Real Estate Research Topic

Local Market Intelligence Scout

Researches a single residential real estate market each run — pulling active inventory, median sale price, days on market, list-to-sale ratio, new listings, and months of supply from public portals; layering buyer/seller sentiment from Reddit; and reconciling against historical snapshots stored in the agent's database. Synthesizes findings into a confident, data-driven briefing, writes it to a Google Doc, logs the run, and emails a recipient with a scannable summary plus the doc link.

97 template uses · 165 catalog views

Agent snapshot

Built for real estate work, not a generic template.

97

template uses

165

catalog views

4

integrations used

2

labels matched

Real Estate Research Topic

Sample input

Build an agent to local Market Intelligence Scout. Use Gmail, Follow Up Boss, Realtor, and Notion. Focus on research topic. Return a ready-to-review result after each run.

Sample output

Every Monday morning, scrapes MLS portals, Reddit, and web sources for your market, compares against the prior 30 days of snapshots, and emails a structured briefing with a linked Google Doc.

Workflow brief

Where Local Market Intelligence Scout fits in a real estate automation system

Local Market Intelligence Scout is designed for a specific recurring job: researches a single residential real estate market each run — pulling active inventory, median sale price, days on market, list-to-sale ratio, new listings, and months of supply from public portals; layering buyer/seller sentiment from Reddit; and reconciling against historical snapshots stored in the agent's database. Synthesizes findings into a confident, data-driven briefing, writes it to a Google Doc, logs the run, and emails a recipient with a scannable summary plus the doc link. The agent page keeps the workflow concrete by showing the connected apps, the input a team can give Twin, and the output the run is expected to produce.

A team can start from this public template, adjust the instructions, connect the relevant accounts, and schedule the agent once the review path is clear. That makes it useful for repeatable work where the same research, update, summary, or follow-up needs to happen again.

In this setup Twin uses Gmail, Follow Up Boss, Realtor, and Notion as source systems, action targets, or reporting destinations. The agent can combine those tools with browser automation and API calls when the workflow crosses systems.

What this agent automates

This run includes 6 concrete steps from the published agent data.

Signal 1 · 1

Load the last five market snapshots and the covered-topics list from the agent database

Signal 2 · 2

Scrape Realtor.com or equivalent portals for inventory, median price, DOM, list-to-sale ratio, new listings, and months of supply

Signal 3 · 3

Pull Reddit threads for the metro and adjacent communities, then fall back to Web Search if the scrape returns zero results

Signal 4 · 4

Run targeted Web Search queries for the freshest official MLS/board statistics for the current month

Signal 5 · 5

Synthesize all signals with Twin AI in the requested brand voice and write a structured briefing to Google Docs

Signal 6 · 6

Email the recipient a scannable HTML summary plus the doc link, then insert the new snapshot and report log rows

Integrations used

Local Market Intelligence Scout connects Gmail, Follow Up Boss, Realtor, and Notion.

Gmail

Connected in this agent

Follow Up Boss

Connected in this agent

Realtor

Connected in this agent

Notion

Connected in this agent

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Clone Local Market Intelligence Scout

Start from the exact agent behind this page, then adapt the prompt, apps, and review steps to your real estate workflow.

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Plans start at €20/mo

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