In my analysis of more than 20,000 expired listings in my local market (homes whose listing agreement ran out before they sold), the expired listings most likely to relist had price reductions, more than 120 days on market and a list price at or below the owner’s purchase price. I score every expired into a top 40%, middle 40% and bottom 20%, then work the list from the top down. Listing remarks, the free-text description an agent writes on the MLS, barely moved the needle in my data, including phrases like “motivated seller.”
Here is how I answer the questions that came up around this research, from a live webinar I gave on October 1, 2026. Every figure below comes from my analysis of my own market, so run the same exercise on yours before you lean on the numbers.
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My data shows a wide spread in relist odds across the expireds in my market. The habit I see most often is this one: “Oftentimes, we group expired listings as a whole.”
“Within expired listings, there are those that are more likely to relist, and there are those that are less likely to relist.”
To find that spread, I exported every listing that expired in my market over the last 12 months. My MLS limits exports, so I pulled the data in buckets. I threw out anything back on the market the next day, since those almost always relist with the same agent who already has a new contract.
Then I analyzed more than 40 data points across listing history, property, owner, agent and the listing remarks. When it comes to how many expired listings relist, my baseline after that cleanup was about 11 in 100 within 90 days with a new agent. As I told the room, “I was blown away at how wrong some of my gut feelings were.”
In my market analysis, the expired listings most likely to relist came down to four factors: price reductions, days on market, the original purchase price, and who listed the property and when it expired. The first three are all price history, and they did most of the work. Here is what each one did in my data:
I found that expireds with a price reduction during the listing were 64% more likely to relist. More reductions and a bigger gap between the starting price and the ending price pushed the likelihood higher.
Expireds that sat on the market more than four months were 129% more likely to relist than those under 60 days in my analysis. Listings under 60 days on market were significantly less likely to relist.
I saw owners who listed at or below what they originally paid come back 31% more often. The year they bought did not matter in my data.
Builder and land-agent listings were less likely to relist than a typical agent’s single-family listing. Listings that expired between September and November were less likely to relist than those that expired between January and April, and in my experience January 1 is historically the best day of the year for expired listings.
When I stacked these signals, I got “a 288% chance better to list a property when I’m prospecting to the right ones.” I treat this as an upgrade to my lead stack, the standing priority order I work my calls through, which already sorts by distance from me and price range.
No, and this was the biggest surprise in the data. Listing remarks are the free-text blurb an agent writes on the MLS listing, the part that reads “motivated seller, bring all offers, as-is.” Agents treat that language as a read on how badly the owner wants to sell, which is why I expected it to predict a relist: “I thought that would move the needle more.”
“If it said ‘motivated seller’ in the comments and remarks, it barely moved the needle.”
My conclusion was blunt: “Whatever the agent goes and puts into those remarks and comments hardly moved the needle at all.” Here is how the phrases sorted in my market:
I still believe the phone is the most time and cost-effective way to reach a lot of people quickly, and “I believe that expired listings are still the very best seller leads that there are.” Ten years ago 100 calls meant 26 to 40 people answering. Now it is somewhere between 4% and 9%.
Owners get 20, 30, maybe 50 calls the day a listing expires, and many stop answering by noon. When I asked the room who has time to make twice as many calls, the answer came back the way I expected: “We don’t have the time to make more calls.” So I sort the list first to prioritize expired listings, because “we want to make sure that we’re spending it on the leads that are most likely to convert.”
Whichever group you call first, REDX recommends that agents avoid dialing numbers on the Do Not Call list.
I built an AI prompt that scores an MLS export, and the steps fit any market:
My top 40% is the group most likely to relist within 90 days, and it gets most of my time and money. The middle 40% gets some dedicated resources. The bottom 20% gets very little attention.
“If a group has to be skipped altogether, this is the one that you skip.”
My market may look different from yours. My average single-family home is in the high $570,000s, and construction is booming here in Utah.
Weekly. My setup is a scheduled AI task that runs every Sunday or Monday morning on the last seven days of expireds, so the groups are ready when my prospecting block starts.
If you would rather not schedule a task, you can save an MLS search and export it each week. I suggest importing each group into your CRM, or into Vortex, the REDX contact record that remembers your last conversation, and dropping each one into its own folder: top 40, middle 40 and bottom 20. REDX Expired Leads are skip-traced against your MLS, meaning the homeowner’s contact details are matched to the expired property record for you, and they land in Vortex ready to file that way.
Want the prompt and the weekly automation? I share the scoring prompt and the rest of this system with agents inside Listing Academy.
An attendee asked me this live, and my answer was yes: “You could absolutely use this same method for determining and measuring the likelihood of a canceled listing relisting on the MLS.” My analysis was built for expireds, so you would adapt it.
That said, “I guarantee you on canceled listings, the data will be different.” Run the numbers on your own canceled listings before you trust any expired benchmark.
My goal is for the analysis to be done before you sit down, so your time goes to the expired listings most likely to relist. Start with this checklist:
The way I see it, “If we’re going to spend time or money getting in front of people, we want to spend it on the people that are most worth it.” A scored list can make mail, email and ad campaigns cheaper to run, and it gives your expired listing strategy a clear starting point.