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One Million Passive Income Opportunities Dataset

A source-backed one-million-row dataset for comparing passive-income and semi-passive online opportunity variants across digital products, marketplace categories, creator monetization paths, and productized automation workflows.

Each row represents a specific opportunity variant built from public marketplace listings, public marketplace taxonomies, public workflow template pages, or official platform monetization documentation. The dataset is designed for research, comparison, dashboard building, content planning, and opportunity screening. It does not guarantee income, profitability, traffic, sales, or business success.

This published run includes 1,000,000 rows. The one-million-row output is created by deterministic expansion of public, source-backed seed opportunities into monetization, packaging, audience, and positioning variants.


Dataset Preview

opportunity_id opportunity_title opportunity_category opportunity_subcategory monetization_model target_audience buyer_problem example_offer platform_or_channel source_url source_name source_type startup_cost_bucket skill_level_bucket time_to_launch_bucket time_to_revenue_bucket upfront_work_intensity_score maintenance_intensity_score automation_potential_score passive_potential_score competition_intensity_score platform_dependency_score scalability_score fulfillment_complexity_score content_dependency_score paid_adjacency_signal search_demand_signal risk_notes source_confidence_score collection_date
gumroad-gumroad-2696c5dadd139ebd-bundle-asset-bundle-beg-ever AI MASTERCLASS | bundle sales | asset bundle | beginner buyers | evergreen angle AI resources Prompt packs and AI workflow assets | asset bundle | evergreen angle Bundle sales beginner buyers researching ai users, marketers, and operators Beginner buyers want a source-backed way to solve operators want reusable prompt systems that reduce... [46 more chars] Asset bundle for AI MASTERCLASS sold as a bundle sales Gumroad https://vincentschwenk.gumroad.com/l/ai_for_artists?layout=discover&recommended_by=search | https:/... [21 more chars] Gumroad Discover | Gumroad Discover Public digital product marketplace listing | Public digital product marketplace search Medium Medium Medium Short 48 22 88 90 85 88 88 10 40 True medium Research only. Public source grounding exists, but platform rules, execution quality, and competitio... [52 more chars] 88 2026-06-05 00:00:00+00:00
automation-zapier-348ee2a2418b2217-template-library-agents-agency-one-time Auto-post Fathom team meeting notes to Slack | template library sale | agent library | agencies ... [16 more chars] Automation workflows General no-code workflows | agent library | one-time scope Workflow template pack agencies researching small businesses, consultants, and no-code builders Agencies want a source-backed way to solve buyers want a repeatable way to auto-post fathom team mee... [40 more chars] Agent library for Auto-post Fathom team meeting notes to Slack sold as a template library sale Zapier https://zapier.com/templates/details/team-meeting-notes-automation-fathom-ai-slack | https://zapier... [14 more chars] Zapier Templates | Zapier Templates Public automation template library listing | Public automation template directory Medium Medium Medium Medium 52 32 94 62 56 86 88 42 20 True high Research only. Public source grounding exists, but platform rules, execution quality, and competitio... [61 more chars] 82 2026-06-05 00:00:00+00:00
gumroad-gumroad-ff97a34582044fc9-bundle-asset-bundle-beg-ever Adjustable Mannequin v1.3 - Blender 4.3+ | bundle sales | asset bundle | beginner buyers | everg... [10 more chars] Creative assets 3D assets and design files | asset bundle | evergreen angle Bundle sales beginner buyers researching 3d artists, game developers, and creative-tool buyers Beginner buyers want a source-backed way to solve creators want ready-made production assets that sh... [43 more chars] Asset bundle for Adjustable Mannequin v1.3 - Blender 4.3+ sold as a bundle sales Gumroad https://vertexarcade.gumroad.com/l/adjustable-mannequin?layout=discover&recommended_by=search | htt... [25 more chars] Gumroad Discover | Gumroad Discover Public digital product marketplace listing | Public digital product marketplace search Medium Medium Medium Short 48 22 88 90 95 88 88 10 40 True medium Research only. Public source grounding exists, but platform rules, execution quality, and competitio... [52 more chars] 88 2026-06-05 00:00:00+00:00
creator-youtube-0101e9118b67a234-owned-shopping-companion-beg-evergreen 3D assets and Blender resources | owned-product shopping path | downloadable companion | beginner... [37 more chars] Creator monetization 3D assets and Blender resources | downloadable companion | evergreen backlog cadence YouTube Shopping for owned products beginner viewers researching 3d artists, game developers, and creative-tool buyers Beginner viewers want a source-backed way to solve creators want ready-made assets that speed up ren... [57 more chars] Downloadable companion for 3D assets and Blender resources sold as a owned-product shopping path YouTube https://support.google.com/youtube/answer/12257682 | https://gumroad.com/discover?query=3d+model |... [48 more chars] YouTube Help | Gumroad Discover | YouTube Help Official monetization documentation plus public digital product marketplace search | Official monet... [21 more chars] Medium Medium Medium Medium 66 60 58 62 78 90 88 34 94 True high Research only. Public source grounding exists, but platform rules, execution quality, and competitio... [67 more chars] 72 2026-06-05 00:00:00+00:00
gumroad-gumroad-827d30d2e820fa71-bundle-asset-bundle-beg-ever Architecture Presentation Board Template (A0-A3) #1 | bundle sales | asset bundle | beginner buye... [21 more chars] Digital products Templates and planning systems | asset bundle | evergreen angle Bundle sales beginner buyers researching digital-product buyers looking for time-saving or skill-specific reso... Beginner buyers want a source-backed way to solve buyers want a polished digital asset or shortcut t... [46 more chars] Asset bundle for Architecture Presentation Board Template (A0-A3) #1 sold as a bundle sales Gumroad https://creativearchitect.gumroad.com/l/CanvatemplateA1?layout=discover&recommended_by=search | htt... [25 more chars] Gumroad Discover | Gumroad Discover Public digital product marketplace listing | Public digital product marketplace search Medium Medium Medium Short 48 22 88 90 92 88 88 10 40 True medium Research only. Public source grounding exists, but platform rules, execution quality, and competitio... [52 more chars] 88 2026-06-05 00:00:00+00:00

Access Requirements (Paid Dataset)

This dataset is behind manual gated access.

To obtain access:

  1. Purchase the dataset here:
    https://thearticulated.gumroad.com/l/one-million-passive-income-opportunities

  2. Provide your Hugging Face username at checkout.

  3. Return to this Hugging Face page and click:
    "Request Access"

  4. Your access will be approved within 1-12 hours.

Once approved, you can use the Python snippet at the bottom of this README to load the dataset.


Dataset Structure

Total rows: 1,000,000

Total columns: 30

Splits

  • data: 1,000,000 rows

Data Files

  • data: data/data.parquet

Data Dictionary

The table below describes the columns included in this dataset.

column pandas_dtype dataset_type description
opportunity_id object string Text column. Stable unique identifier for the opportunity row.
opportunity_title object string Text column. Customer-readable title describing the specific passive-income or semi-passive opportunity variant.
opportunity_category object string Text column. Top-level opportunity grouping such as digital products, education resources, creator monetization, or automation workflows.
opportunity_subcategory object string Text column. More specific opportunity niche or taxonomy path used to segment rows inside the broader category.
monetization_model object string Text column. Primary revenue model for the row, such as digital product sales, memberships, course sales, template packs, or productized automation.
target_audience object string Text column. Best-effort description of the likely paying customer or operator segment for the opportunity.
buyer_problem object long text Free-text column containing longer text values. Problem or workflow pain point that the opportunity appears to solve for the customer.
example_offer object string Text column. Example product, content angle, workflow offer, or package that illustrates the opportunity.
platform_or_channel object string Text column. Primary platform or channel attached to the opportunity, such as Gumroad, Teachers Pay Teachers, Zapier, or YouTube.
source_url object long text Free-text column containing longer text values. Public source URL or pipe-delimited source URLs that grounded the row.
source_name object string Text column. Public source name or pipe-delimited source names used for the row.
source_type object string Text column. Description of the public source type, such as marketplace listing, marketplace taxonomy, workflow template library, or official monetization documentation.
startup_cost_bucket object string Text column. Bucketed estimate of the upfront cash cost required to start the opportunity.
skill_level_bucket object string Text column. Bucketed estimate of the skill depth needed to launch the opportunity responsibly.
time_to_launch_bucket object string Text column. Bucketed estimate of how long it may take to produce a launchable first version.
time_to_revenue_bucket object string Text column. Bucketed estimate of how long it may take before the opportunity can plausibly generate revenue.
upfront_work_intensity_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how much front-loaded work the opportunity usually requires.
maintenance_intensity_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating ongoing upkeep after launch.
automation_potential_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how much of the workflow can be templatized, systemized, or automated.
passive_potential_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how passive the opportunity can become after initial setup.
competition_intensity_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how crowded the opportunity appears based on public source signals and marketplace density.
platform_dependency_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how dependent the opportunity is on one main platform's rules or discovery systems.
scalability_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how well the opportunity can scale without matching labor growth one-for-one.
fulfillment_complexity_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how hard delivery, onboarding, support, or updates may be.
content_dependency_score int64 integer Whole-number numeric column. Directional score from 0 to 100 estimating how much continued content production is required.
paid_adjacency_signal bool boolean True/false column. Boolean signal that public sources already show buyers spending money, subscriptions, or software budget in the same opportunity lane.
search_demand_signal object string Text column. Directional text label summarizing visible public demand clues, marketplace density, or monetization-surface evidence.
risk_notes object long text Free-text column containing longer text values. Research-only notes about platform risk, saturation, compliance limits, or other caveats. This is not financial advice.
source_confidence_score int64 integer Whole-number numeric column. Directional confidence score from 0 to 100 based on the specificity and completeness of the public source evidence.
collection_date datetime64[us, UTC] datetime Date or timestamp column. UTC collection date for the row.

Intended Use

This dataset is intended for research, experimentation, analysis, and model prototyping.

Loading the Dataset


import os
from datasets import load_dataset

HUGGINGFACE_API_KEY_KARMANE = os.environ.get("HUGGINGFACE_API_KEY_KARMANE")

dataset = load_dataset(
    "Karmane/one-million-passive-income-opportunities",
    token=HUGGINGFACE_API_KEY_KARMANE,
)

print(dataset)
print(dataset[list(dataset.keys())[0]][0])

# getting the DataFrame itself
# df = dataset[list(dataset.keys())[0]].to_pandas()

Karmane. (2025). One Million Passive Income Opportunities Dataset. Hugging Face. https://huggingface.co/datasets/Karmane/one-million-passive-income-opportunities

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