A seller called me from her home in Inver Grove Heights on a Thursday evening with a number already in her head.
She had spent two evenings on Zillow, Redfin, and a few other platforms, collecting the automated value estimates for her property. The numbers she found ranged from three hundred twelve thousand to three hundred forty-eight thousand dollars across the different sites. She had averaged them, added a little for what she believed was an advantage her home had over the algorithm’s assessment, and arrived at three hundred fifty-five thousand as her target list price.
She wanted to know if I agreed.
I asked her if I could come see the home before I gave her a number. She said yes. I came the following morning.
Her home was genuinely lovely. She had made meaningful improvements over her fourteen years of ownership. The kitchen had been fully updated two years earlier. The bathrooms were renovated. The basement was finished and well-done. The yard was beautifully landscaped.
My CMA, completed after the visit and after reviewing the specific comparable sales for her neighborhood and her home’s characteristics, supported a list price of three hundred thirty-eight thousand to three hundred forty-five thousand dollars.
There was a gap between what the automated tools had told her and what the market data actually supported. And there was also a gap, in the other direction, between where she had landed on her own and where the data pointed.
She was not happy about either gap. But she needed to understand both before she could make an informed pricing decision.
This article is about that understanding.
What Automated Valuation Models Actually Are
The value estimates that appear on Zillow, Redfin, Realtor.com, and similar platforms are produced by automated valuation models, commonly called AVMs. These are algorithms that process large volumes of publicly available data to produce an estimated market value for a specific property.
The inputs these algorithms use typically include recent sales of nearby properties, the subject property’s recorded characteristics from public records including square footage, bedroom and bathroom count, lot size, and year built, historical sale data for the subject property itself, tax assessment data, and in some cases listing data from the MLS.
The output is a single estimated value, sometimes presented with a confidence range, that the algorithm believes represents the current market value of the property based on that data.
These tools have become enormously popular with homeowners precisely because they are instant, free, and available without any professional interaction. They satisfy the very human desire to know what your home is worth right now without waiting for an appointment, a visit, and a formal analysis.
The appeal is completely understandable. The problem is what the algorithm does not know and cannot know.
What the Algorithm Cannot See
The fundamental limitation of any AVM is that it cannot see the inside of your home. It cannot evaluate the condition of your property. It cannot assess the quality of your renovations. It cannot distinguish between a kitchen that was updated in 1998 with contractor-grade materials and one that was updated in 2023 with custom cabinetry and premium appliances. Both homes, from the algorithm’s perspective, have an updated kitchen if that is how the public records describe them.
This matters enormously because condition and renovation quality are among the most significant determinants of value in the residential real estate market. Two homes with identical recorded characteristics in the same neighborhood can differ in market value by fifty thousand dollars or more based on condition, presentation, and improvement quality alone.
The algorithm also cannot account for location nuances within a neighborhood. Two homes on the same street might have very different values because one backs to a pond and one backs to a commercial property. Two homes in the same school district might differ meaningfully because one is in a pocket of the district served by a highly rated elementary school and one is not. These hyperlocal factors affect value in ways the algorithm cannot reliably detect or measure.
The algorithm cannot account for unique property features that do not fit neatly into standard data fields. A home with an exceptional view, a rare configuration of indoor and outdoor living space, professional-grade systems, or other distinctive features may be worth significantly more than the algorithm suggests because those features cannot be adequately captured in public records data.
And the algorithm cannot account for the current micromarket dynamics in your specific neighborhood. If three similar homes are currently under contract in your neighborhood and none of them has closed yet, the algorithm does not know about those pending sales because they are not yet reflected in closed sale records. But a Realtor who is actively working your market knows about those pending sales and can factor them into a pricing assessment.
What a Comparative Market Analysis Actually Is
A comparative market analysis, or CMA, is a professional assessment of your home’s market value prepared by a licensed real estate agent who has personally visited your property, reviewed the specific comparable sales in your market, and applied their professional judgment to produce a pricing recommendation grounded in both data and direct observation.
The process of preparing a CMA involves several distinct steps that together produce something fundamentally different from what an algorithm can generate.
The property visit is the most critical distinction. When your Realtor visits your home before preparing the CMA, they are gathering the information the algorithm does not have. They see the condition of the interior and the quality of improvements. They note the functionality of the floor plan and how it compares to buyer preferences in the current market. They observe the views, the light, the feel of the space, and the specific characteristics that will affect how buyers respond to the home.
The comparable selection process involves identifying the properties that are most relevant to your home’s value assessment. This is not simply selecting the most recent nearby sales. It involves judgment about which sales are genuinely comparable in terms of size, age, condition, style, location, and market timing, and which ones should be weighted more or less heavily because of how closely they resemble your specific property.
The adjustment process is where the Realtor accounts for differences between each comparable and your home. A comparable with an extra bathroom gets a downward adjustment. A comparable that is significantly older and less updated than your home gets an upward adjustment. These adjustments translate the differences between properties into dollar values based on the Realtor’s knowledge of what buyers in your market are actually paying for specific features.
The market context analysis incorporates the current conditions in your specific market, including how quickly homes are selling, what the competition looks like, whether buyer demand is strong or moderate, and what direction prices appear to be trending, into the pricing recommendation.
The result is a specific, defensible pricing recommendation that reflects your home’s actual characteristics, current market conditions, and the professional judgment of someone who has seen your home and knows your market.
The Accuracy Gap: How Much Do AVMs Typically Miss?
The accuracy of automated value estimates varies significantly based on the type of property, the location, and the availability of comparable sales data.
In neighborhoods with consistent housing stock and frequent sales, where most homes are similar in size, age, and style and where sales happen regularly, algorithms can produce estimates that are reasonably close to actual market value. In these settings the variance might be within five to eight percent of actual value in many cases.
In neighborhoods with more variety in home types, less frequent sales, significant variation in condition and renovation quality, or unusual property characteristics, the variance can be much larger. Studies of AVM accuracy in diverse residential markets consistently find that a meaningful percentage of automated estimates are off by ten percent or more, and that some properties produce estimates that are off by twenty percent or more in either direction.
In the specific context of Minnesota’s housing market, the variance in AVM accuracy is influenced by the significant diversity of housing stock across the metro. Older inner-ring suburbs with diverse home types and condition ranges, newer outer suburbs with more consistent but rapidly changing sales prices, lake-adjacent properties with unique value characteristics, and communities with limited recent sales all present challenges for algorithms that rely on historical pattern matching.
The seller in Inver Grove Heights experienced a specific version of this accuracy gap. The algorithms were unable to account for the specific quality of her kitchen and bathroom renovations, the quality of her finished basement, and the specific positioning of her lot relative to green space. The CMA, prepared with a physical visit and specific market knowledge, produced a number that reflected those factors.
When AVM Estimates Run High Versus Low
Understanding in which direction automated estimates are likely to be off helps sellers calibrate how to use these tools most productively.
AVMs tend to run high relative to actual market value in situations where the algorithm is using comparable sales from a stronger market period and has not adequately accounted for a market shift, where a home has deferred maintenance or condition issues the algorithm cannot see, or where the neighborhood or property type has specific challenges that reduce buyer demand relative to what the recorded data would suggest.
AVMs tend to run low relative to actual market value in situations where recent renovations have not been captured in public records, where the home has unique features that add value beyond what standard data fields can reflect, where local market dynamics are generating above-average buyer competition that closed sales data has not yet captured, or where the home benefits from hyperlocal location advantages the algorithm cannot detect.
Both errors matter to sellers, but in different ways. An AVM that runs high relative to actual value may encourage a seller to price too aggressively, producing the overpricing problems described in earlier articles in this series. An AVM that runs low may discourage a seller who worries they cannot sell for what they actually can, or may be used by buyers as leverage in negotiation when it does not accurately reflect the home’s true value.
How to Use AVM Estimates Productively
Given their limitations, the appropriate role for automated value estimates in a seller’s research process is as a preliminary orientation tool rather than as a pricing foundation.
Checking multiple AVM estimates gives you a rough sense of the general price neighborhood your home likely occupies, even if the specific numbers are not reliable. If every AVM estimate you find is in the range of three hundred thousand to three hundred fifty thousand, that tells you something meaningfully different from a situation where all the estimates are clustering around four hundred fifty thousand. The range itself provides orientation even when the specific numbers are uncertain.
Looking at the trend in your AVM estimate over time on a platform that tracks this, as Zillow does for some properties, can give you a directional sense of whether automated tools perceive values in your area as rising, falling, or stable. This trend information has some value even when the absolute numbers are uncertain.
Using AVM estimates as a conversation starter rather than a conversation ender is probably their most productive role. Bringing your AVM findings to a listing consultation with your Realtor and asking them to explain why the CMA they have prepared differs from the automated estimates is a productive way to understand what the algorithm is missing and what the professional assessment adds.
Common Mistakes Sellers Make About Online Estimates
Treating the Zestimate or other AVM as the definitive value of their home and pricing accordingly without obtaining a professional CMA.
Averaging multiple AVM estimates and treating the average as more accurate than any individual estimate, when averaging multiple imprecise estimates produces a more precise-seeming but not more accurate result.
Using AVM estimates to override their Realtor’s CMA recommendation when the CMA is based on a physical visit and specific market knowledge that the algorithm does not have.
Selecting the AVM estimate that is most favorable to the price they want to achieve rather than treating the range of estimates as collectively informative.
Not understanding that AVM estimates can be significantly less accurate for homes with distinctive features, recent renovations, or limited comparable sales data in the immediate area.
Practical Tips for Sellers
Use AVM estimates as preliminary orientation before obtaining a professional CMA, not as a substitute for one.
Share the AVM estimates you have found with your Realtor during the listing consultation and ask specifically how they have accounted for the factors the algorithm could not see in their pricing recommendation.
Ask your Realtor to explain the specific comparable sales they used in the CMA, how they adjusted for differences between each comparable and your home, and why those adjustments reflect current market conditions.
If there is a significant discrepancy between the AVM estimate and the CMA recommendation, ask your Realtor to explain specifically what accounts for the difference rather than simply accepting the professional recommendation without understanding it.
Understand that the CMA is also an estimate, not a guarantee of sale price, and that the actual sale price will ultimately be determined by what buyers in the current market are willing to pay for your specific home under current conditions.
Frequently Asked Questions
Is a Zestimate accurate enough to use for pricing my home?
In most cases, no. The Zestimate provides a rough general orientation but lacks the property-specific and market-specific precision necessary to be a reliable basis for a listing price decision. A professional CMA from a Realtor who has visited your home and reviewed specific comparable sales is the appropriate tool for pricing.
Why do different AVM sites give different estimates for the same property?
Different platforms use different algorithms, different data inputs, different weighting of various factors, and different comparable selection methodologies. The variance between platforms reflects the different approaches each algorithm uses and the genuine uncertainty in automated valuation for any specific property.
Can I challenge an AVM estimate I believe is inaccurate?
On some platforms you can submit updated information about your home, such as renovation details or corrected square footage, that may be incorporated into an updated estimate. This does not make the AVM a substitute for a CMA but can improve the estimate in situations where the platform’s records are clearly incomplete.
How often are AVM estimates updated?
This varies by platform. Some update daily or weekly. Others update less frequently. In a rapidly moving market, even a frequently updated estimate can be significantly out of date relative to current conditions.
Should I use the CMA or an independent appraisal for pricing?
For pricing purposes, a CMA prepared by an experienced Realtor with specific knowledge of your market and your home is generally the most appropriate tool. An independent appraisal is more commonly ordered by lenders and buyers than by sellers for pricing purposes, though some sellers choose to obtain one for additional confidence, particularly for distinctive or high-value properties.
Final Thoughts
The seller in Inver Grove Heights listed at three hundred forty-two thousand after a thorough conversation about what the CMA showed, why it differed from the AVM estimates she had collected, and what the specific factors were that made her home worth what the professional analysis suggested.
She initially pushed back on the number being lower than some of the AVM estimates she had found. I walked her through the specific comparable sales and the adjustments made for each one. She understood why the number was where it was.
She received two offers within the first week. She accepted one at three hundred forty-nine thousand, seven thousand above her list price and solidly within the range the CMA had identified as achievable.
The automated tools had given her a range that straddled the truth in different directions. The CMA had given her the specific, grounded number that reflected what the market was actually going to pay for her specific home.
That is the difference between orientation and precision, and in a pricing decision of this magnitude, precision is what you need.
Lesley The Realtor helps Minnesota sellers understand the true market value of their homes through thorough, property-specific comparative market analysis that reflects what buyers in today’s market will actually pay.
Visit https://sell.dreamhomesminnesota.com/ to start the conversation.