MLS Integration

Overview

Multiple Listing Services (MLS) contain critical real estate data—listings, sales, prices, days on market—but this data is often locked inside MLS portals with limited export options. Scoop can import your MLS data to enable AI-powered market analysis, historical tracking, and blending with marketing spend to understand true ROI.

What You Can Analyze

Data Type	Example Questions
Market Trends	"How have prices in this zip code changed?"
Inventory	"What's the current months-of-supply by area?"
Performance	"Average days-on-market by listing agent?"
Pricing	"List-to-sale price ratio by neighborhood?"
Marketing ROI	"Revenue generated per $1,000 marketing spend?"
Competition	"Market share by brokerage this quarter?"

Importing MLS Data

Option 1: Scoop Bot (Recommended)

The Scoop bot can automatically extract data from many MLS systems:

Contact Scoop support to configure MLS integration
Provide your MLS login credentials
Specify which reports/data to extract
Set your sync frequency (daily recommended)

Option 2: Manual Export

Most MLS systems allow some form of data export:

Log into your MLS portal
Run your desired search or report
Export to CSV or Excel
Upload to Scoop as a new dataset

Option 3: Email Report Forwarding

If your MLS emails reports:

Forward MLS report emails to your Scoop ingest address
Scoop automatically processes attachments
Data appears in your workspace

See Email Automated Imports for setup.

Key Data to Import

Active Listings

Current inventory:

Property address and details
List price and original list price
Days on market
Listing agent and brokerage
Property features

Sold/Closed Listings

Historical transactions:

Sale price and date
Days on market to close
List-to-sale ratio
Buyer's agent and seller's agent
Concessions and terms

Pending/Under Contract

Pipeline visibility:

Properties under contract
Pending sale price
Expected close date

Expired/Withdrawn

Market feedback:

Why listings didn't sell
Price vs. expired inventory
Seasonal patterns

Snapshotting MLS Data

MLS data changes daily. Scoop's snapshot feature is essential for:

Track Market Trends

Daily inventory snapshots
Price change tracking
Days-on-market evolution

Historical Analysis

Compare current market to 6 months ago
Identify seasonal patterns
Track market cycles

Competitive Intelligence

Monitor competitor listings
Track market share changes
Agent/brokerage performance trends

See Snapshot Datasets for setup.

Blending with Other Data

Source	Analysis Enabled
Marketing Spend	ROI by campaign, channel, or property
Google Analytics	Website traffic to listing views
CRM (Salesforce)	Lead-to-close conversion
Transaction Management	Full deal pipeline
Advertising	Cost per lead by property type

Example: Marketing ROI Analysis

Ask Scoop:
"Show revenue generated from closed deals
versus marketing spend by zip code this quarter"

Best Practices

Daily Snapshots

MLS data changes constantly:

New listings appear
Prices change
Status updates occur
Properties close

Daily snapshots capture this movement for trend analysis.

Include All Statuses

Don't just track active listings:

Active (current inventory)
Pending (pipeline)
Sold (performance measurement)
Expired/Withdrawn (market feedback)

Standardize Geography

Ensure consistent geographic coding:

Zip code or postal code
City/municipality
County
Custom market areas

Track Agent Data

Include agent/brokerage fields for:

Market share analysis
Performance benchmarking
Competitive intelligence

Common Use Cases

Market Analysis

Understand market conditions:

"What's the average list-to-sale ratio by price tier in my market?"

Inventory Tracking

Monitor supply trends:

"Show months-of-supply trend over the past 12 months"

Agent Performance

Benchmark productivity:

"Average sales volume per agent by brokerage"

Pricing Strategy

Inform pricing decisions:

"What's the optimal list price for a 3BR in this zip code based on recent sales?"

Marketing Attribution

Connect spend to results:

"Which marketing channels produced the highest-value closed deals?"

Seasonal Analysis

Plan for market cycles:

"Compare inventory levels and prices: spring vs. fall markets"

MLS-Specific Metrics

Metric	What It Shows
DOM (Days on Market)	Time from list to contract
CDOM (Cumulative DOM)	Total time including relists
List-to-Sale Ratio	Pricing accuracy
Months of Supply	Market balance (buyer's vs. seller's)
Absorption Rate	How fast inventory sells
Price per Sq Ft	Normalized pricing

Troubleshooting

Can't Export from MLS

Check your MLS membership level/permissions
Some MLS systems restrict bulk exports
Contact Scoop for bot-based extraction options

Data Quality Issues

MLS data depends on agent input accuracy
Verify key fields (price, DOM, status) are populated
Some fields may be optional in your MLS

Historical Data Limited

Most MLS systems purge old data
Start snapshotting now to build history
Some MLS vendors offer historical data products

Geographic Mismatches

MLS areas may not match other data sources
Standardize on zip code when possible
Create mapping tables for custom areas

Related Resources

Snapshot Datasets - Track changes over time
Blending Datasets - Combine with marketing data
Email Automated Imports
Google Analytics Integration - Website traffic analysis