When someone puts their home up for sale, they're about to move. Pre-mover data tells you which households have just taken that step — weeks before the move actually happens.
The simple version
Every week, thousands of Canadian homeowners list their properties for sale. Each listing is a public signal that the household behind it is preparing to relocate. Pre-mover data captures those signals, validates the addresses, and delivers them in a structured file that businesses can use.
That's it. Pre-mover data is a weekly list of households that are about to move, identified from the moment their home hits the market.
The reason it's valuable is timing. From the day a property lists to the day the household physically moves, there's typically a window of four to twelve weeks. Inside that window, the household is making decisions about everything tied to their address: internet, insurance, banking, utilities, home services, furniture, appliances. Every one of those decisions is a commercial opportunity — for the business that reaches them first.
Why it matters
Moving is one of the biggest spending events in a household's life. People changing addresses need new service providers, new insurance policies, new utility connections, and new everything-else for the new home. Canadian research consistently puts the average household spend during a move at several thousand dollars — on top of the property transaction itself.
For businesses, there are two sides to this:
If a household is your existing customer and they're about to move, you're about to lose them — unless you know about the move early enough to intervene. A telecom provider can offer a smooth service transfer. A bank can proactively discuss the next mortgage. An insurer can quote a new policy at the destination address. All of these work, but only if the outreach happens before the customer finds a replacement on their own.
If a household isn't your customer but they're about to move into your service area, they're looking for new providers right now. The first business to reach them during the move window has a structural advantage. Not because of a better price or a better product — just because they got there first, at the exact moment the household was making the decision.
How it's different from new-mover data
This is the most common source of confusion in the category, so it's worth being clear about it.
Pre-mover data identifies households before the move, from the listing event. The household's property has just entered the market. The move hasn't happened yet. You have weeks to act.
New-mover data identifies households after the move, from change-of-address records, utility hookups, and similar post-move filings. The household has already relocated. The address-bound decisions have largely been made.
The gap between the two is roughly eight to sixteen weeks — and for most business purposes, that gap is the entire campaign. If you're trying to retain a customer, pre-mover data gives you time to intervene. New-mover data tells you the customer has already left. If you're trying to acquire a customer, pre-mover data lets you be the first offer they see. New-mover data puts you in line behind whoever got there earlier.
Both kinds of data are useful. They solve different problems. Pre-mover data is for businesses that want to act before the move. New-mover data is for businesses that are comfortable acting after.
Who uses it
Pre-mover data shows up in nearly every industry where the customer relationship is tied to a residential address. The specific application changes, but the underlying logic is always the same: know about the move early, act inside the window.
Telecoms and internet providers use it to retain subscribers who are about to disconnect and acquire new subscribers at addresses entering the market. The move event is the single biggest driver of subscriber churn.
Banks and mortgage lenders use it to spot upcoming mortgage discharges, identify new origination opportunities, and retain borrowers by proactively offering financing for the next property.
Insurers use it to quote new policies before policyholders start shopping at the new address. Also for portfolio monitoring — a listed property signals a change in risk profile.
Home services, moving companies, and retailers use it for acquisition — reaching households during the high-spend window around a move, when they're buying furniture, appliances, cleaning services, landscaping, and home improvement.
Direct marketing teams use it as a trigger-based targeting layer on top of their existing campaigns. A household that is actively moving responds at a materially higher rate than a household that isn't.
What's actually in the data
A pre-mover record is a property-level record. It describes the property and the listing event — not the person living there. A typical record includes:
Standardized address and postal code. Listing date. Listing status (active, price changed, sold, expired, withdrawn). Property type (detached, semi, condo, townhouse). Asking price and price history. Bedrooms, bathrooms, square footage. Geocoded latitude and longitude. Days on market.
What it does not include: names, phone numbers, email addresses, or demographic information. The data is about the property and the market event. The customer identification happens when the business matches the file against their own records on address — inside their own systems, under their own privacy framework.
How it's delivered
Three ways, depending on what fits the business's existing infrastructure:
Snowflake Marketplace — a live data share inside the business's own Snowflake environment. No file transfers, no ETL. The data appears as a table that can be joined directly to the business's CRM or subscriber database with SQL.
MCP connector — an AI-native access point. AI agents (Claude, ChatGPT, custom agents) can query the pre-mover data directly inside a conversation or an automated workflow. Useful for teams building AI-driven retention and acquisition systems.
Flat file — a weekly CSV or Parquet file delivered to the business's existing data infrastructure. The traditional shape, compatible with any CRM, campaign platform, or direct-mail system.
All three deliver the same underlying data. The choice is operational — it depends on what the business's team already uses.
Common questions
A weekly record of households that are about to move, identified from the moment their property is listed for sale. It gives businesses a 4–12 week head start to reach those households before the move happens.
Pre-mover data flags households before the move, from the listing event. New-mover data flags households after the move, from change-of-address records. Pre-mover gives you weeks of advance notice. New-mover arrives after most buying decisions have already been made.
No. Pre-mover data is property-level: address, postal code, listing date, property type, price. No names, phone numbers, or emails. The business matches the data against their own customer records on address.
Weekly. A new file every week reflecting the latest listings, price changes, and sold events across all 10 Canadian provinces.
Banks, telecoms, insurers, utilities, moving companies, home services providers, retailers, and direct marketing teams. Any business whose customer relationship is tied to a residential address.
No. A list of houses for sale is a snapshot. Pre-mover data is a continuously maintained, address-validated, deduplicated weekly record of households transitioning through the move lifecycle — listed, relisted, price-changed, sold, expired. It's structured for CRM matching, not property browsing.
This page is the overview. For pipeline architecture, delivery specifications, privacy posture, and vendor evaluation criteria, read the technical guide.