Asked chatgpt and perplexity the same 100k questions, they agreed on 11% of the sources
▲ 2 r/GEO_optimization+2 crossposts

Asked chatgpt and perplexity the same 100k questions, they agreed on 11% of the sources

Ranked #1 on google, never cited by chatgpt or claude, that complaint again today from someone in this sub, and it's not a content problem people mostly get told it is.

profound ran the same 100k prompts through chatgpt and perplexity and checked which domains got cited in each, 11% overlap, that's it. chatgpt cited a domain perplexity never touched 37.4% of the time, perplexity did the same back 51.6% of the time. across their wider dataset every engine pair lands somewhere between 6% and 16.4% overlap, none of them get close to half. if you're cited in one you're probably invisible in another, same question, same day.

ranking still matters though, just not as much as people assume, and not the same amount in every engine. airops mapped 548k pages chatgpt retrieved against actual google rankings, #1 in google got cited by chatgpt 43.2% of the time, 3.5x the rate of anything outside google's top 20. real lift, just not a guarantee, chatgpt only cited 15% of everything it retrieved total.

Freshness is the other one nobody flags. ahrefs pulled 17 million citations across 7 platforms, ai assistants cite content 25.7% fresher than organic google on average, chatgpt specifically runs 458 days newer than organic. google's own ai overviews is the outlier, cites content 16 days OLDER than organic, the only one with no freshness bias at all. whatever refresh cadence you're running for ai overviews is roughly half as aggressive as what chatgpt actually rewards.

so treating "ai visibility" as one score is the actual mistake, not the content. you could be cited in 40% of chatgpt answers and 0% of perplexity answers and the average still looks fine while half your buyers never see you. anyone here actually tracking citation rate per engine separately or is everyone still averaging it into one number?

Sources:

u/Dictator_0007 — 14 days ago

Why your warmup dashboard can say you're clean while you're still landing in spam

Saw two threads here this week that are really describing the same problem from two different angles. One was a mailbox landing in spam even though everything looked fine on paper. The other, posted today, is someone running 5 identically configured inboxes, same provider, same warmup settings, same limits, and one of them shows 132 warmup emails received, 71 sent, 15 of those saved from spam, while the other four look completely normal.

I ran into this myself across 12 domains and 36 mailboxes. Warmup dashboards stayed clean the whole time, nothing flagged, nothing red. What actually tipped me off was real replies drying up, not the dashboard. Once that happened I ran an actual seed test into real Gmail/Outlook addresses and it landed in spam. Ran a second, different seed test just to make sure it wasn't a fluke, same result both times. That's when I started running seed tests as a biweekly process instead of trusting the warmup score on its own.

The thing that trips people up is treating the warmup score and real inbox placement as the same measurement. They're not. A warmup dashboard is scoring you inside the tool's own warmup network, other inboxes running the same tool, generally established, generally cooperative, opening and replying to each other on purpose because that's the whole point of the network existing. It's a curated, closed network by design. Gmail and Outlook deciding where your actual cold email lands is a completely different system, built off real recipient behavior, complaint rates, and domain/IP reputation from actual sending history, not from friendly warmup traffic.

So a mailbox can look basically clean on the warmup dashboard and still get flagged by real Gmail users, because the warmup network never had a reason to spam-report you and real recipients do. It runs the other way too, a mailbox with a rougher-looking warmup score can still land fine in real inboxes, because the two signals were never actually correlated the way the dashboard makes it look.

If you're staring at a number like that 15 out of 71, that's the more useful data point of the two, not the received count, because it's telling you a chunk of your own warmup peers already isn't trusting that inbox, before you've sent a single real cold email. Worth treating a ratio like that as a reason to pull the mailbox and check its IP and blacklist history specifically, rather than assuming more warmup days will fix it. More time inside the same closed loop doesn't touch whatever's actually wrong on the real-inbox side. In my case the fix wasn't more warmup time either, it was catching it through seed tests and dealing with the actual mailbox.

Anyone else running seed tests against real Gmail/Outlook addresses alongside their warmup score on a regular cadence, or is most people here still trusting the dashboard on its own?

reddit.com
u/Dictator_0007 — 19 days ago

Why your warmup dashboard can say you're clean while you're still landing in spam

Saw two threads here this week that are really describing the same problem from two different angles. One was a mailbox landing in spam even though everything looked fine on paper. The other, posted today, is someone running 5 identically configured inboxes, same provider, same warmup settings, same limits, and one of them shows 132 warmup emails received, 71 sent, 15 of those saved from spam, while the other four look completely normal.

I ran into this myself across 12 domains and 36 mailboxes. Warmup dashboards stayed clean the whole time, nothing flagged, nothing red. What actually tipped me off was real replies drying up, not the dashboard. Once that happened I ran an actual seed test into real Gmail/Outlook addresses and it landed in spam. Ran a second, different seed test just to make sure it wasn't a fluke, same result both times. That's when I started running seed tests as a biweekly process instead of trusting the warmup score on its own.

The thing that trips people up is treating the warmup score and real inbox placement as the same measurement. They're not. A warmup dashboard is scoring you inside the tool's own warmup network, other inboxes running the same tool, generally established, generally cooperative, opening and replying to each other on purpose because that's the whole point of the network existing. It's a curated, closed network by design. Gmail and Outlook deciding where your actual cold email lands is a completely different system, built off real recipient behavior, complaint rates, and domain/IP reputation from actual sending history, not from friendly warmup traffic.

So a mailbox can look basically clean on the warmup dashboard and still get flagged by real Gmail users, because the warmup network never had a reason to spam-report you and real recipients do. It runs the other way too, a mailbox with a rougher-looking warmup score can still land fine in real inboxes, because the two signals were never actually correlated the way the dashboard makes it look.

If you're staring at a number like that 15 out of 71, that's the more useful data point of the two, not the received count, because it's telling you a chunk of your own warmup peers already isn't trusting that inbox, before you've sent a single real cold email. Worth treating a ratio like that as a reason to pull the mailbox and check its IP and blacklist history specifically, rather than assuming more warmup days will fix it. More time inside the same closed loop doesn't touch whatever's actually wrong on the real-inbox side. In my case the fix wasn't more warmup time either, it was catching it through seed tests and dealing with the actual mailbox.

Anyone else running seed tests against real Gmail/Outlook addresses alongside their warmup score on a regular cadence, or is most people here still trusting the dashboard on its own?

reddit.com
u/Dictator_0007 — 19 days ago

Why your warmup dashboard can say you're clean while you're still landing in spam

Saw two threads here this week that are really describing the same problem from two different angles. One was a mailbox landing in spam even though everything looked fine on paper. The other, posted today, is someone running 5 identically configured inboxes, same provider, same warmup settings, same limits, and one of them shows 132 warmup emails received, 71 sent, 15 of those saved from spam, while the other four look completely normal.

I ran into this myself across 12 domains and 36 mailboxes. Warmup dashboards stayed clean the whole time, nothing flagged, nothing red. What actually tipped me off was real replies drying up, not the dashboard. Once that happened I ran an actual seed test into real Gmail/Outlook addresses and it landed in spam. Ran a second, different seed test just to make sure it wasn't a fluke, same result both times. That's when I started running seed tests as a biweekly process instead of trusting the warmup score on its own.

The thing that trips people up is treating the warmup score and real inbox placement as the same measurement. They're not. A warmup dashboard is scoring you inside the tool's own warmup network, other inboxes running the same tool, generally established, generally cooperative, opening and replying to each other on purpose because that's the whole point of the network existing. It's a curated, closed network by design. Gmail and Outlook deciding where your actual cold email lands is a completely different system, built off real recipient behavior, complaint rates, and domain/IP reputation from actual sending history, not from friendly warmup traffic.

So a mailbox can look basically clean on the warmup dashboard and still get flagged by real Gmail users, because the warmup network never had a reason to spam-report you and real recipients do. It runs the other way too, a mailbox with a rougher-looking warmup score can still land fine in real inboxes, because the two signals were never actually correlated the way the dashboard makes it look.

If you're staring at a number like that 15 out of 71, that's the more useful data point of the two, not the received count, because it's telling you a chunk of your own warmup peers already isn't trusting that inbox, before you've sent a single real cold email. Worth treating a ratio like that as a reason to pull the mailbox and check its IP and blacklist history specifically, rather than assuming more warmup days will fix it. More time inside the same closed loop doesn't touch whatever's actually wrong on the real-inbox side. In my case the fix wasn't more warmup time either, it was catching it through seed tests and dealing with the actual mailbox.

Anyone else running seed tests against real Gmail/Outlook addresses alongside their warmup score on a regular cadence, or is most people here still trusting the dashboard on its own?

reddit.com
u/Dictator_0007 — 20 days ago

The mailbox warmup lessons we only learned after tanking one

15 sends per mailbox per day, five days a week, is the number we settled on, and we only got there the hard way, we lost a mailbox even after two weeks of warmup. Ramped volume up right after those two weeks ended, treating that as proof the domain was solid, and it wasn't, it never recovered enough to trust again, we retired it rather than keep trying to rehab it.

What changed after that: every new domain gets treated as unproven no matter how clean the DNS setup looks on paper, or how long the warmup ran. Volume ramps up gradually over weeks, not days, and any mailbox that fails an inbox placement test under about 90% gets pulled from sending until it passes a retest, warmup period or not.

The domain choice itself turned out to matter as much as the ramp schedule. A brand new custom domain with zero history needs real time to build trust before you can send volume through it. A pre-warmed domain skips that wait, but you're trusting someone else's warmup process instead of your own, worth knowing which trade-off you're actually making before you pick one.

Anyone else had to retire a mailbox instead of rehab it? Curious what recovery actually looked like for people before they gave up on one.

reddit.com
u/Dictator_0007 — 28 days ago
▲ 3 r/SalesOperations+1 crossposts

Cut our outbound tool spend by ~79% without losing any capability

We finally sat down and audited every tool in our multi-channel outbound stack, from prospecting right up to email warm-up platforms. Total fixed monthly spend dropped from around $1,989 to $417.

Five tools got cut entirely: ElevenLabs, Sending.ac, Saleshandy, LeadMagic, and Hunter. Most of these were overlapping with something else already in the stack, doing some version of the same job. That overlap was the real issue, not just the cost; having 2-3 tools solve the same problem made it harder to standardize and connect everything cleanly through API/MCP for our automations.

Two tools weren't cut but got renegotiated hard: Apify had a usage-based pricing spike we hadn't caught until the audit, and Apollo, we were paying for far more volume than we actually needed. Five tools stayed exactly as they were: HubSpot, Instantly, Zapmail, Unipile, and SalesMsg, no overlap, each doing a job that nothing else in the stack covered.

Curious if others have gone through the same exercise. Are you trending toward fewer, more standardized tools, or still running best-of-breed per category?

reddit.com
u/Dictator_0007 — 1 month ago