How Lead Scoring Helps Real Estate Investors Find the Best Leads & Close More Deals

Hey, I’m Jamie! I’ve been a professional digital marketer since 2010 and have spent a ton of time building lead scoring models over my career. So let me tell you all about lead scoring, how it’s useful, why it’s important, and how to set it up in a way that actually works for you. (Plus, I’ll share a template so you can build your own lead scoring matrix!)

Key Takeaways

  • Lead scoring rates how well new leads fit your ideal customer profile based on their activity and details about the opportunity.  
  • Lead scoring helps you quickly identify the best leads, telling you where to focus your time and resources for the best chance of closing lucrative deals.
  • Real estate investors should use lead scoring to identify the most motivated sellers. You can do lead scoring manually with a spreadsheet or use an AI lead scoring tool.

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Why Real Estate Pros Should Use Lead Scoring

Professional marketers have used lead scoring for years, particularly at B2B companies. It’s one of the ways we decide who the sales team should spend time reaching out to. Put simply, lead scoring is a way to rate how well new leads fit your ideal customer profile based on their activities and details about the opportunity. 

Real estate investment teams with high lead volume should definitely use lead scoring to prioritize the most promising leads. Without lead scoring, you’re likely treating each new lead the same when they, quite frankly, are not. This leaves you vulnerable to wasted time and missed opportunities. Not only does lead scoring tell your team which leads to focus on first, it also helps with lead distribution. Give higher score (more promising) leads to your more experienced managers to ensure deals are done quickly before someone else locks it up. Lower score leads can be routed to newer managers or assigned to AI outreach tools that collect additional information for you while your team focuses elsewhere.

Even investors with more manageable lead volume can use lead scoring to decide which leads to follow up with first or more aggressively. If someone isn’t a good fit for your business or isn’t likely to turn into a deal, it’s not wise to spend the same amount of time, energy, and effort trying to close them. A low lead score tells you this quickly,

Lead scores change over time based on the lead’s engagement and the intel you collect. This tells you if a particular lead is turning into a stronger opportunity or is becoming less promising. Working with up-to-date lead scores ensures you stay focused and don’t waste your time. If you’re doing lead scoring manually, be sure to update the score each time you gather new information. If the lead stops responding, this should also negatively impact their score. If you use an AI lead scoring tool, the score automatically updates over time and as new information is added to the opportunity. 

Essentially, without lead scoring you’re flying in the dark or spending too much time manually reviewing each opportunity to identify the best ones. Focusing only on the best-fit leads helps you close more deals and stop wasting time.

What Criteria to Use for Real Estate Lead Scoring

Customize your lead scoring algorithm based on what you find most valuable. If you already have a defined Ideal Customer Profile, great! If not, take a second to jot down the attributes your perfect lead would have — the one that is a slam dunk deal that you’d love to see come through your pipeline.

Do you have an ideal:

  • Seller/buyer motivation
  • Closing timeline/urgency
  • Ownership type
  • Decision maker
  • Property condition or location
  • Occupancy status
  • Lead source (e.g. PPC versus cold calling)

Don’t forget to factor in less concrete criteria that nevertheless impact a lead’s willingness or ability to make a deal, like how responsive they are to your communications and if you know (or suspect) you’re not the only investor they’re speaking to. While these are harder to measure, they can have a big impact on opportunity potential. 

These are just some examples of lead scoring criteria you can build into your model. You can make it as complex or as simple as you’d like based on your “buy box.” If you’re practicing manual lead scoring, I recommend keeping things simple so it’s easier to maintain as you gather new information.

Want help planning your lead scoring matrix? This free Real Estate Lead Scoring Template is an interactive worksheet you can use to build your customized manual or AI lead scoring models.

Over time, as you gain a better understanding of what makes a good or bad lead for your business, refine your scoring matrix. 

Note: Be cautious of lead scoring programs that decide your scoring criteria for you. They often claim they analyze your deals to identify the most important factors and commonalities. But without full control over your lead scoring algorithm, you can’t ensure leads with a high score are truly a good fit. If you decide to change your business focus, these “smart” AI scoring models need time to adjust, meaning your lead scores are blatantly incorrect until they catch up.

How to Set Up Lead Scoring

In the most manual way, you can use a spreadsheet for lead scoring. Add all your criteria in the first column and define how you’ll score each value (our lead scoring template has this pre-setup for you). You can manually enter the values each time or build dropdown options to keep scoring consistent. Then use the SUM function to add up the individual scores to get a total. 

If you’re lead scoring on a spreadsheet, I recommend using a single document to track scores for all your leads. This allows you to easily see which leads have the highest scores for outreach prioritization. You can even set conditional formatting to color-code leads based on their score (this feature is already built into the lead scoring template linked above).

Every time you get a new lead, give them their own column in the spreadsheet and set their initial scores. Whenever you gather more information, adjust the relevant scores. You may want to add an additional row to keep track of their most recent lead score before adjusting any values so you can see if the score goes up or down.

As you can see, this can be a tedious process to do manually and is vulnerable to scoring discrepancies because of user error or forgetfulness.

AI lead scoring takes a little bit of upfront work (and an occasional tweak as you refine your process), but once the setup is done scoring is handled for you. Any time new information is gathered, the score updates. You don’t need to do anything special and there’s no risk of forgetting.

I wouldn’t have identified the hottest leads without CarrotCRM’s AI lead scoring.

We have hundreds of leads coming in every single week. … Thanks to CarrotCRM, I can see the hottest leads we have. I wouldn’t have identified some of these leads if we didn’t have AI lead scoring.

– Kyler Peters

Want to Sell Now

Kyler Peters, Carrot customer

AI lead scoring also allows you to add another layer of nuance to your sources — attribute weight. Does urgency, motivation, or property condition matter more to you than lead source or occupancy status? With AI lead scoring, you can tell the algorithm that some attributes are more important than others and should account for a larger percentage of the overall score. 

With manual lead scoring, if you have 10 attributes, each accounts for 1/10th of the total score (unless you want to get into some seriously complicated spreadsheet formulas). But with AI lead scoring, you can tell the algorithm that seller motivation should account for 20% of the overall score while lead source is only 6%. So a high seller motivation score will drive the total score up while a high lead source score won’t have much impact on the total. This allows you to index off what matters most to you.

There’s a worksheet for mapping out your AI lead scoring algorithm in the Lead Scoring Template, or you can build it directly in CarrotCRM’s AI Lead Scoring settings.

Focus Where it Matters

Lead scoring is a tried and true tool that marketing and sales teams have long trusted to identify the most promising leads. It’s not always perfect, but it can be a game changer, especially if you find yourself chasing bad leads. 

Sophisticated real estate investors understand this and have adopted lead scoring in their real estate CRMs. The good news is you don’t have to be a high budget investor to use lead scoring! You can do it manually, or you can turn on AI lead scoring with a CarrotCRM account starting at just $69/month. AI usage is pay-as-you-go, so there’s no need to make a high value commitment!

No matter your lead volume, lead scoring keeps you focused and helps flush out the trash early, giving you more time to work better deals. And in the numbers game of real estate investing, time matters.

Jamie Saine

Jamie has spent the past 15+ years as a content and product marketer, helping companies rank well and build trust online. She specializes in deep research, producing a range of helpful media, and translating technical jargon and complex topics into something anyone can understand.

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