Can Private Listings Really Boost Inventory by 6-12%? Zillow Says Not Likely

Last week, Zillow chief economist Mischa Fisher published a LinkedIn post pushing back on a recent report. 

The post focused on the claim that giving sellers the ability to test pricing through private or coming-soon listings could increase inventory by as much as 6%–12%. Fisher’s response was direct: the math behind that estimate “doesn’t hold up.”

While Fisher never names the source, it’s clearly a response to a recent Redfin report making that exact argument.

We’re breaking down Fisher’s response, including the specific claims he calls out and the gaps he sees in Redfin’s analysis. 

Redfin’s Report vs Fisher’s Analysis

Redfin’s report builds a clear narrative around phased marketing, and was published shortly after Compass announced a partnership with Redfin, in which Compass’s ‘Coming Soon’ and ‘Private Exclusive’ properties will appear exclusively on Redfin. 

The report, which includes a link to the methodology used, argues that giving sellers more flexibility upfront leads to better pricing decisions, which then unlocks more inventory. Fisher’s response focuses on how those claims are framed and supported.

Here are the core statements from Redfin’s report that come under scrutiny:

• Inventory could increase by 6%–12% in markets where phased marketing is widely used
• Sellers who test pricing early are more likely to list
• More accurate pricing reduces price cuts and time on market
• Phased marketing lowers the “barrier to entry” for hesitant sellers
• Increased seller confidence leads to more listings, which increases inventory
• Reduced pricing mistakes help homes sell closer to list price, with examples suggesting 2%–5% differences tied to price-drop stigma
• Overpricing by 10% or more can extend time on market by more than a month, reinforcing the need for early pricing feedback

Fisher’s critique focuses on how these ideas are presented. 

Several of these claims rely on modeled relationships between seller behavior and pricing outcomes. The report connects those relationships to a projected inventory increase, even though the underlying inputs are not drawn from observed phased marketing outcomes.

In other words, there’s no hard data to back them up. 

In addition, Redfin uses and cites Zillow research in its references to support the argument. The report leans on the idea that pricing uncertainty is a primary reason sellers hesitate. 

Fisher noted that goes against Zillow’s own framing of seller behavior. He states that Zillow’s survey data points to a broader mix of factors, including affordability concerns and life uncertainty. Realistically, pricing tools alone have a more limited influence on inventory than Redfin’s report suggests. 

Fisher’s Case Against the 6–12% Inventory Claim

Fisher’s response focuses on how the estimate was constructed and what it leaves out. 

His argument centers on the gap between a precise-sounding number and the evidence required to support it.

He starts with the foundation of the model itself and the assumptions driving the result:

• The 6%–12% estimate is not based on observed outcomes; it comes from a model built on layered assumptions.
• The model stacks multiple assumptions about seller behavior (based primarily on pricing confidence) and listing decisions to arrive at a single number.
• The model assumes a large share of sellers will respond to phased marketing, including an estimate that roughly 50% of sellers would adjust pricing and move forward with listing, without supporting evidence.

Also, as Fisher points out, some of the data used to back Redfin’s claims don’t accurately reflect U.S. seller behavior in 2026, including; 

• Dutch household data from the 1990s 
• Toronto tax data from the 2010s

Redfin’s model presents a specific range (6-12%) without providing basic statistical validation, including sample size, standard errors, or goodness-of-fit measures. 

Fisher then turns to how existing data is used and what the analysis leaves out of the equation. 

He leads with Redfin’s misleading use of Zillow data to support its argument, even though that research does not make a causal link between pricing uncertainty and listing behavior. 

As mentioned earlier, Zillow’s data shows sellers are influenced by multiple factors, including affordability concerns and life uncertainty, not a single driver. 

He also points out a few missing details: 

• Redfin’s analysis does not account for sellers who receive weak early signals and decide not to list, which could reduce net inventory
• Buyer-side effects are not considered, including the impact of fragmented listings and limited visibility
• Sellers who achieve higher prices re-enter the market as buyers, facing those same price levels, which offsets potential gains
• Homes that fail to generate interest in early phases may carry a signal when they hit the open market, even if official days on market remain low

Fisher also points out that small changes to these assumptions would materially change the outcome. In a model like this, the inputs drive the result. Adjust those inputs in a different direction and the projected inventory increase can shrink or even reverse.

Taken together, his argument is that the model produces a clean number by narrowing the scope of what it measures. 

What This Means for Agents and the Inventory Conversation

Fisher’s response lands on a broader point about how inventory is created and what role marketing strategies can realistically play.

Phased marketing may offer value in specific situations. When sellers are uncertain about pricing, early feedback can help refine expectations and reduce the likelihood of major pricing adjustments once a home hits the market.

The limitation is scale. A marketing strategy changes how existing homes are introduced to the market. It does not necessarily lead to an increase in housing supply. Data shows the underlying constraints on inventory are still tied to larger structural factors:

• Mortgage rate lock-in, which continues to limit seller mobility
• Affordability challenges that affect both buyers and move-up sellers
• Long-term underbuilding that has left a persistent supply gap
• Local regulations and construction costs that limit new development

The conversation around inventory often centers on tools that promise quick results. 

Specific percentage claims tend to get attention, especially in a market where agents and consumers are looking for signs of relief.

Fisher’s argument brings the focus back to what the data can support. A precise range like 6%–12% suggests a measurable, repeatable outcome. His position is that the estimate reflects a modeled scenario built on unverified assumptions, not evidence drawn from real-world phased marketing results.

Sharing those claims with your buyers and sellers is likely to get mixed results. And any argument based on assumptions rather than hard data will eventually ring hollow. 

Sooner rather than later for your more analytical clients.