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PRYCD Pricing Strategy


Our pricing strategy is unique to our system, and has been created, updated and modified over the past several years. Input from hundreds of land investors with expertise in all areas and facets of investing have contributed to the current model. Below are some topics that apply to all of our pricing schemes. To read about a specific pricing scheme, please visit our Pricing Schemes page!

Listing Sources

The first step in our pricing is to collect as much information as possible. This involves going to several comp listing sources and aggregating all of the for sale and sold comps into a single database. The listing sources we use are below:



Lands of America

Land Flip

Duplicate Comps

One of the side effects of pulling data from multiple listing sources is that you are bound to have duplicate comps in the aggregated database. We do our best to eliminate duplicates during collection, but occasionally some will still make it in. While all of our tools and services show all comps in a particular location, our pricing model is designed to find these duplicates and only use one of them in the actual modeling.

Modeling Acreages

Something unique about our system is our acreage increment input, which determines how to break apart the different acreage ranges. One important part of this feature is that the way the acreages are broken up also determines how they are modeled. For example, searching for property from 0-10 acres in increments of 1 acre will model each range (0-1, 1-2, etc) as it's own model. However, the same search of 0-10 acres in increments of 10 will model 1 single range (0-10), which will yield a drastically different price/acre.

For Sale and Sold Comps

When we look at creating our model, one of the more critical aspects is how we use for sale and sold comps. We prioritize the value of sold comps higher than for sale comps, as these are a more accurate reflection of the property's value. All sold comps in our system are sold within the previous 12 months from the time of our last data update. All of the for sale comps are what is currently listed on our targeted listing sites at the time of the data update. We also consider the time on market of a for sale comp when we create our model, as a property that hasn't sold for a substantially long time may indicate that the listing price is too high, or that it's an undesirable property.

Weights and Distributions

Weighting and distribution analysis for our pricing systems are very unique. When we take a set of comps to create a model, we first run them through a statistical analysis engine to determine what the distribution of the comps are. Once we are able to determine the distribution, what we then do is isolate and remove outlier comps from the set that do not fall within an acceptable range of the distribution, otherwise known as an IQR. Once we have our final list of comps to create a model, we then weight them accordingly. Weights can be based on comp status (sold/for sale), time on market, or distance to a property (Geo Pricing).

Learn more about how to use our Weights and Distributions

Non Disclosure State Pricing

One question we get a lot is how our model handles non-disclosure state pricing. While we do have a limited number of sold comps to use, we are still able to create a quality model! We have minimum criteria that all models must meet, and for non-disclosure states we adjust our criteria to look more closely at the for sale comps, since these are the majority of the comps going into the model. To compensate for a lack of consistent sold data, we also create a tighter distribution to ensure that outliers are more effectively managed.

Please contact support if you have any questions or concerns.

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