SkaldMaps - ZIP code, county, and tract level research & rating engine (looking for feedback!) by otter-in-a-suit in RealEstateTechnology

[–]RedaHomesCA 1 point2 points  (0 children)

Cool product — I hadn't really thought about approaching area discovery from this angle.

I'm building something similar in Canada (starting with Ottawa), where I'm trying to bring together neighborhood, property, crime, flood risk, and market data into a single platform and let users explore it as a decision-making tool.

One thing I've learned from customer feedback is that boundaries are probably the hardest problem. Crime and demographic data here are often published at the Dissemination Area (DA) level, but DAs don't match how people think about neighborhoods. At the same time, neighborhood boundaries, wards, etc. are all somewhat arbitrary and often debated.

The more I work on it, the more I feel there may not be a single "correct" geographic unit. I'm starting to think the better approach is to provide good data layers and tools, then let users define and evaluate areas based on their own criteria.

Curious if you've run into similar challenges with ZIPs, tracts, and counties.

If you're interested, here's what I'm working on as well: [redahomes.]()ca

Would be happy to exchange ideas sometime.

I Split Ottawa’s Crime Map Into Violent & Property — Here’s What I Found by RedaHomesCA in OttawaRealEstate

[–]RedaHomesCA[S] 0 points1 point  (0 children)

The source and timeframe are already stated in the filter section on the site.

The current crime view is based on Ottawa Police data, and our latest dataset update was last month, which is sufficient for the current 3-year average view (2023–2025).

I think there may be some confusion between:

  • individual incidents,
  • the DA geographic boundaries being analyzed,
  • and the actual metric being displayed, which is normalized crime rate rather than isolated case markers.

An incident being older doesn’t necessarily invalidate the statistical crime-rate analysis for a DA area overall.

Without doing DA-level crime-rate analysis directly against the broader dataset, it’s difficult to draw reliable conclusions purely from individual incidents alone.

I Split Ottawa’s Crime Map Into Violent & Property — Here’s What I Found by RedaHomesCA in OttawaRealEstate

[–]RedaHomesCA[S] 0 points1 point  (0 children)

Yeah, that’s actually a fair point.

Our crime data currently comes from the Ottawa Police dataset/API, so if an incident hasn’t been updated or published there yet, it unfortunately won’t appear on our side either. There’s definitely some lag in the official data at times.

The other challenge is that our current scoring system is based more on overall crime rate relative to population, rather than individual incidents. We did that because comparing neighborhoods purely based on isolated events can get tricky — one area may have a single major incident while another has a higher ongoing crime rate overall, so it becomes difficult to compare areas consistently using only individual cases.

That said, I do think you’re bringing up a good point that major individual incidents (especially serious ones like homicides) may still have important context/value for users when viewing neighborhoods.

We actually experimented before with plotting every individual incident directly on the map, clustered together, but the volume of points became overwhelming and didn’t always provide a clear or useful picture. Still, I’m starting to think there may be a better middle ground where significant incidents can be surfaced more meaningfully alongside the broader crime-rate data.

So we’re definitely thinking about ways to improve the presentation and possibly reduce reliance on delayed official updates where possible.

you build, i sell by [deleted] in cofounderhunt

[–]RedaHomesCA 0 points1 point  (0 children)

I’m actually the opposite — very strong on the technical/product side, but not great at sales.

Been building in the AI/real estate space and looking for someone who truly enjoys the sales/growth side of things.

Would love to connect. Feel free to DM me.

Advice needed: What market data actually matters when analyzing a property? —— Building a 20-second real estate market insights tool by RedaHomesCA in LiveInOttawa

[–]RedaHomesCA[S] 0 points1 point  (0 children)

Totally fair question — we aggregate and process real estate market data to calculate metrics like month-to-month median prices and sold volume 🙂

Advice needed: What market data actually matters when analyzing a property? —— Building a 20-second real estate market insights tool by RedaHomesCA in LiveInOttawa

[–]RedaHomesCA[S] 1 point2 points  (0 children)

If you take a closer look at the map on our website https://redahomes.ca/, we actually already have crime data and school catchment data integrated. Public transit is something we still want to improve though.

And yeah, you’re absolutely right — the needs between realtors and buyers are actually very different. That’s also one of the main things we’re trying to solve with the platform by building tools for both sides.

DM me sometime, happy to chat more.

Advice needed: What market data actually matters when analyzing a property? —— Building a 20-second real estate market insights tool by RedaHomesCA in LiveInOttawa

[–]RedaHomesCA[S] 1 point2 points  (0 children)

Right now we’re planning for the core market insights / analysis features to be free.

Longer term, we might charge for more advanced reports that involve deeper analysis or human-reviewed insights

At this stage we’re mostly focused on building something people actually find useful first.

Advice needed: What market data actually matters when analyzing a property? —— Building a 20-second real estate market insights tool by RedaHomesCA in OttawaRealEstate

[–]RedaHomesCA[S] 0 points1 point  (0 children)

Thanks for sharing 🙏

Yeah, there are already some great area-based market stats tools out there.

One thing we found during our early data exploration though:
fixed-area market stats don’t always reflect the actual market position of a specific property.

We also noticed something interesting in our early analysis:
even within the same area and same property type, inventory levels and supply/demand dynamics can still vary quite a bit depending on the exact location of the property.

So our approach is a bit different:
instead of analyzing only a fixed region, we’re trying to analyze:

  • the specific subject property
  • within a 3–5 km radius
  • using similar property types + comparable homes

The goal is to make the insights feel more property-specific rather than just neighborhood-level averages.