GetESP는 수신자의 이메일 서비스 제공업체(ESP)를 식별하여 이메일 전달률을 향상시키는 무료 도구입니다. 이메일 목록을 업로드하여 Gmail, Outlook과 같은 ESP별로 연락처를 분석하고 분류하세요. 이 'ESP 매칭' 전략은 이메일이 받은 편지함에 도달하고 스팸 필터를 우회하며 열람률을 높이는 데 도움이 됩니다. 또한 고급 스팸 방지 도구를 탐지하여 더 효과적인 캠페인 계획을 가능하게 합니다.
Warmy는 발신자 평판을 개선하고, 스팸 필터를 피하며, 이메일 열람률 및 클릭률을 높이기 위해 설계된 AI 기반 이메일 웜업 및 전달률 플랫폼입니다. 아웃리치 캠페인을 위한 도메인 및 IP 준비 과정을 자동화하여 Gmail, Outlook, Yahoo와 같은 주요 제공업체의 기본 받은 편지함에 메시지가 안정적으로 도달하도록 보장합니다.
제품 개요
GetESP 제품 개요
GetESP는 수신자의 이메일 서비스 제공업체(ESP)를 식별하여 이메일 전달률을 향상시키는 무료 도구입니다. 이메일 목록을 업로드하여 Gmail, Outlook과 같은 ESP별로 연락처를 분석하고 분류하세요. 이 'ESP 매칭' 전략은 이메일이 받은 편지함에 도달하고 스팸 필터를 우회하며 열람률을 높이는 데 도움이 됩니다. 또한 고급 스팸 방지 도구를 탐지하여 더 효과적인 캠페인 계획을 가능하게 합니다.
Warmy 제품 개요
Warmy는 발신자 평판을 개선하고, 스팸 필터를 피하며, 이메일 열람률 및 클릭률을 높이기 위해 설계된 AI 기반 이메일 웜업 및 전달률 플랫폼입니다. 아웃리치 캠페인을 위한 도메인 및 IP 준비 과정을 자동화하여 Gmail, Outlook, Yahoo와 같은 주요 제공업체의 기본 받은 편지함에 메시지가 안정적으로 도달하도록 보장합니다.
Detailed feature comparison
GetESP vs Warmy monthly traffic
Compare GetESP and Warmy by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the GetESP vs Warmy monthly traffic comparison, GetESP currently shows 3.5K visits and Warmy shows 181.2K; Warmy has about 51.8 times the visible traffic of GetESP, an absolute difference of about 177.7K visits. This reflects visible reach, not feature quality or paid users.
Only Warmy has complete third-party traffic details; GetESP uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
GetESP monthly traffic:
Latest traffic
Warmy monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 152.9K 월 방문
- 2026/1: 208.9K 월 방문
- 2026/2: 190.8K 월 방문
- 2026/3: 243.9K 월 방문
- 2026/4: 198.8K 월 방문
- 2026/5: 181.2K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 35.94% | 65.1K |
| 🇳🇬Nigeria | 22.78% | 41.3K |
| 🇬🇪Georgia | 17.11% | 31K |
| 🇮🇳India | 14.98% | 27.1K |
| 🇬🇧United Kingdom | 9.19% | 16.7K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 79.86% | 144.7K |
| 리퍼럴 | 15.55% | 28.2K |
| 이메일 | 4.59% | 8.3K |
검색 키워드
Usage comparison
Compare the core capabilities of GetESP and Warmy
GetESP Core features
Warmy Core features
Use cases
GetESP Use cases
Warmy Use cases
GetESP vs Warmy:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth GetESP vs Warmy comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. GetESP is primarily listed under “이메일 마케팅”, while Warmy is primarily listed under “이메일 마케팅”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Pricing (GetESP: Free; Warmy: Freemium); Monthly visits (GetESP: 3.5K; Warmy: 181.2K); Favorites (GetESP: 112; Warmy: 131); Website (GetESP: getesp.io; Warmy: www.warmy.io); Added (GetESP: 2025-08-13; Warmy: 2025-08-07). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the GetESP vs Warmy monthly traffic comparison, GetESP currently shows 3.5K visits and Warmy shows 181.2K; Warmy has about 51.8 times the visible traffic of GetESP, an absolute difference of about 177.7K visits. This reflects visible reach, not feature quality or paid users.
Only Warmy has complete third-party traffic details; GetESP uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Product positioning, use cases, and roles
GetESP and Warmy currently overlap in shared categories: 이메일 마케팅 및 리드 생성; shared tags: 콜드 이메일, 이메일 전달률, 이메일 마케팅 및 리드 생성. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
GetESP's unique categories/tags are 데이터 분석, 이메일 인증, ESP 검사기, 수신함 배치, 영업 아웃리치 및 스팸 필터; Warmy's are 자동화, AI, 이메일 웜업, 영업 자동화, 발신자 평판 및 스팸 검사기. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
GetESP has no verified rating, 0 comments, 112 favorites, and 116 likes;Warmy has no verified rating, 0 comments, 131 favorites, and 126 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate GetESP first
Put GetESP on the priority trial list when the task aligns with “이메일 마케팅” and especially 데이터 분석, 이메일 인증, ESP 검사기, 수신함 배치, 영업 아웃리치 및 스팸 필터. This follows recorded positioning and does not imply unlisted capabilities are absent.
GetESP also currently records: pricing is free, product type is website, 3.5K on-site monthly views, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Warmy first
Put Warmy on the priority trial list when the task aligns with “이메일 마케팅” and especially 자동화, AI, 이메일 웜업, 영업 자동화, 발신자 평판 및 스팸 검사기. This follows recorded positioning and does not imply unlisted capabilities are absent.
Warmy also currently records: pricing is freemium, product type is website, 181.2K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in GetESP and Warmy, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




