In Search, you can use Layers to target specific properties and remove any properties that you don't want included in your search.
Let's try finding potential listings in your current neighborhood. We recommend applying the Ownership Time and Home Equity layers to find your market neighborhood.
Since we know that people typically sell their homes every 7 to 12 years, you'd select the Ownership Time layer and set the minimum to 7. When you click Apply, all the blue dots that don't meet that criteria will disappear from the map.
We also know that if a person doesn't have enough equity, they probably aren't eligible to sell. To filter based on equity, set the Home Equity layer minimum to 250,000. When you click Apply, more ineligible blue dots will disappear.
For more information on the available layers, visit the Remine Filters and Layers article.
- Sell Score: We recommend using the Sell Score filter alongside other filters to increase accuracy. For example, you could combine Sell Score, Ownership Time, and Home Equity.
- Absentee: You can use this filter to identify people who may be tired of renting their property and are looking to sell or tenants who are renting and may be ready to buy.
- Flood Zone: You can use this filter to ensure that you are not pulling listings that fall in high-risk zones unless your buyers are willing to pay for expensive flood insurance.
- Building Type: A great use case for this, is someone that works with condominiums. Using this filter, you pair the Building Type and Home Equity filters to find condo owners with enough equity to sell. You can also add the Sell Score filter to narrow your results to those who are likely to sell within the next year.
- Land Use: If you have a client that is interested in a parcel of land, but they are concerned about the zoning of the empty parcel of land across the street. You can view this data instantly with Remine.
- Distressed Deals: You can use this filter to find potential opportunities for investors.
- Airbnb: You can use this filter if you're working with someone who wants to rent a property. You can use the Airbnb layer to identify popular areas for rentals and average short-term rental prices. Alternatively, you can use this filter if you're working with a buyer who doesn't want to live in an area with lots of short-term rentals. You can use the Airbnb layer to identify areas with fewer short-term rental properties.
The Cash Buyers overlay displays properties that were paid for in cash.
We reference the transaction date and whether a mortgage was taken out on the property within 48 hours before or after that date. You can confirm the exact mortgage date on the Property Details page.
When you click Cash Buyers, flags appear for any properties in the area that we've determined were cash sales. This is an overlay, rather than a filter because applying the Cash Buyers overlay does not remove any blue dots.
If you can't find distressed deals it's possible that your state doesn't require lenders to report all of these document types. Check your state's foreclosure laws for more information.
Alternatively, if your state's foreclosure laws say it is reported, it is possible we could be missing data. If you believe the latter is more likely, please Submit a Bug and include corresponding documents, if any.
Airbnb is a company that specializes in vacation home rentals. Individuals can use Airbnb to set up short-term rentals for their own properties.
The Airbnb overlay in Remine displays flags for available Airbnb rentals in the area. Airbnb does not publicly reveal property addresses for security reasons. Specific addresses are only provided to guests after they book a rental.
Since we don't receive addresses from Airbnb, the flags displayed in Remine don't correspond to any particular blue property dots, and you cannot filter for Airbnbs. However, the flags will appear within the neighborhood or block of the rental, so the Airbnb layer is useful for identifying the concentration of short-term rental properties in a given area.
To learn more about Airbnb, visit the Airbnb Help Center.
How do I interpret Sell Score?
The Sell Score model searches for underlying patterns based on available data. This means that agents will often have important information about a property that isn't included in the Sell Score model. For this reason, we recommend combining Sell Score with other layers, like Home Equity, to most effectively identify your target market.
Properties can have a Sell Score of High, Medium, or Low.
- High - The property is in the top 5% of properties that are likely to sell in the next 6 months.
- Medium - The property is in the next 15% of properties that are likely to sell in the next 6 months.
- Low - The property is in the lower 80% of properties, meaning it's less likely to sell in the next 6 months than High or Medium properties.
Predictive analytics involves using historical data with machine learning and artificial intelligence to predict what will happen in the future. We analyze historical data with a mathematical model that considers key trends and patterns. We then apply this model to current data to predict what will happen next.
A High Sell Score property is 2 to 6 times more likely to transact in the next 6 months than a randomly selected property.
What does this mean?
- If you select 100 off-market homes at random, on average, 2 to 3 of those properties will likely sell in the next 6 months.
- If you select 100 off-market homes with a High Sell Score, 5 to 20 of those properties will likely sell in the next 6 months.
How do we measure the Sell Score's accuracy?
We measure the Sell Score's performance through an equation that compares properties with a High Sell Score to the homes that have actually sold. We run this equation in limited geographic areas to calculate accuracy among various markets.
We calculate Sell Scores biweekly to keep the scores as up to date as possible. Not every property will see a difference with each Sell Score update, but an average of about 5% of properties change each month.
A property's Sell Score may change over time as we receive the new or updated information. The Sell Score model is always changing and improving, so Sell Score changes are a good thing.
We calculate Sell Score using weighted values, so you may occasionally come across some surprising results (e.g., a property that transacted within the last year with a high Sell Score).
The following are the primary variables that affect the Sell Score:
- Property attributes (e.g., square footage, bedrooms/bathrooms, and current valuation).
- Property transaction history (e.g., time since last sale, current mortgage(s), and foreclosure history).
- Neighborhood averages of the previous two variables, for many different neighborhoods (e.g., by ZIP code, by city, and by state).
When any of these data points change, the Sell Score changes accordingly.