Today we’re thrilled to announce that TopHap has national coverage! This momentous milestone means that you can now see detailed property facts and analytics across all 50 states.
National coverage has been one of the most frequently requested features, and its launch unlocks an extraordinary amount of use cases for understanding and analyzing Real Estate data at scale.
National Data At a Glance
The national launch introduced a whole bunch more data! Our latest dataset is over 15TB and includes:
- 161,705,043 property records
- 7,269,134 streets
- 726,061 zones (schools, cities, etc)
- 45B unique data points
- ~300 data points per property
The power of national data
While the sheer amount of data added to TopHap over the last several months is impressive, these stats only scratch the surface of what market insights can be discovered in a few short minutes on the platform.
Let’s see how national data is a game-changer for real estate analysis on TopHap:
The most apparent difference of having national data is the ability to identify patterns across properties along any metric on TopHap — even in places you’ve never been.
On TopHap, purple areas represent higher values and yellow areas represent lower values. If you change the map area, the hexagon groupings are recalculated on the fly to visualize the scale for the new set of properties. You can see the color scale in the legend.
Interpreting this map, we can see that the largest concentrations of expensive homes are are in coastal states: California, New York, Connecticut, Rhode Island, Massachusetts, etc. Perhaps more surprising are the noticeably dark pockets in Colorado, Utah, Arizona, Texas, Wyoming, Montana, Tennessee, and Virginia.
Hovering over the the map reveals the number of properties in the hexagon group and the median value.
When using different analytics layers, you see data that confirms the observations you’ve made from working in a given area for years. When using the heatmap in areas you’re unfamiliar with you’ll discover fascinating insights that were previously only known by veterans in that market.
Use Case: Block-level analysis from afar
With the rise in offers sight unseen, the ability to gather data and accurately assess property values without stepping foot on the premises is quickly becoming an invaluable asset.
The picture below is a random street in Knoxville, TN, but what caught my attention is this clearly distinct row of high valued homes. All of the homes on the north side of the street are almost twice as valuable as the homes on the south side.
This insight is something that you never would have known just looking at listings, so let’s dig in and make an educated guess about why this is the case.
We can find the specific neighborhood we are looking at by hovering over a parcel and finding the neighborhood name.
Adding the neighborhood name to the search bar shows us the boundary of the neighborhood and restricts our results to this area.
Filtering out properties outside of the neighborhood shows us even more detail. We can see which specific parcels are the most and least valuable.
Just from looking at the parcel shapes, we can tell that the expensive homes have bigger lots. Let’s verify this with the heatmap:
The data confirms our suspicion! All of the expensive homes on the north size of Scenic Dr. lots larger than 1 acre compared to the lots on the south side which are typically around 0.5 acres.
Let’s finally check on the size of the homes. Usually with a bigger lot, you’ll find bigger homes too. Let’s see the difference between the homes north and south of Scenic Dr.
Aha! As we suspected, the homes north of Scenic drive tend to be almost twice as big as the ones south of the road.
Already, we can see some of the essential factors that explain how the houses on one side of the street (and in the exact same neighborhood) can have such drastically different valuations.
Use Case: Relocating to a larger home for the same price
Let’s say that you’re currently living in a $1 million 3 bedroom, 3 bath, 1800 ft² house in California and would like to relocate somewhere else where you can get a bigger house for the same price.
Using the new national data on TopHap, you can easily find which areas in the US have the largest homes that fit your criteria.
Step 1: Add filters
In our case, we only want to include data for single family homes under $1M with more than 3 bedrooms and 3 baths, so we’ll add those filters accordingly.
Step 2: Toggle filter heat map
By default, filters only apply to listings. If instead, we want to apply filters to the heatmap data, we can toggle the filter heatmap switch. Turning this option on excludes data from properties that don’t match your filter criteria.
You can see in the gif above that when filter heatmap is off, the heatmap includes all properties. Once we toggle filter heatmap on, the heatmap only takes into account the data of single family homes under $1M with more than 3 bedrooms and more than 3 baths.
This is an incredibly powerful feature because it allows us to remove properties that are skewing our heatmap data and see a clearer picture of possible locations to buy our new property.
Step 3: Expand your search nationally
Zooming out on map, we can now see the areas that have the largest homes for our selected criteria (under $1M and more than 3Bd 3Ba).
Armed with this knowledge, you can now begin a deeper search in the dark purple areas in the map shown above. These areas in general have larger homes.
Hopefully these demonstrations have given you a few ideas about how TopHap’s new national coverage can help you research real estate at massive scale and with impressive detail. Macro and micro, TopHap’s tools allow you to understand any market, property, and region in minutes, not years — even from across the country!
Try TopHap today and start exploring any market in the USA at www.tophap.com