Reports/Report 1
Run · Jul 27Sources X 10 · Reddit 0

Report 1 — Fathom AnalyticsPublished today

One run, told in four chapters. WarmList collected 146 posts from X, threw away 135 of them, scored the 10 that survived, and put 5 people in front of you. Every number below is followed by the evidence it came from.

Back to Overview

How this run narrowed down

The four chapters below, in one line — each step links to its evidence.

Collected146 100%Chapter 01 · 10 queriesPassed screening128 88%Chapter 02 · 18 removed, rule by ruleScored as candidates10 7%Chapter 03 · 5 hot · 5 near-miss · 1 watchReady to contact5 3%Chapter 04 · hot × contact-safe

Collected

What this run went looking for, and everything it dragged back before a single judgement was made.

146posts collected from 10 queries

The 10 queries that ran

Built from usefathom.com, searched on X. 4 produced candidates, 6 came back empty.

Search queryLeadsHotShare
bot traffic analytics5250%
hate Google Analytics2120%
need simple analytics2120%
GA4 is confusing1110%
6 queries found nothing00—

One query, bot traffic analytics, produced 5 of the 10 candidates and 2 of the 5 hot leads. The 6 empty queries are the cheapest thing to change before the next run.

Run scope

The reach behind the 146.

Run
Jul 27
Product
usefathom.com
Sources
X
Search queries
10 built from your site
Posts collected
146
Candidate posts span
May 26 – Jul 27

When the 10 posted

Candidate posts per week across the 9-week span.

May 26Jun 23Jul 21
Candidate posts per week
Week ofCandidates
May 261
Jun 20
Jun 90
Jun 160
Jun 230
Jun 301
Jul 70
Jul 142
Jul 216

8 of 10 candidates posted in the final two weeks — this report is mostly fresh complaint, not archaeology.

146 collected− 18 screened out=128 passed screening

Cleaned

The part of the run you never see. 135 posts were thrown away in two passes — here is which rule removed each batch.

128passed screening · 18 removed before scoring

Noise removed

All 146 collected posts, by what happened to them.

135removed for you · 117 low-fit · 18 screened
146 collected10 candidates
Low-fitScored, but landed below the candidate bar. Removed after scoring.117
Screened out before scoringNever worth a scoring call.Company accounts 9Promotional posts 4Other rules 518
Watch-onlyReal pain, flagged do-not-contact — market intel, not an outreach target.1
Survived to Chapter 03The candidates you actually read.10

The cut happens in two passes: 18 screened out before scoring, 117 more after. Near-misses are not counted as noise — all 5 are still in Chapter 03, one condition away from hot.

Inside the 18

What the pre-scoring screen removed, and what reached the scorer.

 Collected from X146
−Company accountsBrand or product accounts, not a person with the problem.9
−Promotional postsSomeone selling, not someone hurting.4
−Other pre-scoring removalsThe balance of the screening total. The run counts these in its screening figure without itemising them by rule.5
=Reached the scorer128

The run keeps a count per rule, not the handles behind them — so this chapter names the rule that fired, never the account it removed.

128 passed− 117 low-fit− 1 watch-only=10 candidates

Chosen

10 posts scored against your rubric. The category decides what you do with each one; the score out of 90 is the evidence behind the category.

10candidates · 5 hot · 5 near-miss · 1 watch alongside

The full slate

All 10 candidates, ranked, each with the 90-point bar that produced its score · the rule marks the hot floor of 60.

#PersonFound byScore compositionCategoryScore
1Ben Otero@benoteroGA4 is confusinghot76/90
2Kévin Miguet | CRO for high-growth Shopify brands@kevin_miguethate Google Analyticshot75/90
3clicky web analytics@clickybot traffic analyticshot74/90
4Kullar@kullarneed simple analyticshot67/90
5PostHog@posthogbot traffic analyticshot66/90
6Hiroki Tamba | Narrative & Governance@TambaClanbot traffic analyticsnear-miss57/90
7Policifyai@Policifyaineed simple analyticsnear-miss45/90
8Tomilola • Software Engineer@tomilola_nghate Google Analyticsnear-miss44/90
9Dennis Hüttner@proofwebwizardbot traffic analyticsnear-miss40/90
10SUNE 🌼@sunejuniorbot traffic analyticsnear-miss36/90
Score composition, all 10 candidates (points out of 90)
CandidatePain fit (max 35)Buying stage (max 25)Buyer (max 15)Urgency (max 5)Freshness (max 10)Not earnedTotal
Ben Otero352515011476
Kévin Miguet | CRO for high-growth Shopify brands2525150101575
clicky web analytics282515061674
Kullar3015120102367
PostHog301515062466
Hiroki Tamba | Narrative & Governance2015120103357
Policifyai1015100104545
Tomilola • Software Engineer101515044644
Dennis Hüttner200100105040
SUNE 🌼18010085436

The 5 hot leads run from 66 to 76 out of 90 — a tight band, not one runaway. Read down the bars and the pattern repeats: the dark pain-fit block carries the score, and the last axes are where everyone loses points.

Score distribution

All 10 candidates this run · scores out of 90.

5of 10 candidates ≥ 66
hot ≥ 60below
3040506070
Candidate score distribution
Score bucketCandidates
30–391
40–493
50–591
60–692
70–793

Buying stage

How ready this slate is to buy · from the scoring rubric.

Complaining about a competitor3
Problem-aware5
Not problem-aware yet2

3 of 10 are already naming a competitor’s product as the problem — the shortest distance between a post and a reply.

The 5 that stopped short

Near-misses, with the bar that fell short of 60 and every condition they were missing — not just the first one.

Hiroki Tamba | Narrative & Governance@TambaClannear-miss57/90
57 · 3 short of hot

Good fit on bot/crawler tracking and retention, but the post is about evidence preservation rather than replacing analytics, so buying intent is only moderate.

What’s missingOperator note · original run text
  • GA代替の言及がない
  • 導入・乗り換え意欲がない
Policifyai@Policifyainear-miss45/90
45 · 15 short of hot

Compliance awareness is present, but there’s no sign they’re unhappy with GA or actively comparing analytics tools.

What’s missingOperator note · original run text
  • GA4の複雑さへの不満がない
  • 代替ツールを探していない
  • 解析導入の具体課題が薄い
Tomilola • Software Engineer@tomilola_ngnear-miss44/90
44 · 16 short of hot

Good pain awareness around GA data quality, but they’re not yet looking for a replacement or showing switch urgency.

What’s missingOperator note · original run text
  • 代替ツールを探している様子がない
  • 今すぐ乗り換えたい切迫感がない
Dennis Hüttner@proofwebwizardnear-miss40/90
40 · 20 short of hot

Clear pain around bot-heavy traffic, but there’s no sign they’re evaluating a new analytics product or a privacy-first alternative yet.

What’s missingOperator note · original run text
  • GA代替の検討がない
  • プライバシー重視やCookie不要の言及がない
  • 導入したいツールの具体性がない
SUNE 🌼@sunejuniornear-miss36/90
36 · 24 short of hot

The pain is real, but the post is just an observation about bot traffic, not a search for a replacement or a compliance-driven switch.

What’s missingOperator note · original run text
  • GA4の不満がない
  • 代替ツールを探している様子がない
  • 導入の緊急性がない

2 of the 5 are missing the same thing — 代替ツールを探している様子がない. That is the condition to watch for next run, not a reason to write them off.

Also worth knowing Watch · do-not-contact

One post cleared the pain bar but is not an outreach target. Delivered as market intel.

Sunny Dodeja@sunny63203197 X · Jun 2watch70/90
70 would have cleared hot — the contact-safe check is what stops it, not the score
WHY WE FLAGGED THEM

building their own tool — a maker, not a buyer

WHAT THEY SAID

They’re openly saying they built their own tool because they hate dashboards and the GA attribution workflow is too messy. That’s a strong sign of a builder mindset, but it also means they’re creating their own solution instead of shopping for one.

A score you should not contact is still worth reading: it is the clearest description of the problem in this run, written by someone who solved it themselves.

10 candidates− 5 near-miss=5 hot, all contact-safe

Act

What the whole run was for: 5 people you can message today, each with the post that qualified them and the bar that scored them.

5ready to contact today · hot × contact-safe

How to read a score bar

Axis maxima and both thresholds come from this report’s rubric version — not from this page.

Pain fitup to 35
Buying stageup to 25
Buyerup to 15
Urgencyup to 5
Freshnessup to 10
Not earned — the points this post did not makecloses at 90

Each bar below is the whole 90-point rubric, not a percentage. The 5 axis blocks sit at their true share of 90 and the hatch closes the bar, so the segments you can see and the points that were missed always add up to 90.

Two rules cross every bar: near-miss at 35 and hot at 60. A lead is hot because its coloured blocks reach past the second rule — the category is a fact about the picture, not a separate opinion.

Pain fit 35 · Buying stage 25 · Buyer 15 · Urgency 5 · Freshness 10 · total 90

Ben Otero@benotero · X · May 26
#1 of 10HOT · CONTACT-SAFE
@benoteroon X · May 26
Google Tag Manager and GA4 is truly a hot mess. It shouldn't be this confusing to get these two things to work together.
002View original ↗
WHY WE PICKED THEM

They’re calling GA4 and Google Tag Manager a “hot mess” and saying the setup is too confusing, which is a direct opening for a simpler analytics replacement. This is the kind of frustration that often comes right before a switch.

Found by GA4 is confusing · ranked #1 of 10 candidates · 146 posts scanned

WHY THIS SCORE
76/ 90hot ≥ 60 · cleared by +16

35+25+15+0+1=76

Pain fit 35/35Buying stage 25/25Buyer 15/15Urgency 0/5Freshness 1/10Not earned 14/90

Strong pain signal about GA4 setup complexity, but there’s no urgency or explicit buying intent yet.

Open profile ↗
Kévin Miguet | CRO for high-growth Shopify brands@kevin_miguet · X · Jul 25
#2 of 10HOT · CONTACT-SAFE
@kevin_migueton X · Jul 25
btw stay away from https://t.co/2Ek1hhuBmN , they're cheap and store their data in europe but that's pretty much it. bad product, bad customer care, and even their google analytics integration is broken. Allegory of what is wrong with so many french/german tools (not customer centric, slow, inneficient...). I hate them with passion
307View original ↗
WHY WE PICKED THEM

They’re publicly saying a competitor’s Google Analytics integration is broken and that the product is bad, which shows active dissatisfaction with their current analytics stack. That makes this a timely moment to offer a cleaner, more reliable alternative.

Found by hate Google Analytics · ranked #2 of 10 candidates · 146 posts scanned

WHY THIS SCORE
75/ 90hot ≥ 60 · cleared by +15

25+25+15+0+10=75

Pain fit 25/35Buying stage 25/25Buyer 15/15Urgency 0/5Freshness 10/10Not earned 15/90

Competitor complaint is the strongest signal here, and the recent post suggests the frustration is fresh even though urgency is still low.

Open profile ↗
clicky web analytics@clicky · X · Jul 15
#3 of 10HOT · CONTACT-SAFE
@clickyon X · Jul 15
We're going to release user agent filters very soon, to block AI/bot traffic as you see fit, like you already can with countries etc. We update our global filters weekly, but it keeps getting harder to do that without too many false positives affecting other sites.
003View original ↗
WHY WE PICKED THEM

They’re actively shipping user-agent filters to block AI/bot traffic and are already maintaining global filters weekly, which shows they care about cleaning up traffic reporting now. That lines up with a need for bot/spam filtering in analytics, especially if they want less manual filter maintenance and fewer false positives.

Found by bot traffic analytics · ranked #3 of 10 candidates · 146 posts scanned

WHY THIS SCORE
74/ 90hot ≥ 60 · cleared by +14

28+25+15+0+6=74

Pain fit 28/35Buying stage 25/25Buyer 15/15Urgency 0/5Freshness 6/10Not earned 16/90

Strong pain fit and clear product work on bot filtering, but there’s no immediate deadline or buying trigger, so urgency stays low.

Open profile ↗
Kullar@kullar · X · Jul 26
#4 of 10HOT · CONTACT-SAFE
@kullaron X · Jul 26
Lesson learned today from Ads: go simple and specific in explaining the problem. I'm too deep into AI and tech to explain the product well. What I think is simple, is not simple or specific. Customers are screenshotting google analytics dashboards into chatgpt. That's where people are. That's where we need to meet them.
000View original ↗
WHY WE PICKED THEM

They’re already seeing customers screenshot Google Analytics dashboards into ChatGPT, which is a clear sign the current analytics workflow is too awkward to explain and use. That makes a simpler replacement worth reaching out about now.

Found by need simple analytics · ranked #4 of 10 candidates · 146 posts scanned

WHY THIS SCORE
67/ 90hot ≥ 60 · cleared by +7

30+15+12+0+10=67

Pain fit 30/35Buying stage 15/25Buyer 12/15Urgency 0/5Freshness 10/10Not earned 23/90

Strong pain signal around Google Analytics complexity, but there’s no explicit buying deadline, so urgency stays low.

Open profile ↗
PostHog@posthog · X · Jul 16
#5 of 10HOT · CONTACT-SAFE
@posthogon X · Jul 16
The bot detection scout watches web analytics logs for crawlers hitting our website and not being classified as bots. It found 37 self-declared crawlers slipping through, including one with 6,000+ requests per week, all showing up as regular traffic. https://t.co/3Ir1yWHhdy
105View original ↗
WHY WE PICKED THEM

They found 37 crawlers slipping through as regular traffic, including one generating 6,000+ requests per week. That’s a strong signal they care about accurate bot filtering and cleaner analytics data now.

Found by bot traffic analytics · ranked #5 of 10 candidates · 146 posts scanned

WHY THIS SCORE
66/ 90hot ≥ 60 · cleared by +6

30+15+15+0+6=66

Pain fit 30/35Buying stage 15/25Buyer 15/15Urgency 0/5Freshness 6/10Not earned 24/90

This is the strongest buying-stage signal here: they’ve identified a specific analytics problem, though they still haven’t mentioned switching tools or compliance needs.

Open profile ↗

What this run leaves you

The last chapter is the one WarmList cannot write.

3.4%market temperature · 5 hot out of 146 posts scanned

One run is a reading, not a trend. Once a second run lands, this becomes the line you watch week over week.

146 posts read, 135 discarded, 10 scored, 5 people worth your morning — all of them named a problem you already solve, and all of them cleared the contact-safe check. The next number in this story is the one you write.

End of run · Jul 27 · Fathom Analytics · scores out of 90 · hot ≥ 60

Candidate counts and scores are estimates from public posts — a guide, not a guarantee. You decide who to contact.