What is the Buy Score?
Buy Score is a predictive analytics tool that identifies which individuals are likely to purchase a property sooner than others in their area, measured on a High, Medium, and Low scale. Buy Score is attached to people, whereas Sell Score is attached to properties. When you see a Sell Score attached to an individual on the People tab of the Track page, that Sell Score corresponds to the latest known associated property for the person.
Note: Buy Scores are available only with our Success and Pro plans.
Predictive analytics uses 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.
The Buy Score ranks people based on which people are most likely to purchase property in the next year. People can have a Buy Score of High, Medium, or Low. The higher the score, the more likely an individual is to purchase property.
To identify a person's Buy Score, we reference hundreds of characteristics of millions of people nationwide. The following are the primary variables that affect the Buy Score:
- Attributes of properties owned by the individual (e.g., square footage, bedrooms/bathrooms, and current valuation).
- Individual's transaction history (e.g., number of properties owned, net equity, and mortgage/foreclosure history).
When any of these data points change, the Buy Score changes accordingly.
We calculate Buy Scores monthly to keep the scores as up to date as possible. Not every individual will see a difference with each Buy Score update.
An individual's Buy Score may change over time as we receive new or updated information. The Buy Score model is always changing and improving, so Buy Score changes are a good thing.
An individual with a High Buy Score is approximately 7 times more likely to purchase property in the next year than a randomly selected person.
What does this mean?
- High - The individual is in the top 5% of people that are likely to buy in the next year.
- Medium - The individual is in the next 25% of people that are likely to buy in the next year.
- Low - The individual is in the lower 70%, meaning the individual is less likely to buy in the next year than others with Medium or High Buy Scores.
The purpose of predictive analytics is to help you prioritize your time, so you can reach out to the right people with the right message. The Buy Score is a tool to help with prioritization. Because not everyone on your leads list will purchase a home within the next year, you can focus on individuals with higher Buy Scores to set yourself up for success.
Buy Score use cases
- Upload your contacts or sync your CRM to get Buy Score analytics on your sphere of influence (SOI).
- Invite your High Buy Score clients to Remine to engage with them directly in the platform.
- Filter for absentee properties and view property details to find and track associated people with High Buy Scores.
- Search for people in your SOI to see their Buy Scores so you can better prioritize your time.