It is one of the most common conversations we have with sellers in this market. Someone pulls up their address on Zillow, sees a number, and arrives at the listing conversation with that number already anchored in their mind. Sometimes it is too high. Sometimes it is too low. Almost always it is wrong in ways that are not obvious until you look at how it was calculated and what it was calculated from. The Zestimate is a useful tool for national averages. It is a poor substitute for a local agent's analysis of a market that behaves unlike almost anywhere else in the country.

How the Zestimate Actually Works

The Zillow Zestimate is a machine learning model that estimates home value based on publicly available data: tax records, deed transfers, listing history, and comparable sales pulled from MLS feeds. The algorithm is trained on millions of transactions and is genuinely impressive at what it does in markets with high transaction volume, recent comparable sales, and relatively homogeneous housing stock.

What it cannot do is account for the things that most significantly determine value in a market like northern Michigan. It cannot see that one property has a western-facing dock and another faces east. It cannot distinguish between Grand Traverse Bay frontage and a backwater slough. It cannot assess the quality of a renovation, the condition of a well and septic system, the presence of riparian rights, or the difference in demand between a property on the Old Mission Peninsula and an otherwise similar property ten miles inland. These are the variables that move prices here, and none of them are in the data the Zestimate draws from.

Zillow has published its own median error rate, which nationally hovers around 2 to 3 percent for on-market homes and climbs to 6 to 7 percent for off-market properties. In low-volume, high-variability markets like Leelanau County and rural Benzie County, that error rate is considerably higher because the model has fewer recent comparable transactions to draw from and the variables between properties are wider.

The Northern Michigan Variables That Algorithms Cannot Weigh

At The Foerster Group, we work with buyers across Traverse City, Leelanau and Benzie counties who come to us after doing their research online, and the gap between what they expect from a Zestimate and what properties actually trade for is one of the most consistent patterns we see. Here is why that gap exists:

•        Water orientation and access. Two properties on the same lake can trade at dramatically different prices based on which direction the shoreline faces, the depth of the water at the dock, the quality of the sandy bottom, and whether the riparian rights are clean and documented. None of these variables exist in public records data.

•        Seasonal use patterns. A property that has been used as a seasonal cottage for forty years has different maintenance history, different systems condition, and different buyer appeal than a year-round primary residence of identical square footage. The Zestimate treats them the same.

•        View premiums. A bay view adds measurable and significant value in this market. The premium varies by the quality and permanence of the view, neither of which can be assessed algorithmically.

•        Lot character. In a market where land is limited and geography is the product, the character of the lot matters as much as the structure. Flat lakefront versus steep bank access. Mature hardwoods versus cleared lawn. These are value drivers that require human eyes.

•        Renovation quality. A kitchen renovation in northern Michigan can range from a builder-grade flip to a custom installation using locally sourced materials and skilled craftsmanship. The Zestimate records that a renovation occurred. It cannot assess what it is worth.

What a Comparative Market Analysis Actually Does

A professional comparative market analysis, or CMA, is the tool that replaces the Zestimate for anyone making a real financial decision. Where the Zestimate draws from automated data feeds, a CMA is built by a local agent who has physically seen the comparable properties, understands the micro-geography of the market, and applies judgment about which sales are truly comparable and which are outliers.

A well-built CMA for a northern Michigan property accounts for:

•        Recent closed sales within a meaningful radius, filtered by water access, view, lot character, and condition rather than just square footage and bedroom count

•        Active listings that a buyer choosing your property would also be considering, which establishes the competitive context for pricing

•        Days on market patterns by price tier, which reveal where buyer resistance begins and where properties are moving at or above asking price

•        Seasonal market context, because a property priced in February competes in a different buyer environment than one priced in June

The result is a pricing recommendation grounded in what buyers in this specific market are actually paying for properties with this specific combination of attributes. That is a fundamentally different exercise than running an address through an algorithm.

When Zestimates Hurt Sellers

The most common way an inaccurate Zestimate costs a seller money is through overpricing. A seller who anchors to a Zestimate that is ten or fifteen percent above market value lists at a price buyers will not meet. The property sits. Days on market accumulate. Price reductions follow. And by the time the listing reaches its correct price, it has acquired the stigma of a property that could not sell, which suppresses final offers below what a correctly priced launch would have achieved.

The second common damage pattern is underpricing. A Zestimate that fails to capture the premium of a specific water view or a rare lot feature can lead a seller to leave significant money on the table by accepting the first offer at a number that reflects the algorithm's blind spot rather than the market's actual appetite.

In both cases, the cost of relying on the Zestimate rather than a professional valuation is real and measurable. The Foerster Group has closed over $200 million in sales in this market, and both Marc and Erica's marketing background means every listing is priced not just from comparable data but from a strategic understanding of how price positioning affects buyer psychology and offer behavior.

When Zestimates Mislead Buyers

Buyers use Zestimates differently than sellers, but the risk is equally real. A buyer who sees that a listed property is priced above its Zestimate may assume the seller is overreaching, when in fact the premium reflects attributes the algorithm missed entirely. Walking away from a property because its Zestimate is lower than the asking price is a reasonable heuristic in a market with abundant comparable data. In northern Michigan, it can mean passing on a legitimately priced property that reflects real value the model could not see.

Conversely, a buyer who sees a Zestimate above the asking price and assumes they are getting a deal may not be accounting for the condition issues, seasonal access limitations, or title complications that explain the discount. The Zestimate does not know about any of those things either.

The Number That Actually Matters

One of the questions we hear most often at The Foerster Group is what a property is worth before a seller has decided whether to list or a buyer has decided whether to offer. The answer to that question is always the same: let us look at it together. Walk us through the property, show us what you have done and what you have not, and we will build you an analysis grounded in what this specific market is actually doing right now.

That analysis will not always match the Zestimate. In northern Michigan, it rarely does. What it will do is give you a number you can make a real decision from, in a market where the difference between the algorithm’s guess and the actual value can be substantial in either direction.

We are here when you are ready to get the real number. Start at thefoerstergroup.com.