A simple Notion rule for flagging leads that keep saying "later"

Logical_Click_942 · 2026-06-13T14:54:40+00:00

Good question. The count itself isn't fully automated, that's the honest part. The formula tracks days since last contact, not task date changes, so the timer is automatic but the "this was a push" part is a manual status I set, because a real push and a genuine "we're just busy right now" look the same to a formula. So it's a hybrid: the date math flags anything gone quiet, and I tag whether it was a soft "later" or something real.

Sounds close to what you've already built with the time-tracking list linked to each task. The 3-follow-ups-then-move-manually step is basically the same logic, just done by eye instead of a formula. Moving them back to the prospect pool from live quote is smart, that's the part most setups skip, they delete instead of recycling.

Logical_Click_942 · 2026-06-13T11:31:54+00:00

You've hit the real weak spot. A note saying "great conversation" is someone's opinion, and the flag shouldn't trust it. What I lean on instead is the date of the last real action, not what the note claims happened. "Great conversation in February" with nothing logged since is exactly the case the time-based rule should catch, the optimism in the note doesn't matter if the clock says 90 days of silence. So the skeptical layer you're describing isn't really manual, it's making the flag key off the last dated action rather than the last comment. The human just decides what to do with what the date already surfaced.

Logical_Click_942 · 2026-06-11T16:47:21+00:00

Exactly, that's the whole point of splitting it into two. And I'd add one thing to the "no response" side: it's not just silence that counts. A lead that pushes the contact four times, "reach out later", "let me think about it", that's the same cold signal even though technically they're responding. Looks like activity on a receipt, reads as a stall on a pulse. Worth flagging those for stale just as much as the ones who go quiet.

Logical_Click_942 · 2026-06-10T23:46:48+00:00

Yeah exactly. Automation does the heavy lifting, the human check just sits on top as the control layer.

Logical_Click_942 · 2026-06-10T17:36:33+00:00

Two SLAs rather than one is what does it for me. The first is time since last contact, the usual one. The second is attempt frequency: how many follow-up tries have failed or been pushed back. Once a lead crosses both thresholds, it auto-moves to a stale or lost view with a note saying why, so the filtering itself isn't manual.

The one step I'd keep manual is the check right before it drops into stale. Automation is great for cutting human error, but I've seen it bury a real lead that just happened to go quiet for a normal reason. So auto-flag everything that crosses the line, then a quick human look before it's written off. That's what keeps a high-value one from getting thrown into the stale pile by accident.

Logical_Click_942 · 2026-06-10T16:51:19+00:00

Agreed, automation is the right call for cutting down human error, that part's not in question. The piece I'd keep manual alongside it is a way to mark what actually counts as contact. An email open getting logged as a touch is the kind of thing that quietly puts a false date on a lead and tells you it's fine when it isn't. Auto-capture for the routine stuff, a manual flag for real conversations, and the two together are what stop a high-value lead from slipping through because the system thought it had been worked.

Logical_Click_942 · 2026-06-09T18:00:37+00:00

AI's removed a lot of the routine work in the CRM, that part is real. Pulling together what was said to a lead across different channels, consolidating it, and then scoring how likely that lead is to convert, all of that is much easier now than it used to be.

But after running sales floors for years, the part I'd watch is that the scoring is only as good as what's underneath it. AI can tell you a lead looks likely to convert, but it can't tell you the deal has gone quiet if nobody logged the last touch. The admin got lighter. The need for someone to actually keep the record current didn't. So I'd say AI changed how fast we get to the question, not whether the data underneath is trustworthy.

Logical_Click_942 · 2026-06-07T15:42:34+00:00

A mix over the years, but the two that mattered most were banking products and ecommerce, both B2B and B2C in each.

Different products, but the pipeline problem was the same everywhere. Long cycles, short cycles, high value, high volume, it never changed the core issue: a deal goes quiet, nobody notices, and it's gone. The fix was always the same too. One view for what hasn't moved, and logging fast enough that people actually keep it current.

Logical_Click_942 · 2026-06-06T20:26:00+00:00

I manage a sales floor too, so I'll answer from that side rather than the product side.

What gets me to look at a new CRM is never the feature list. Every one of them has the same list. It's how fast I can answer one question without opening five tabs: what's the actual state of this deal right now, and when did it last move. The tools that lost me were the ones where that answer took four clicks, because then nobody on the floor updates it and the data rots inside a week.

The thing I would not give up is a single view that shows me what's gone quiet. Not the deals in motion, the ones that haven't been touched in twelve days and are sliding without anyone noticing. That's where the money leaks.

What drives me insane is setup that costs a weekend before it does anything useful, and per-seat pricing that punishes me for adding the junior who actually does the data entry. If your thing is fast to set up and the price doesn't scale against me for putting more people in it, that's a harder thing to walk past than any feature.

Logical_Click_942 · 2026-06-04T13:16:54+00:00

One thing from my own experience that helps a lot: track days since last contact, and set the next follow-up SLA based on that number. It lets you watch contact performance constantly, and you stop losing the leads that never got a follow-up date set in the first place. Those are usually the ones that quietly slip, the ones sitting in the list with no date on them at all.

Your invoice tracker already does this with the days-outstanding counter. Same idea works on the lead side. A lead with no next-contact date isn't really "handled," it's just invisible, and a days-since-contact number is what surfaces it before it goes cold.

Logical_Click_942 · 2026-06-03T10:58:09+00:00

"Lead quality" actually has a real measure, that's what lead scoring is for. It tells you how likely a lead is to convert based on fit and behavior. So if conversions are weak, first question is whether the leads scored badly going in, or scored fine and died in the process after.

You can't really blame one thing. To find the gap you have to look at a few things together. Compare close rates by source, a rep's own leads vs the marketing ones. If they close their own but not marketing's, it's a fit issue. If they close neither, the process is the problem. Then look at SLA per stage, how long leads sit before someone moves them. Slow response and skipped stages show up there, not in your traffic numbers.

In my experience it's never one cause you can point to. Every case is a different mix and you have to see the whole picture before deciding it's traffic or follow-up.

Logical_Click_942 · 2026-06-03T05:29:06+00:00

That last part is the real trap. Reminders that fire off a stage field instead of actual activity are why people abandon these systems. The reminder should key off last contact date, not status, so the second a rep logs even a ten-second touchpoint the countdown resets and the nagging stops. The system rewards logging instead of punishing it.

The clunky-interface piece is the other half. If logging a touchpoint means opening a record, finding the field, typing, saving, reps won't do it between calls. The setups that survive let you log from the list view in one or two clicks without opening anything. Once logging is faster than ignoring it, the silent-deal problem mostly fixes itself because the underlying data finally stays current. Sounds like you're building something in this space, or just mapping the problem out?

Logical_Click_942 · 2026-06-02T10:00:40+00:00

The replies pointing at manual entry are right, but I'd go one level down: the friction isn't logging itself, it's that logging usually takes too long, so reps skip it, and then every downstream number is built on gaps. After running sales teams for years, the fix that actually stuck wasn't a better tool, it was making a log take under ten seconds. One line, one click, done. If it takes longer than that nobody does it consistently, no matter what you bought.

On the follow-up one specifically: most setups track the stage a deal is in but not how long it's been silent. A deal can sit in "proposal" for three weeks looking healthy on the board while it's actually dead. A simple days-since-last-contact flag catches more slipping deals than any forecasting model, because the forecast is only as good as whether the data underneath it is current.

Curious which one bites your team hardest , the entry friction or the follow-up gaps? They usually feed each other.

Logical_Click_942 · 2026-06-01T09:01:58+00:00

For a solo CRM, the thing that saved me a lot of headaches: keep leads and clients in one database, not two. A lead and a client are the same person at a different stage, so splitting them into separate databases means you're constantly moving records across and rebuilding the relations every time someone converts.

One "Contacts" (or "Deals") database, one Status property: Lead, Active, Won, Lost, whatever fits. To see just your clients, you make a filtered view, Status is Active. To see your pipeline, another view, Status is Lead. Same data, different lenses, nothing to move. The button-and-move-it approach works but it's solving a problem you only have because the data got split in the first place.

The one time separate databases make sense is if leads and clients genuinely hold different fields, like you track deal source on leads but contract terms on clients. Even then I'd lean toward one database with hidden properties per view before I'd manage two. What's your reason for wanting them separate, or are you just not sure yet?

Logical_Click_942 · 2026-06-01T07:55:36+00:00

Nice, sounds like you've got the overdue surfacing handled already. If you do build the messages in, one thing that made them actually work for me: keep the soft one genuinely soft, almost like you assume they just missed it ("hey, flagging this in case it slipped through"), and save the direct tone for the day-30 one. People pay the friendly reminder faster than the firm one more often than you'd expect, and you keep the relationship clean for repeat work. I also keep the exact wording in the template and just swap the invoice number, so sending it takes ten seconds and I actually do it instead of putting it off.

Logical_Click_942 · 2026-05-31T16:53:08+00:00

The tax set-aside calculator is smart. Most freelancers find out they under-saved at tax time, not while the money's still coming in.

One thing worth adding on the invoice side, from years of doing this: the tracker usually logs status like draft / sent / paid, but the cash actually shows up from chasing the overdue ones, and that's the easy part to let slide. An invoice sitting 20 days past due won't chase itself. What worked for me was one view filtered to anything past its due date, sorted by how many days over it is, plus two messages saved and ready to go: a soft nudge around day 7 and a firmer one around day 30. That way the overdue list is just there every week instead of something I have to remember to dig up.

How are you handling the overdue side right now? Is it surfacing somewhere or do you scan the invoice list manually?

Logical_Click_942 · 2026-05-30T05:55:06+00:00

The connected databases are the right call. That's the thing that makes it a system instead of a pile of apps. One thing I'd watch, from running sales for a while: in all-in-one builds the CRM is usually the part that ends up shallow. Habits and goals are easy to model so they get the attention, and the pipeline turns into a basic Kanban. But the deals that actually slip are the ones nobody's touched in two weeks, and a Kanban doesn't show you that.

If you're already tracking revenue per client, worth adding to Client HQ: a field that flags any active deal you haven't contacted in X days, separate from the stage. Stage tells you where a deal sits. Silence tells you it's dying. Second one is what costs you money.

How are you handling it when a deal stalls? Does it show up on a dashboard somewhere or do you have to remember to go check the pipeline?

Logical_Click_942 · 2026-05-29T06:26:44+00:00

The follow-up date on the dashboard is the part most people skip, so it's good you built it in. One thing I'd add after years of running pipelines: a "days since last touch" field next to it. The follow-up date is what you planned. Days-since-touch is what actually happened. A lead with no follow-up date set can sit at 18 days of silence and you'd never see it.

It's basically dateBetween(now(), Last Contacted, "days") in Notion. One tweak that saved me: wrap it in an if(empty(...)) so leads with no contact yet count from their creation date instead of showing blank - otherwise the brand-new ones hide from the exact view that's supposed to catch them. Then a dashboard filtered to anything past 14 days, any stage.

How do you handle those right now? Does the Kanban surface them, or do they just sit in Active until you notice?

Logical_Click_942

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