information.

Endpoint: POST https://api.repliers.io/estimates

Request Body Structure:

The request body mirrors the listing object structure from the history response:

{
  "overallQuality": "average",
  "address": {
    "area": "York",
    "city": "Vaughan",
    "district": "Vaughan",
    "streetName": "South Belair",
    "streetNumber": "30",
    "streetSuffix": "Dr",
    "zip": "L4H2R5",
    "state": "Ontario"
  },
  "map": {
    "latitude": "43.824520",
    "longitude": "-79.621904",
    "point": "POINT (-79.621904 43.824520)"
  },
  "details": {
    "basement1": "Unfinished",
    "numBathrooms": "3",
    "numBedrooms": "4",
    "numGarageSpaces": "2.0",
    "propertyType": "Detached",
    "style": "2-Storey"
  },
  "lot": {
    "depth": "111.58",
    "width": "38.98"
  },
  "taxes": {
    "annualAmount": "4929.26"
  }
}

Note: Don't worry about including extra fields—they'll simply be ignored if not needed for the estimate.

Understanding `overallQuality`

The overallQuality field defines the property's renovation quality:

poor: Significant deferred maintenance or dated finishes
below average: Functional but dated or basic finishes
average (default): Standard finishes typical for the area
above average: Recently renovated with high-end finishes
excellent: Magazine-quality finishes with premium materials

This field also affects comparable searches (explained later).

Response:

{
  "estimateId": 123,
  "estimate": 508597.59,
  "estimateHigh": 577311.20,
  "estimateLow": 439883.98,
  "confidence": 0.135,
  "history": {
    "mth": {
      "2024-12": { "value": 508597.59 },
      "2024-11": { "value": 508491.09 },
      "2024-10": { "value": 511354.31 },
      "2023-01": { "value": 484527.66 }
    }
  }
}

Key Response Fields:

estimate: Current property value
estimateHigh / estimateLow: Value range
confidence: Confidence score (lower = more confident)
history: 24 months of historical values for trend visualization

Step 4: Find Sold Comparables

Display recently sold properties with similar characteristics to support the estimate.

Recommended Criteria:

Sold within the past 90 days
Similar property attributes (type, bedrooms, bathrooms)
Sold within the estimate range
Within a reasonable radius (5km is a good starting point)

Endpoint: GET https://api.repliers.io/listings

Example Request:

GET https://api.repliers.io/listings?status=U&lastStatus=Sld&lat=43.824520&long=-79.621904&radius=5&minSoldDate=2025-11-07&maxSoldDate=2026-02-08&fields=imageInsights.summary.quality.qualitative.overall,mlsNumber,soldDate,soldPrice,details.numBedrooms,images[0],details.numBathrooms,details.propertyType,details.style&propertyType=Detached&minBedrooms=4&minBathrooms=4&minSoldPrice=1300000&maxSoldPrice=1600000&type=sale

Query Parameter Breakdown:

status=U&lastStatus=Sld: Unavailable listings that sold
lat & long: Subject property coordinates
radius=5: Search within 5km
minSoldDate & maxSoldDate: Date range (90 days)
propertyType, minBedrooms, minBathrooms: Match subject property
minSoldPrice & maxSoldPrice: Within estimate range
fields: Specific data to return (including quality rating)

Response:

{
  "count": 14,
  "listings": [
    {
      "mlsNumber": "N12703668",
      "soldPrice": "1448000.00",
      "soldDate": "2026-01-30T00:00:00.000Z",
      "details": {
        "numBathrooms": "3",
        "numBedrooms": "4",
        "propertyType": "Detached",
        "style": "2-Storey"
      },
      "imageInsights": {
        "summary": {
          "quality": {
            "qualitative": {
              "overall": "average"
            }
          }
        }
      },
      "images": ["IMG-N12703668_1.jpg"]
    }
  ]
}

UX Best Practices:

1. Provide Filter Controls

Allow users to refine comparable criteria:

☐ Same property type
☐ Same style
☐ Same bedrooms
☐ Same bathrooms

This flexibility helps when there are too many or too few comparables.

2. Adjustable Time Frames

30 days if the market is very active
90 days (recommended default)
120+ days if inventory is limited

3. Display Quality Ratings

Group comparables by quality (excellent, above average, average) to help users understand value differences.

4. Show Property Images

Display the first image to give visual context.

Step 5: Find Active Listings

Show currently available properties for reference.

Endpoint: Same as sold comparables, but change status parameters

Example Request:

GET https://api.repliers.io/listings?status=A&lastStatus=New&lat=43.824520&long=-79.621904&radius=5&fields=mlsNumber,listPrice,details.numBedrooms,images[0],details.numBathrooms,details.propertyType,details.style&propertyType=Detached&minBedrooms=4&type=sale

Key Difference: status=A&lastStatus=New returns active listings instead of sold ones.

Step 6: Allow Exclusions

Real estate professionals often need to exclude listings that aren't truly comparable.

Excluding a Listing:

Add mlsNumber=not: followed by the MLS number to exclude:

&mlsNumber=not:N12703668

Multiple Exclusions:

Chain exclusions with additional mlsNumber=not: parameters:

&mlsNumber=not:N12703668&mlsNumber=not:N12640284

UX Best Practices:

1. Easy Removal

Add a "Remove from report" button/link on each comparable

2. Undo Capability

Allow users to re-include accidentally excluded listings with an "Include in report" option

3. Visual Indication

Clearly show which listings have been excluded (e.g., grayed out with a "Excluded" badge)

Step 7: Display Market Statistics

Show market trends to provide context for the estimate.

Endpoint: GET https://api.repliers.io/listings

Example Request:

GET https://api.repliers.io/listings?status=U&lastStatus=Sld&lat=43.824520&long=-79.621904&radius=5&minSoldDate=2024-02-07&propertyType=Detached&minBedrooms=4&minBathrooms=4&type=sale&listings=false&statistics=grp-mth,med-soldPrice,avg-daysOnMarket

Key Parameters:

listings=false: Speeds up request by skipping listing data (we only need statistics)
statistics=grp-mth,med-soldPrice,avg-daysOnMarket:
Group by month
Calculate median sold price
Calculate average days on market
minSoldDate=2024-02-07: Go back 24 months

Response:

{
  "count": 910,
  "statistics": {
    "soldPrice": {
      "med": 1629444,
      "mth": {
        "2024-02": { "med": 1640000, "count": 40 },
        "2024-03": { "med": 1739000, "count": 56 },
        "2025-12": { "med": 1800000, "count": 21 },
        "2026-01": { "med": 1466500, "count": 20 }
      }
    },
    "daysOnMarket": {
      "avg": 29,
      "mth": {
        "2024-02": { "avg": 23, "count": 40 },
        "2024-03": { "avg": 19, "count": 56 },
        "2026-01": { "avg": 44, "count": 20 }
      }
    }
  }
}

Visualizing Market Trends:

Use this data with charting libraries (Chart.js, Recharts, D3.js, etc.) to create:

1. Median Price Trend Chart

Shows whether the market is appreciating or depreciating

2. Days on Market Trend

Indicates market speed (seller's vs buyer's market)

3. Transaction Volume

The count field shows market activity levels

Advanced Features

Using Quality Filters for Better Comparables

When searching for comparables, you can filter by quality to match the subject property:

&overallQuality=above average

This helps ensure you're comparing properties with similar renovation levels.

Additional Statistics Available

Repliers supports dozens of statistics beyond median price and days on market. Refer to the Real-Time Market Statistics Guide for complete options.

Finding Comparables by Address

For a deeper dive into comparable searches, see the Finding Comparables by Address Guide.

Complete Workflow Summary

Collect Address → User inputs street number, name, and postal code
Check History → GET /listings to find previous transactions
Confirm Details → Display property attributes in editable form
Generate Estimate → POST /estimates with property details
Find Sold Comps → GET /listings with sold status and filters
Find Active Listings → GET /listings with active status
Allow Exclusions → Support removing irrelevant listings
Show Statistics → GET /listings with statistics parameters
Visualize Data → Create charts and present the complete CMA

Best Practices for Production

Performance Optimization

Cache property history to avoid redundant API calls
Use listings=false when only statistics are needed
Request only necessary fields to reduce payload size

Error Handling

Handle cases where no history exists
Manage empty comparable searches gracefully
Validate address inputs before API calls

User Experience

Show loading states during API calls
Provide clear feedback when no comparables are found
Allow refinement of search criteria
Enable comparison exclusion and restoration

Data Presentation

Display confidence levels clearly
Show historical value trends visually
Group comparables by quality or date
Highlight key statistics with visual indicators

Getting Started

To start building CMAs with the Repliers API:

Ensure your account has the Estimates add-on enabled
Review the Estimates Implementation Guide
Implement the workflow outlined in this guide
Test with various property types and markets

For additional support, refer to Repliers documentation or contact their support team.

Updated on: 17/02/2026

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Building CMAs with the Repliers API: Complete Implementation Guide

Introduction

What Makes a Good CMA?

1. Estimated Property Value

2. Sold Comparables

3. Active Listings

4. Market Statistics

Implementation Guide

Step 1: Collect Property Address

Step 2: Check for MLS History

Response When History Exists:

Response When No History Exists:

UX Best Practices:

Step 3: Generate Property Estimate

Understanding overallQuality

Response:

Key Response Fields:

Step 4: Find Sold Comparables

Query Parameter Breakdown:

Response:

UX Best Practices:

Step 5: Find Active Listings

Step 6: Allow Exclusions

Excluding a Listing:

Multiple Exclusions:

UX Best Practices:

Step 7: Display Market Statistics

Key Parameters:

Response:

Visualizing Market Trends:

Advanced Features

Using Quality Filters for Better Comparables

Additional Statistics Available

Finding Comparables by Address

Complete Workflow Summary

Best Practices for Production

Performance Optimization

Error Handling

User Experience

Data Presentation

Getting Started

Understanding `overallQuality`