Decoding Online Metrics: Do Zillow and Redfin Views and Saves Predict Home Sales?
In the digital age of real estate, platforms like Zillow and Redfin have transformed how homes are bought and sold.
Sellers often scrutinize metrics such as “views” and “saves” (or “favorites” on Redfin) on their listings, wondering if these numbers hold any real predictive power.
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- Do high views guarantee a quick sale?
- Can a surge in saves signal offers above asking price?
While these metrics aren’t crystal balls, they do offer valuable insights into buyer interest and market demand.
Zillow’s Metrics: Views, Saves, and Shares as Early Indicators
Zillow, one of the most popular real estate websites, tracks user engagement through views, saves, and shares, displaying data from the last 30 days. Views represent how many times a listing has been seen, saves indicate users bookmarking the property, and shares show when it’s forwarded to others. According to Zillow’s research on listings from spring 2023, these metrics in the first week can strongly predict sale speed and price.
For example, homes averaging over 250 daily views often go under contract within a week, with three-quarters selling in two weeks. Listings exceeding 500 views per day frequently fetch prices above the asking amount.
Saves are even more telling of serious intent: An average of five or more daily saves correlates with offers in about a week, while 10+ saves link to above-list sales.
Shares, though less common, amplify this—20+ daily shares suggest a home could sell faster than the median 15 days on market, often at 98% or more of the list price.
These patterns stem from Zillow’s vast user base, where high engagement reflects broad appeal. In hot markets, a listing with hundreds of saves might indicate competitive bidding, giving sellers leverage to hold firm on price or even encourage escalations.
Redfin’s System: Favorites and the “Hot Homes” Algorithm
Redfin takes a slightly different approach, emphasizing “favorites” (equivalent to saves) alongside views in its owner’s dashboard for claimed listings. These feed into Redfin’s proprietary “Hot Homes” algorithm, which predicts a property’s likelihood of selling quickly based on over 500 attributes, including price, location, and user activity.
A home earns “Hot Home” status if the algorithm estimates a 70% or higher chance of an accepted offer within two weeks. High initial views and favorites are key triggers, often leading to a visible “HOT” banner that boosts visibility and creates buyer urgency.
While Redfin doesn’t explicitly tie these to sale prices, user reports and platform data show that “Hot Homes” tend to move faster in competitive areas, sometimes resulting in cash offers or multiple bids.
Unlike Zillow’s straightforward counts, Redfin’s metrics are part of a dynamic system that updates daily. If interest wanes—say, due to a price that’s too high—the status can drop, alerting sellers to adjust strategies promptly.
The Predictive Power: Correlations with Sale Speed and Price
Across both platforms, elevated metrics correlate with positive outcomes. Zillow’s analysis shows homes with strong first-week engagement selling quicker and closer to (or above) list price, especially in seller’s markets. For example, in regions like Seattle or Austin, where inventory is low, 500+ views might foreshadow a bidding war.
Redfin’s “Hot Homes” boast an accuracy rate where labeled properties often close rapidly, helping sellers gauge demand without waiting for showings. Broader industry studies, including from the National Association of Realtors, support this: Online interest metrics align with offline actions, as engaged users are more likely to request tours or submit offers.
In essence, these numbers act as a barometer of demand. High saves suggest the listing resonates—perhaps due to appealing photos, competitive pricing, or desirable features—potentially leading to a smoother, more profitable sale.
Limitations and Caveats: Not All Metrics Translate to Sales
However, views and saves aren’t infallible. High views might stem from casual browsers or algorithmic boosts rather than genuine buyers. Saves can accumulate without follow-through; a listing with poor interior photos or undisclosed issues might rack up bookmarks but few showings. Overpricing is a common culprit—metrics may plummet if the home seems out of reach.
Market conditions play a huge role. In slower economies or buyer-heavy areas, even stellar metrics might not yield quick sales. Zillow notes that while correlations exist, they’re probabilistic, not guarantees. Redfin’s algorithm, though sophisticated, can misfire in atypical markets or with unique properties.
Additionally, these platforms capture only a slice of the market. Not all buyers use Zillow or Redfin; some rely on agents or other sites like Realtor.com. Fake engagement or bots could inflate numbers, though platforms mitigate this through verification.
Practical Advice for Sellers: Leveraging Metrics for Success
Sellers can use these insights proactively. Monitor metrics weekly and compare to local averages—if views lag, refresh photos or virtual tours. Low saves? Revise the description to highlight strengths like “updated kitchen” or “proximity to schools.” If metrics soar but offers don’t follow, consider open houses to convert interest.
Consulting a local agent is crucial; they can interpret data in context, perhaps using Zillow’s tools for pricing adjustments. In competitive markets, aim for that first-week surge by listing mid-week and promoting on social media.
Ultimately, treat views and saves as guides, not gospel. Combine them with traditional metrics like days on market and showing feedback for a holistic view.
For Your Consideration
Zillow and Redfin’s views and saves do hold meaning for sellers, serving as early signals of interest that often predict faster sales and better prices. While not perfect, they empower data-driven decisions in an increasingly online real estate landscape. By understanding and acting on these metrics, sellers can navigate the market more confidently, turning digital curiosity into real-world closings. As platforms evolve, these tools will likely become even more refined, bridging the gap between virtual views and signed contracts.
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