Getting the right numbers has always been a major challenge in real estate marketing. We are discussing extensive calculations from various aspects to determine the correct property value. Even after years of experience, real estate professionals remain subject to voluminous amounts of manual analysis. But with AVMs, the work became much easier.

Still, you need to master how best to use these models. You must ensure their accuracy and representation of the market value. That’s why experts focus on pre-list benchmarks for real estate AVM accuracy. But what are these, and how can you put them to the best use?

What is an Automated Valuation Model?

Imagine using a calculator that runs on an almighty formula. This device takes your input, runs it across a selected model, and gives you a satisfying result. That’s how AVMs work. They use automated processes to compute real estate values and generate a final result.

The speed of automated valuation models (AVM) makes them popular. Rather than run manual property valuation calculations, you can use these models to generate a general value. They’re also largely convenient because they take the bulk of the workload off your shoulders.

AVMs operate using different categories of data benchmarks, namely property-specific, market-level, and transaction-level. Let’s focus on the latter, specifically, prelist benchmarks.

What are Prelist Benchmarks?

A prelist benchmark is a property’s baseline value. The automated valuation models generate this prelist benchmark prior to listing, allowing you to compare the property’s sale performance. The prelist benchmark enables the AVM to make accurate market predictions without knowing the list price.

With a prelist benchmark, you get to understand how an automated valuation model analyzes the selling price without prior knowledge of the list price. Instead, you use the AVM’s estimate before the list date to calculate the sale’s accuracy. This ensures an unbiased price comparison, as the AVM operates independently of the price list. So, your AVM runs accurate pricing analysis without the influence of elements in list prices. 

Prelist vs. Postlist Benchmarks

Transaction-related benchmark levels often come in two forms: prelist and postlist. Both have unique characteristics.

• Postlist benchmarks reveal the automated valuation model’s prediction compared with the property’s sale price. This way, you can analyze how accurately the AVM works and improve its future performance.
• Prelist benchmarks provide an estimate without knowing the price list. It allows you to write an acceptable review without listing biases.

When it comes to discussing automated valuation models in real estate, both benchmarks are quite similar. However, their key difference lies in how they conduct valuations. While postlist benchmarks need the price list, prelist benchmarks operate without them. We exclude the historical list and sales date as long as there is a significant period between the previous and current list dates.

Why Prelist Benchmarks Are Better for Real Estate AVM Accuracy

On automated valuation models, postlist benchmarks run comparisons between the final price estimate and predictions. This method, however, means that the model operates using samples from the price list. The samples on the price list will heavily influence the result. Therefore, the calculation usually overestimates the final result.

However, prelist benchmarks do so without the price list. That means they run their analysis with the value offered before the property listing. As a result, prelist benchmarks are more preferred for real estate AVM accuracy.

But how are they better? 

Less Partiality

A real estate automated valuation model typically employs a “snap to” list price logic. That means they take into account the sample prices listed when making valuations. This often causes inaccuracies in valuations, as the AVM’s logic runs on the element of bias.

But prelist benchmarks eliminate this problem. By conducting the valuation without a set price list, you gain a clearer understanding of the property’s market value. A prelist benchmark model provides a more concise analysis.

Deeper Market Focus

Real estate AVM valuations, along with postlist benchmarks, frequently provide accurate on-market results. However, due to their reliance on the price list, they often overlook or disregard numerous other crucial details.

However, with prelist benchmarks, AVMs can scan through a wider pool of factors affecting property prices. This lets them create a more reliable analysis of property value. Additionally, the results can work for both on- and off-market assets.

Stronger Insights

Postlist benchmarks rely entirely on the provided property list. Therefore, even though their results might seem precise, they tend to overlook numerous elements. That means you’ll be running a property sale based on incomplete information. And you may end up selling the property at an incorrect value, resulting in losses.

With prelist benchmarks, however, you can avoid this real estate automated valuation model problem. Because its model is based on information prior to price listing, the analysis is more robust. This lets the valuation generate results from a wider database. With that, you can make better property sale decisions.

More Transparency

The informed real estate agent knows that off-market properties comprise 98-99% of housing stock every time. However, when you use postlist benchmarks to run property valuations, you miss out on this information. Instead, the real estate AVM model analyzes only on-market listings. The result is a valuation that doesn’t properly reflect the property’s true price.

However, prelist benchmarks solve this problem for automated valuation models in real estate by running an analysis based on every relevant factor. These include:

• Property location
• Investment horizon
• Property condition
• Indirect investments (trusts, mortgages, etc.)

We can also evaluate these using postlist benchmarks. However, the bias in the price list data may make the results accurate. However, with prelist benchmarks, you can get a stronger, more accurate estimate of a property’s worth. They make your assessments clearer and more honest. This advantage not only proves your prowess in the real estate field, but it also saves your reputation as an expert.

How We Can Help

Real estate valuation is complex and time-consuming. Many professionals are turning to automated valuation models (AVMs) to streamline their processes. However, not all AVM implementations are equally effective. At North South Tech, we’ve developed AVM solutions that prioritize prelist benchmarks, ensuring more accurate and unbiased property valuations.
Our AVM technology goes beyond traditional postlist benchmarks, which can lead to skewed results. By focusing on prelist data, we provide a clearer picture of a property’s true market value. This approach considers a wider range of factors, including off-market properties, resulting in more comprehensive and reliable assessments.
We understand the importance of maintaining your reputation as a real estate expert. Our prelist benchmark-based AVMs help you avoid costly errors and demonstrate your commitment to precise valuations. Whether you’re dealing with residential or commercial properties, our solutions adapt to your specific needs.
Curious about how our AVM technology can transform your valuation process? Let’s talk.