How are you deciding who to call first on your lists?

Question

I’ve been digging into the outbound side of real estate investing lately—specifically how people are working through lead lists.

One thing I keep noticing is that most skip tracing just returns data… but doesn’t really help answer the bigger question:

Who should you actually call first?

From what I’ve seen, a lot of teams end up dialing straight down a list without much prioritization, even though some leads are clearly better than others (based on things like vacancy, equity, ownership, etc.).

I’ve been working on a way to take a standard property list and layer in:

○ contactability (how reachable someone actually is)

○ motivation signals (equity, absentee, distress, etc.)

○ and a simple “call-first” ranking

The goal is just to turn a raw list into something more actionable for whoever is doing the calling.

Curious how others are handling this right now—

Are you guys prioritizing your lists in any structured way, or mostly just working through them top to bottom?

Chris Arnold · Answer

That’s a solid way to look at it—the combination of equity and real-world distress signals is where the deals are.

And I agree, skip tracing by itself doesn’t tell you much beyond how to reach someone. The motivation side is really what determines whether the conversation goes anywhere.

What I’ve been seeing though is even when you’ve got strong indicators like vacancy or absentee ownership, a lot of teams still end up spending time on leads they can’t actually get on the phone with.

That’s the piece I’ve been digging into—taking those same motivation signals you mentioned and layering in contactability so the top of the list isn’t just “good on paper,” but also more likely to actually turn into a conversation.

Curious—once you’ve identified those types of properties, are you just working through them in order, or doing anything to prioritize within that group?

Jacob Camhi · Answer

Love this question. You are right, most people just start at the top of a CSV and wonder why it feels so random.

The simple version of what you are describing is just putting a little scoring system around two buckets: how likely they are to need you, and how likely you are to actually reach them. On the motivation side that usually looks like points for things like high equity, absentee, length of ownership, clear distress signals, recent change like inheritance or eviction, and maybe property condition or code issues if you have it. On the contactability side it is things like number of unique numbers, phone quality, presence of email, and whether you have multiple ways to reach the same person.

In practice, the teams I see doing this well keep it really simple for the callers. They roll all that into a score behind the scenes, then surface it as an A, B, C priority or a basic rank and tell the dialers “start with A’s, then B’s.” The magic is not in picking the perfect formula on day one, it is in looping your call results back into the scoring. After a few weeks you can see which traits are actually showing up in your real deals, tweak the weights, and keep making the list a little smarter each time instead of just grinding straight down the spreadsheet.

Chris Arnold · Answer

That’s a great breakdown—and I like how you separated motivation and contactability. That’s exactly the two buckets that seem to matter most in practice.

And I agree 100% on keeping it simple for the callers. If it doesn’t translate into something like A/B/C or a clear call order, it usually doesn’t get used consistently.

The feedback loop piece you mentioned is interesting too—that’s something I don’t see a lot of teams actually doing, even though it probably has the biggest long-term impact.

What I’ve been focused on is taking that same concept and just trying to standardize the front end a bit—so instead of each team building their own scoring logic, there’s a consistent way to surface the strongest leads right away based on those same signals.

Curious—are you actively feeding call outcomes back into your scoring, or is it more of a static model right now?

Chris Arnold · Answer

Yeah that makes sense—once you get into actual operations it’s way more than just having a list. It’s training, tracking, and hitting numbers consistently.

What I’ve been seeing is even with solid systems in place, a lot of teams still lose time on the front end—calling numbers that don’t connect or leads that technically fit the list but aren’t really in a position to move.

The piece I’ve been focused on is just tightening that front end a bit—taking those same lists and helping surface the people most likely to actually engage so the callers are spending more time in real conversations.

Not replacing the process at all, just trying to make the input into it a little more efficient.

Do you guys track connection rate or contact rate by list or by caller?

Chris Arnold · Answer

@Ken M.

That makes a lot of sense—especially staying local and working direct. Hard to argue with that kind of spread.

And yeah, the buckets you mentioned—probates, tired landlords, liens—that’s exactly where the opportunity is.

What I’ve been noticing is once you’ve got those stacked lists, a lot of teams still end up spending time dialing through leads that either don’t pick up or aren’t really in a position to move.

That’s the piece I’ve been focused on—taking those same categories and layering in things like contactability and a few additional signals to help surface the ones most likely to actually engage, not just fit the criteria.

Curious—once your team starts calling, are they just working top-down within those stacks, or do you have another way of prioritizing who gets hit first?

Chris Arnold · Answer

@Ken M.

Yeah, stacking is a solid approach—that’s actually what got me thinking more about this.

What I’ve noticed is that a lot of people either:

• aren’t stacking at all, or
• are doing it manually or based on just a couple variables

What I’ve been working on is taking that idea a step further by combining:

• contactability (how reachable the numbers actually are)
• motivation signals (equity, absentee, vacancy, etc.)
• and then rolling it into a simple “call-first” ranking

So instead of just sorting by one or two filters, it tries to surface the strongest overall opportunities at the top.

Curious—what variables are you usually prioritizing when you stack your lists?