Would you test something that improves connection rates on your lists?

Question

Hi everyone...

I’ve been spending the last few weeks digging into outbound workflows—specifically why some lists perform significantly better than others, even when they look similar on paper.

Across a few conversations here, a common theme keeps coming up:

*good filters don’t guarantee conversations

*timing matters more than expected

*and a lot of time still gets spent on leads that never connect

I’ve been working on a way to prioritize lists before they hit the dialer—focused on surfacing the leads most likely to actually pick up and engage early.

Still testing it on real datasets, but early results have been interesting in terms of improving connection efficiency.

Curious—would anyone here be open to running this on a sample list and comparing results against how you’re currently working your data?

Chris Arnold · Answer

@Carson Nordmann

That’s a good distinction—and I agree they behave differently.

Connection definitely leans more on data quality and timing, while conversation depends a lot more on actual intent behind the lead.

What I’ve been seeing though is that in practice those two tend to overlap more than expected—some leads consistently show higher pickup and stronger engagement patterns, even within the same lists.

So the approach I’ve been digging into isn’t really blending them into one metric, but looking at both sides together to improve who gets engaged first.

Not perfect, but it seems to help reduce the amount of time spent on leads that don’t move forward at all.

Curious—have you found it more effective to optimize those separately, or do you see value in combining signals when it comes to prioritization?

Carson Nordmann · Answer

Connection rate and conversation rate are two different problems and worth separating before you build. Connection is mostly phone data quality and dial timing. Conversation is list intent. A tool that mixes them tends to underperform on both.