datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
marketing_social_media
Marketing Campaigns Dataset
This repository contains a dataset specifically designed for generating marketing content. The dataset includes various features that are crucial for crafting effective marketing strategies, such as industry, channel, objective, and more. This dataset is ideal for use in machine learning models, AI-powered marketing tools, and data-driven marketing analyses.
Dataset Overview
The dataset consists of multiple entries, each representing a specific… See the full description on the dataset page: https://huggingface.co/datasets/RafaM97/marketing_social_media.alinaboulsi_digital-marketing-performance-dataset
Digital Marketing Performance Dataset
A Synthetic, Benchmark-Based Dataset for Multi-Platform Marketing Analytics & BI
Dataset Info
Source: Kaggle
Original Size: 1.83 MB
Kaggle Downloads: 145
Files: 3
Files
README_DATASET.md
data_dictionary.csv
digital_marketing_dataset_30k.csv
Mirrored from Kaggle
marketingVoicemarketing-instruct-13k
Dataset Card for marketing-instruct-13k
Dataset Details
Dataset Description
A curated instruction-tuning dataset of ~13,000 marketing copywriting
examples across five task types, built for the AutoScientist Challenge
2026 (Marketing category). This is the largest dataset in the
Marketing-Mixtral/Llama series, used to fine-tune
Marketing-Llama-3.3-70B
(88% win rate against base Llama-3.3-70B-Instruct).
It extends marketing-instruct-8k
with an… See the full description on the dataset page: https://huggingface.co/datasets/suehuynh/marketing-instruct-13k.Marketing-Emails
Marketing Emails
A curated corpus of synthetically generated yet realistic marketing email messages designed to support research in Domain Adaptation, Natural Language Processing (NLP), Data Science, Machine Learning, and Communication research.
The dataset is appropriate for a wide spectrum of training paradigms—including pre-training, fine-tuning, and domain adaptation—as well as for rigorous evaluation of models targeting domain-specific language understanding and generation… See the full description on the dataset page: https://huggingface.co/datasets/marketeam/Marketing-Emails.open-email-marketing-dataset
Open Email Marketing Dataset
This repository contains the Open Email Marketing Dataset, a collection of 1,000 question-and-answer pairs in JSONL format. This dataset is created and maintained by LeadsBlue.com to provide a high-quality, public resource for developers, researchers, and marketers. It is specifically designed for tasks such as fine-tuning Large Language Models (LLMs), building advanced Q&A engines, developing cold email tools, and enhancing SEO systems.… See the full description on the dataset page: https://huggingface.co/datasets/emailmarketingdataset/open-email-marketing-dataset.brandvoice-marketing-briefs
BrandVoice Marketing Briefs
Generic AI writes like a robot. This trains it to write like a brand.
The loop is closed. The LoRA adapter
trained on this data scored +24.3% copy quality (7.0 to 8.7) with a 56% win rate against its
base, on Adaption's held-out judge. Dataset, weights, evaluation, and reproduction are all public.
A corpus of real marketing copy. 6,339 lines scraped from the live pages of 83 brands (the actual
Stripe, Liquid Death, Ramp, Duolingo copy)… See the full description on the dataset page: https://huggingface.co/datasets/manifesta/brandvoice-marketing-briefs.social-instagram-marketing
Social — Instagram Marketing Multimodal Dataset
A synthetic, multimodal dataset for Social, an AI Instagram-marketing agent. Every row is a single Instagram post idea that pairs a marketing caption with a matching AI-generated image, conditioned on a business brief and brand preferences.
Agent pattern: owner brief + brand preferences → 3 similar successful posts (retrieval / recommendation) + 1 freshly generated post (caption + image).
Rows (total)
1,447… See the full description on the dataset page: https://huggingface.co/datasets/avihayamor/social-instagram-marketing.cps-marketing-mediatask720_mmmlu_answer_generation_marketing
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task720_mmmlu_answer_generation_marketing
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task720_mmmlu_answer_generation_marketing.bank-marketing-additional
Dataset Card for Bank Marketing (additional)
This dataset is a precise version of UCI Bank Marketing
We first created the default bank marketing dataset, as seen here. Then we further run the following Python script to create this additional portion.
# Define feature types
continuous_columns = ["age", "duration", "campaign", "pdays", "previous",
"emp.var.rate", "cons.price.idx", "cons.conf.idx",
"euribor3m", "nr.employed"]… See the full description on the dataset page: https://huggingface.co/datasets/cestwc/bank-marketing-additional.Data-Analytics-Digital-Marketing-Project-Management-QA_DBmarketing_user_prompts_unfilteredbank-marketing
Dataset Card for Bank Marketing
This dataset is a precise version of Bank Marketing.
To download the original csv from UCI
wget https://archive.ics.uci.edu/static/public/222/bank+marketing.zip
find . -name "*.zip" -exec sh -c 'unzip -d "${1%.*}" "$1" && rm "$1"' _ {} \;
find . -name "*.zip" -exec sh -c 'unzip -d "${1%.*}" "$1" && rm "$1"' _ {} \;
We used the following python script to create this Hugging Face dataset
import pandas as pd
df_bank =… See the full description on the dataset page: https://huggingface.co/datasets/cestwc/bank-marketing.sgym-marketing-dataset
SkillGym Marketing Training Dataset
Training data, evaluation tasks, and benchmark results for fine-tuning small language models on marketing tasks. Contains 99 SFT examples, 67 DPO preference pairs, 80 evaluation tasks, and benchmark scores across 13 marketing skill domains.
Dataset Description
This dataset packages all artifacts from the SkillGym project: compiling public agent skills into training data for small language models. We benchmarked 13 marketing… See the full description on the dataset page: https://huggingface.co/datasets/4MLabs/sgym-marketing-dataset.tanpo-marketing-sft
Tanpo Marketing SFT (10k)
Audit note: This preferred publish file has a high rate (~63%) of assistant 'Situation read' / identity-framing turns by design for the specialist persona. Schema, parse rate, empty-assistant, and duplicate checks are clean.
Ownership
Owner: DarkNinja Solutions
Creator: d4rkninja
Community: DarkLab
Domain
Marketing and go-to-market: ads, hooks, email/SMS, landing pages, offers, positioning, ICP, funnels, pricing, brand… See the full description on the dataset page: https://huggingface.co/datasets/d4rkninja/tanpo-marketing-sft.Marketing-Budget-and-Actual-Sales-Dataset
Dataset Card for tweet_eval
Dataset Summary
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
Supported Tasks and Leaderboards
text_classification: The dataset can be… See the full description on the dataset page: https://huggingface.co/datasets/dianalogan/Marketing-Budget-and-Actual-Sales-Dataset.marketing_exam1bank-marketing-propensity
Introduction
This project explores several classification techniques as applied to a bank's marketing campaign data. The classification goal is to predict whether the client will subscribe a term deposit (variable y).
Source: https://archive.ics.uci.edu/ml/datasets/bank+marketing
It's recommended that the viewer read the Jupyter Notebook in NBViewer: https://nbviewer.jupyter.org/github/sgus1318/marketing_propensity/blob/master/Bank_DirectMarketing_Propensity.ipynb… See the full description on the dataset page: https://huggingface.co/datasets/kokul/bank-marketing-propensity.marketing-benchmark-of-more-than-10-ai-models
Marketing Benchmark of 10+ AI Models
A 5,000-question benchmark for evaluating LLMs across six dimensions of modern
marketing — Meta Ads, Google Ads, SEO & Organic, Email & Lifecycle, Critical
Thinking, and Action-Based scenarios — graded through 10 distinct marketer personas.
Every question is independently authored by the AdsGPT Marketing Bench team.
Knowledge MCQs are hand-authored against 2026 platform documentation; open-ended
and action-based scenarios are built from… See the full description on the dataset page: https://huggingface.co/datasets/adsgpt/marketing-benchmark-of-more-than-10-ai-models.marketing-briefs
Brief 003 · Marketing brief review
Review the generated marketing requests and record approval directly in the dataset. This batch contains 339 briefs. All products, offers, and supporting claims are fictional.
Start reviewing
Open the brief viewer and editor →
Click a row to inspect the brief. Start with user_text, the request a user would send to the model.
Compare it with the structured brief: deliverable, product_description, offer, audience_description… See the full description on the dataset page: https://huggingface.co/datasets/zeton-labs/marketing-briefs.autotree_automl_bank-marketing_gosdt_l512_d3
Dataset Card for "autotree_automl_bank-marketing_gosdt_l512_d3"
More Information needed
Performance-Marketing-Data
Performance Marketing Expert Dataset
Dataset Description
This dataset contains comprehensive performance marketing knowledge and logical reasoning patterns for Meta (Facebook/Instagram), Google Ads, and TikTok advertising platforms. It's designed for fine-tuning language models to understand brand verticals, performance marketing strategies, and develop reasoning capacity for creating winning ad campaigns.
Dataset Structure
Each example follows an… See the full description on the dataset page: https://huggingface.co/datasets/Sri-Vigneshwar-DJ/Performance-Marketing-Data.marketing_campaign_datamarketing_emailsmarketing_campaignhadrianstone-marketing-research-23-laws
The 23 Laws of Marketing - Research Papers by Hadrian Stone
Overview
This dataset contains short research papers and notes expanding on The 23 Laws of Marketing: Master Them or Die. It uses The Machiavellian Marketing Framework™ (MMF), a marketing philosophy created and coined by Hadrian Stone. It explores attention economics, persuasion, consumer behavior, and Machiavellian approach to modern marketing.
Contents Include:
Paper-01-23laws.pdf - flagship paper introducing… See the full description on the dataset page: https://huggingface.co/datasets/HadrianStone/hadrianstone-marketing-research-23-laws.digital_marketing_campaignmarketing-instruct-4k
Dataset Card for marketing-instruct-4k
Dataset Details
Dataset Description
A curated instruction-tuning dataset of ~4,300 marketing copywriting
examples across five task types, built for the AutoScientist Challenge
2026 (Marketing category). Used to fine-tune Marketing-Mixtral-8x7B.
Key finding: this carefully curated dataset at its natural size
outperformed a 12,000-row version expanded via automated augmentation
(80% vs 58% win rate against the… See the full description on the dataset page: https://huggingface.co/datasets/suehuynh/marketing-instruct-4k.MarketingStructuralPrompts
README.md
Enhancing Large Language Model Performance in Digital Marketing Strategies with a Specialized Prompt Dataset
Creator: Muratcan Koylan
About the Dataset
This dataset, comprising 4,643 specialized prompts across various categories of digital marketing, aims to enhance the performance of Large Language Models (LLMs) like GPT-3 in generating accurate, relevant, and industry-specific marketing strategies.
30 Paid Search Prompts
15 ROAS Prompts… See the full description on the dataset page: https://huggingface.co/datasets/MuratcanKoylan/MarketingStructuralPrompts.