Understanding Investor Score

When you run an investor search, Deal Run can return dozens or even hundreds of investors who have purchased properties near your deal. Not all of those investors are equally likely to buy your property. A landlord who bought one rental five years ago in the next zip code is a very different prospect from a flipper who bought three houses on the same street last month.

Investor Score is Deal Run's proprietary scoring algorithm that ranks every investor in your search results based on how well they match your specific deal. Instead of sorting by a single dimension like distance, Investor Score evaluates five independent factors and combines them into a composite score that tells you who to call first.

Why Investor Score matters

The difference between a good buyer list and a great buyer list is not the number of names on it -- it is the order in which you work through it. If you call the 50th-best match before the 1st-best match, you are wasting time and burning through your energy on lower-probability conversations.

Traditional buyer-finding tools give you a list sorted by distance or alphabetically. That tells you nothing about buying intent. Investor Score brings together multiple signals that, combined, predict which investors are most likely to make an offer on a property like yours. The result is a ranked list where the investors most likely to buy appear at the top -- so you spend your time calling the right people first.

The five Investor Score factors

1. Proximity

How close the investor's previous purchases are to your deal address. Proximity is the single strongest predictor of buying interest because real estate investing is fundamentally local. Investors develop relationships with contractors, title companies, and property managers in specific neighborhoods. They understand the rental demand, the school districts, the appreciation trends, and the buyer pool for resale. An investor who has bought three properties within half a mile of your deal knows that micro-market better than anyone -- and they are far more likely to act quickly because they do not need to do extensive due diligence on an area they already operate in.

Investor Score rates proximity on a gradient rather than a hard cutoff. Closer investors score higher, but investors further out are not excluded -- they simply rank lower if all other factors are equal.

2. Recency

How recently the investor made their last purchase. Recency captures buying momentum. An investor who closed on a property two weeks ago is demonstrably in active acquisition mode -- they have funding available, their contractor crew has availability, and they are actively looking for the next deal. An investor whose last purchase was 18 months ago may have shifted focus, run out of capital, or paused operations for personal reasons.

Recent purchases contribute more to the score than older transactions. This does not mean older investors are excluded from results -- they still appear, but they rank lower than investors with recent activity, all else being equal.

3. Price match

Whether the investor buys properties at a similar price point to your deal. Price match is critical because most investors operate within a defined budget range. A flipper who buys $80,000-$120,000 properties in C-class neighborhoods is unlikely to be interested in a $450,000 property in a gated community, even if it is two blocks away. Conversely, an investor who buys $300,000-$500,000 properties is unlikely to chase a $50,000 property in a war zone.

Investor Score compares an investor's typical purchase price range to your deal's anticipated price point. The closer the match, the higher the score. Reasonable variance is accounted for -- an investor who typically buys at $150,000 would still score well for a $175,000 deal, but would score poorly for a $500,000 deal.

4. Property match

Whether the investor buys the same type of property as your deal. Some investors specialize exclusively in single-family residential. Others focus on small multifamily (duplexes, triplexes, quadplexes). Some buy townhouses. A few buy across multiple categories. Property match ensures that an investor who has bought ten single-family homes is ranked higher for your single-family deal than an investor who exclusively buys duplexes.

This factor also considers property characteristics beyond the basic type. The algorithm looks at the overall pattern of what an investor buys, not just the most recent transaction.

5. Activity level

How many properties the investor has purchased during the lookback period. Activity level is a volume metric that separates serious, full-time investors from people who bought one rental property and may or may not be looking for another one.

An investor with 12 purchases in the last two years is running a real acquisition operation. They have systems for funding, renovation, and disposition. They can evaluate a deal quickly, make a decision, and close. An investor with 1 purchase in the last three years may have been a one-time buyer who is not actively seeking deals.

The scoring distinguishes between occasional buyers and active investors. Crossing the threshold from one-time buyer to repeat investor is the most meaningful behavioral signal.

How the composite score works

Each factor is scored independently, then combined into a proprietary weighted composite. The composite score determines the sort order of your results -- the investor with the highest Investor Score appears first.

The composite score is displayed on each investor card as a percentage. A score of 92% means this investor matches your deal on almost every dimension. A score of 45% means there is some match but significant gaps on one or more factors.

How to use Investor Score in practice

Investor Score is designed to save you time by putting the highest-probability buyers at the top of your list. Here is how to make the most of it:

• Start at the top. The first 10-15 investors in your results are almost always your best prospects. Call or text them first before working further down the list.
• Pay attention to score clusters. If your top 5 investors all score above 85% and then there is a drop to 55%, that gap is meaningful. The top cluster are your strongest matches by a significant margin.
• Use scores to prioritize, not to exclude. An investor with a 40% Investor Score is still someone who has bought property near your deal. They may have a lower score because they typically buy at a different price point, but they might be expanding their range. Do not ignore them entirely -- just call them after you have worked through your higher-scored prospects.
• Compare scores across searches. If you run a search and your top investor scores 95%, your deal is in a hot area with highly active buyers. If your top score is 55%, investor activity near your deal is thinner, and you may want to expand your search radius to find more matches.

Investor Score vs. competitors

Most competing platforms either do not rank investors at all (you get an unsorted list) or sort by a single factor like distance. Platforms with comparable scoring charge $249/month or more and often lack built-in outreach tools.

Deal Run's Investor Score provides multi-factor scoring at $99/month -- the same analytical rigor at a fraction of the cost, with skip tracing and outreach built in.

Frequently asked questions

Can I see the breakdown of each factor?

Currently, Investor Score displays a composite score on each investor card. The individual factor breakdown is visible when you expand an investor's profile or click into their portfolio deep dive.

Does Investor Score improve over time?

Yes. The scoring algorithm uses the most current public record data available. As investors make new purchases, their recency and activity scores update automatically. This means your results are always based on the latest transaction data, not a stale snapshot.

Does Investor Score consider my previous deals?

In the current version, the Investor Score evaluates each search independently based on the deal address you enter. Future updates will incorporate your deal history to further personalize rankings -- for example, boosting investors who have already bought from you or expressed interest in previous deals.