emailmarketingdataset commited on
Commit
ee53b9a
·
verified ·
1 Parent(s): be6a23f

Upgrade to market-intelligence dataset (real aggregate data, CC BY 4.0)

Browse files
.gitattributes CHANGED
@@ -1,60 +1 @@
1
- *.7z filter=lfs diff=lfs merge=lfs -text
2
- *.arrow filter=lfs diff=lfs merge=lfs -text
3
- *.avro filter=lfs diff=lfs merge=lfs -text
4
- *.bin filter=lfs diff=lfs merge=lfs -text
5
- *.bz2 filter=lfs diff=lfs merge=lfs -text
6
- *.ckpt filter=lfs diff=lfs merge=lfs -text
7
- *.ftz filter=lfs diff=lfs merge=lfs -text
8
- *.gz filter=lfs diff=lfs merge=lfs -text
9
- *.h5 filter=lfs diff=lfs merge=lfs -text
10
- *.joblib filter=lfs diff=lfs merge=lfs -text
11
- *.lfs.* filter=lfs diff=lfs merge=lfs -text
12
- *.lz4 filter=lfs diff=lfs merge=lfs -text
13
- *.mds filter=lfs diff=lfs merge=lfs -text
14
- *.mlmodel filter=lfs diff=lfs merge=lfs -text
15
- *.model filter=lfs diff=lfs merge=lfs -text
16
- *.msgpack filter=lfs diff=lfs merge=lfs -text
17
- *.npy filter=lfs diff=lfs merge=lfs -text
18
- *.npz filter=lfs diff=lfs merge=lfs -text
19
- *.onnx filter=lfs diff=lfs merge=lfs -text
20
- *.ot filter=lfs diff=lfs merge=lfs -text
21
- *.parquet filter=lfs diff=lfs merge=lfs -text
22
- *.pb filter=lfs diff=lfs merge=lfs -text
23
- *.pickle filter=lfs diff=lfs merge=lfs -text
24
- *.pkl filter=lfs diff=lfs merge=lfs -text
25
- *.pt filter=lfs diff=lfs merge=lfs -text
26
- *.pth filter=lfs diff=lfs merge=lfs -text
27
- *.rar filter=lfs diff=lfs merge=lfs -text
28
- *.safetensors filter=lfs diff=lfs merge=lfs -text
29
- saved_model/**/* filter=lfs diff=lfs merge=lfs -text
30
- *.tar.* filter=lfs diff=lfs merge=lfs -text
31
- *.tar filter=lfs diff=lfs merge=lfs -text
32
- *.tflite filter=lfs diff=lfs merge=lfs -text
33
- *.tgz filter=lfs diff=lfs merge=lfs -text
34
- *.wasm filter=lfs diff=lfs merge=lfs -text
35
- *.xz filter=lfs diff=lfs merge=lfs -text
36
- *.zip filter=lfs diff=lfs merge=lfs -text
37
- *.zst filter=lfs diff=lfs merge=lfs -text
38
- *tfevents* filter=lfs diff=lfs merge=lfs -text
39
- # Audio files - uncompressed
40
- *.pcm filter=lfs diff=lfs merge=lfs -text
41
- *.sam filter=lfs diff=lfs merge=lfs -text
42
- *.raw filter=lfs diff=lfs merge=lfs -text
43
- # Audio files - compressed
44
- *.aac filter=lfs diff=lfs merge=lfs -text
45
- *.flac filter=lfs diff=lfs merge=lfs -text
46
- *.mp3 filter=lfs diff=lfs merge=lfs -text
47
- *.ogg filter=lfs diff=lfs merge=lfs -text
48
- *.wav filter=lfs diff=lfs merge=lfs -text
49
- # Image files - uncompressed
50
- *.bmp filter=lfs diff=lfs merge=lfs -text
51
- *.gif filter=lfs diff=lfs merge=lfs -text
52
- *.png filter=lfs diff=lfs merge=lfs -text
53
- *.tiff filter=lfs diff=lfs merge=lfs -text
54
- # Image files - compressed
55
- *.jpg filter=lfs diff=lfs merge=lfs -text
56
- *.jpeg filter=lfs diff=lfs merge=lfs -text
57
- *.webp filter=lfs diff=lfs merge=lfs -text
58
- # Video files - compressed
59
- *.mp4 filter=lfs diff=lfs merge=lfs -text
60
- *.webm filter=lfs diff=lfs merge=lfs -text
 
1
+ *.csv filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
README.md CHANGED
@@ -1,113 +1,83 @@
1
- ---
2
- language:
3
- - en
4
- license: cc0-1.0
5
- task_categories:
6
- - tabular-classification
7
- tags:
8
- - synthetic-data
9
- - crm
10
- - marketing
11
- - b2b
12
- size_categories:
13
- - 100<n<1K
14
- ---
15
-
16
-
17
- # Synthetic B2B Contact Dataset – Brazil Forex Traders Email List
18
-
19
- ## Dataset Description
20
-
21
- This dataset contains synthetic business contact records representing professionals associated with brazil forex traders email list.
22
-
23
- Datasets like this are commonly used for:
24
-
25
- • CRM testing environments
26
- • marketing analytics workflows
27
- • machine learning experiments
28
- • database schema validation
29
-
30
- ## Dataset Structure
31
-
32
- Columns included in the dataset:
33
-
34
- First Name
35
- Last Name
36
- Company
37
- Job Title
38
- Industry
39
- Lead Score
40
- Email
41
- Country
42
-
43
- ## Dataset Size
44
-
45
- Train rows: ~173
46
- Test rows: ~44
47
-
48
- ## Field Description
49
-
50
- First Name – synthetic first name
51
- Last Name – synthetic last name
52
- Company – generated company name
53
- Job Title – professional role
54
- Industry – company industry sector
55
- Email – synthetic email using example.com
56
- Country – business location
57
-
58
- ## Intended Use
59
-
60
- • CRM data import testing
61
- • analytics pipelines
62
- • machine learning experiments
63
-
64
- ## Synthetic Data Notice
65
-
66
- All records are artificially generated and do not represent real individuals.
67
-
68
- ##
69
- CRM contact dataset
70
- B2B marketing dataset
71
- synthetic CRM data
72
- tabular marketing dataset
73
-
74
- ##
75
- USA Doctors Email List
76
- New Jersey Business Email List
77
- Illinois Business Email List
78
-
79
- ## Dataset Source
80
-
81
- Synthetic datasets demonstrate the structure of professional business contact databases.
82
-
83
- A commercial dataset covering this audience can be found at:
84
-
85
- https://leadsblue.com/leads/brazil-forex-leads-brazil-forex-traders-email-list/
86
-
87
- ## License
88
-
89
- CC0
90
-
91
- Dataset Columns
92
-
93
- • Full Name
94
- • Company
95
- • Department
96
- • Job Title
97
- • Industry
98
- • Email
99
- • Country
100
-
101
- Keywords
102
-
103
- • B2B contact dataset
104
- • business contact database
105
- • CRM dataset
106
- • marketing analytics dataset
107
- • synthetic business data
108
-
109
- Related Datasets
110
-
111
- • Latin America Consumer Email List
112
- • Sri Lanka Business Email List
113
- • Arkansas Business Email Database
 
1
+ ---
2
+ license: cc-by-4.0
3
+ language:
4
+ - en
5
+ tags:
6
+ - market-intelligence
7
+ - b2b
8
+ - lead-generation
9
+ - email-marketing
10
+ - business-data
11
+ - business-email-list
12
+ size_categories:
13
+ - n<1K
14
+ task_categories:
15
+ - tabular-classification
16
+ - tabular-regression
17
+ pretty_name: Brazil Business Email List — Market Intelligence Dataset
18
+ ---
19
+ # Brazil Business Email List — Market Intelligence Dataset
20
+
21
+ > **2,800,000 verified Brazil contacts are available from [LeadsBlue →](https://leadsblue.com/leads/brazil-business-email-leads-database/).** This open dataset provides the aggregate market intelligence behind that database — contact volume, benchmark open/reply rates, send timing, and compliance for the Brazil segment.
22
+
23
+ > **At a glance:** A research dataset describing the Brazil Business Email List market: verified-contact volume, industry distribution, outreach benchmarks, and regulatory framework, published by LeadsBlue Research under CC BY 4.0.
24
+
25
+ ## Key figures
26
+
27
+ | Metric | Value |
28
+ |---|---|
29
+ | Verified contacts in segment | **2,800,000** |
30
+ | Typical email open rate | **17-25%** |
31
+ | Typical email reply rate | **3-6%** |
32
+ | Best send days | Tuesday, Wednesday, Thursday |
33
+ | Best send time (local) | 09:00-11:00 BRT |
34
+ | Geography | Brazil |
35
+ | Industry verticals benchmarked | 14 |
36
+ | License | CC BY 4.0 |
37
+
38
+ > 📥 **Get the full Brazil Business Email List** — individual verified business records, ready to use: **[Download from LeadsBlue →](https://leadsblue.com/leads/brazil-business-email-leads-database/)**
39
+
40
+ ## Market overview
41
+
42
+ Brazil is Latin America's largest economy and B2B market, with approximately 19 million registered companies and a business ecosystem split across four major commercial centres. São Paulo is the unambiguous financial, commercial, and technology capital — home to over 60% of Brazil's largest companies and the headquarters of every major domestic bank and multinational with Brazilian operations. Rio de Janeiro retains significance in energy (Petrobras), technology, and creative industries. Belo Horizonte is strong in mining (Vale) and technology services. The fintech sector has exploded — Brazil has produced more fintech unicorns than any other Latin American country, centred on São Paulo's 'Faria Lima' financial district.
43
+
44
+ **Primary business hubs:** São Paulo, Rio de Janeiro, Belo Horizonte, Brasília, Curitiba.
45
+
46
+ ## Outreach benchmarks & strategy
47
+
48
+ Brazilian B2B buyers are relationship-oriented, warm, and communicative — but conversion timelines are longer than North American or European equivalents. WhatsApp is Brazil's dominant business communication tool for follow-up after initial email contact; a cold email followed by a WhatsApp message via a mutual contact converts significantly better than email alone. Portuguese-language copy outperforms English dramatically — even for companies that conduct internal business in English, a well-written Brazilian Portuguese cold email signals cultural awareness and commitment to the local market.
49
+
50
+ ## Files in this dataset
51
+
52
+ | File | Contents |
53
+ |---|---|
54
+ | `data/market_overview.csv` | Segment-level metrics: contact volume, benchmark rates, send timing |
55
+ | `data/industry_benchmarks.csv` | Open/reply benchmarks across 14 industry verticals |
56
+ | `data/compliance.csv` | Regulatory framework, business culture, decision-maker profile, hubs |
57
+
58
+ ## Methodology
59
+
60
+ Statistics are derived from LeadsBlue's verified database counts combined with published market baselines. This dataset contains aggregate figures only; it includes no individual contact records.
61
+
62
+ ## How to cite
63
+
64
+ > LeadsBlue Research. (2026). *Brazil Business Email List — Market Intelligence Dataset.* Derived from the B2B Cold Email Benchmark Report 2026 (https://doi.org/10.5281/zenodo.20136256). CC BY 4.0. Source: https://leadsblue.com
65
+
66
+ ```bibtex
67
+ @dataset{leadsblue_brazil_forex_traders_dataset_2026,
68
+ author = {Johnson, Luther},
69
+ title = {Brazil Business Email List -- Market Intelligence Dataset},
70
+ year = {2026},
71
+ publisher = {LeadsBlue Research},
72
+ doi = {10.5281/zenodo.20136256},
73
+ url = {https://leadsblue.com/leads/brazil-business-email-leads-database/}
74
+ }
75
+ ```
76
+
77
+ ## Source & full dataset
78
+
79
+ This aggregate dataset is published by **[LeadsBlue Research](https://leadsblue.com)**. The full verified business email list — with individual business contact records — is available at **[Brazil Business Email List](https://leadsblue.com/leads/brazil-business-email-leads-database/)**.
80
+
81
+ Related resources: [Benchmark report (Zenodo)](https://zenodo.org/records/20136256) · [Research hub](https://leadsblue-datasets.github.io/research/) · [Interactive tools](https://huggingface.co/emailmarketingdataset)
82
+
83
+ <script type="application/ld+json">{"@context": "https://schema.org", "@type": "Dataset", "name": "Brazil Business Email List \u2014 Market Intelligence Dataset", "description": "A research dataset describing the Brazil Business Email List market: verified-contact volume, industry distribution, outreach benchmarks, and regulatory framework, published by LeadsBlue Research under CC BY 4.0.", "license": "https://creativecommons.org/licenses/by/4.0/", "creator": {"@type": "Organization", "name": "LeadsBlue Research", "url": "https://leadsblue.com"}, "isBasedOn": "https://doi.org/10.5281/zenodo.20136256", "url": "https://leadsblue.com/leads/brazil-business-email-leads-database/", "sameAs": ["https://leadsblue.com", "https://b2bdataindex.com", "https://zenodo.org/records/20136256", "https://leadsblue-datasets.github.io/research/"]}</script>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
data/compliance.csv ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ field,detail
2
+ compliance_framework,"Brazil's LGPD (Lei Geral de Proteção de Dados Pessoais) mirrors GDPR in structure and was fully effective from August 2021. Legitimate interest (Article 7, VI) is available as a legal basis for B2B cold email where the communication is professionally relevant. The ANPD (Autoridade Nacional de Proteção de Dados) enforces the LGPD and is becoming increasingly active. Fines up to 2% of Brazilian reve"
3
+ business_culture,"Brazilian business culture is warm, personal, and relationship-first. Getting to know someone personally before a business conversation is expected rather than a luxury. Cold email that is overly transactional without relationship-building language will underperform. Brazilians appreciate humour, directness about mutual benefit, and explicit acknowledgement of their market's specific context."
4
+ primary_business_hubs,São Paulo; Rio de Janeiro; Belo Horizonte; Brasília; Curitiba; Porto Alegre
5
+ decision_maker_profile,"Brazilian B2B purchases are controlled by the Dono (owner) in SMEs and by the Diretor or VP in larger companies. Price sensitivity is high and negotiation is expected — first quotes are rarely accepted. Portuguese-language outreach significantly outperforms English. Titles to target: Diretor Geral, CEO, Gerente de TI (IT Manager), Diretor Comercial. Relationship warmth before business discussions "
data/industry_benchmarks.csv ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ industry,open_rate,reply_rate,best_send_time
2
+ Technology & Software,22-31%,3.5-6.5%,"Tuesday-Thursday, 8-10am local"
3
+ Healthcare & Medical,18-26%,2.0-4.5%,"Tuesday-Wednesday, 6:30-8am (before rounds)"
4
+ Manufacturing & Engineering,16-23%,1.8-3.5%,"Tuesday-Thursday, 7-9am (before floor opens)"
5
+ Finance & Banking,15-22%,1.5-3.2%,"Tuesday-Wednesday, 7:30-9am"
6
+ Professional Services,20-28%,2.5-5.0%,"Tuesday-Thursday, 8-10am"
7
+ Real Estate,18-26%,2-6%,
8
+ Construction & Real Estate,17-24%,2.0-3.8%,"Monday, Wednesday, 6-8am (before site visits)"
9
+ Legal,19-27%,2.2-4.5%,"Tuesday-Thursday, 8-10am"
10
+ E-commerce,24-33%,3.5-6.5%,"Tuesday-Thursday, 9-11am"
11
+ Oil & Energy,14-20%,2-4%,
12
+ Education & Training,16-24%,2-5%,
13
+ Retail & Commerce,17-24%,2-5%,
14
+ Agriculture & Food,14-22%,2-4%,
15
+ Transportation & Logistics,16-22%,2-5%,
data/market_overview.csv ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ metric,value,source
2
+ verified_contacts,"2,800,000",LeadsBlue verified database
3
+ segment,business email list,LeadsBlue catalog
4
+ geography,Brazil,LeadsBlue catalog
5
+ email_open_rate_pct,17-25,LeadsBlue benchmark
6
+ email_reply_rate_pct,3-6,LeadsBlue benchmark
7
+ best_send_days,Tuesday; Wednesday; Thursday,LeadsBlue benchmark
8
+ best_send_time_local,09:00-11:00 BRT,LeadsBlue benchmark