Product¶
The product is the software platform in the making. A web application that mine and aggregate relevant data to make them more efficient in achieving their goals.
History¶
The seeding idea was to mine and curate employment opportunities to offer a distilled set of roles the user’s profile match best.
Early market research showed it would be a hard to sell, even for free solution. User retention would be very low turning promotion efforts into a never ending sink hole.
Plus, job seekers have one primary worry, money. But plenty of time. As said, the offering is a hard sell: Improving efficiency for people who need money is looking for the hardest road to make this project financially viable.
Talent acquisition?¶
Related would be to rather focus recruiters. That’s a good audience. They lack time, execute repetitive tasks and would value better efficiency.
The idea didn’t feel exciting. How can we build a great product without a thrill?
Marketers¶
It then appeared obvious that the marketing field is where all the action takes place. Clay.com, Zoominfo, Hubspot, and a gazillion other marketing efficiency tools have flourished and are doing a killkng.
Looked very closely at Clay as they stand as an innovative service. They promise data enrichment and discovery.
Going broad¶
The core technology necessary to make any of this work, regardless of the persona, can in fact be quite abstract. If we make it so.
Since we are set to be a software organisation, why not build software that solves abstract problems in the software domain of data mining, data exploration, synthetization: data enrichment.
Then map it to multiple sort of needs.
Data Enrichment¶
Definition
Data enrichment is the process of enhancing raw data by adding context, information, and insights to make it more useful and valuable. This involves integrating additional data from various external or internal sources to improve the depth, accuracy, and utility of the original dataset.
key components
Data Collection
The process of data already available to the user and exploration then mining of data available elsewhere.
Internal Sources: Collecting data from within the organization dataset, such as customer records, transaction histories
These could be CRM systems, or simply CSV or even raw text dumps.
External Sources: Gathering data from third-party providers, public databases, social media, etc.
Typically web scraping, but also simply feeding from sources intended for such consumption.
Data Integration
We could go both ways, but to avoid mine fields we will simply take data in.
Merging Data: Combining data from different sources to create a comprehensive dataset.
Data Matching: Identifying and linking related data points across different datasets, often using unique identifiers.
Data Cleansing
Who likes a mess.
Removing Duplicates: Identifying and eliminating duplicate entries to ensure data accuracy.
Correcting Errors: Fixing inaccuracies, such as misspellings or incorrect values, to improve data quality.
Data Transformation
Who doesn’t like comsistency
Standardization: Converting data into a consistent format or structure to facilitate easy analysis.
Normalization: Adjusting data values to a common scale, making it easier to compare and analyze.
Imagine a rich data set in german, shared with the english speaking team. Sure they can auto translate pages and pages via a free translator, but really, would they?
Data Augmentation
Last but not the least, the crown of enrichment.
Adding and relating Contextual Information: Enhancing data with additional details, such as demographic information, geographic data, and behavioral insights.
Expand the search: If the user knows of a company, what about showing some of the people who work there, financials, trending news, their customer sentiment.
Metrics: Deriving new insights
etc
So now we can explore the typical use case this tech could serve.
Use cases¶
Some segregated use cases suitable for data enrichment.
There are commonalities across the segregation, so it is followed by the set of entities to process. Along with data points to gather for each of them.
It turns out, most would serve a wide range of persona’s needs.
not only that, one that all personas would likely also be interested in: work opportunities.
It goes full circle. Improving professionals’ efficiencies first, and maybe offer them a digest of what could be their next role.
Job Seekers:
Is after job opportunities, curated matching roles, insights into companies and pay.
Identify job opportunities tailored to their skills and interests.
Improve CVs and cover letters using via suggestions.
Access curated open roles in specific locations.
Gather information about companies, including work culture, benefits, feedback, horror stories. Layoffs. And other key points.
Datasources:
linkedIn
glassdoor
indeed
Sales and Marketers:
Marketers are close to or are sales people, on the look out for business opportunities, insights into customers and competitors, market trends.
Identify new leads and potential clients and likely key decision makers
Gather detailed information about companies, including key personnel and revenue.
Track market trends and competitor activities.
Enrich CRM data with up-to-date information.
Track industry news and events to identify sales opportunities.
Segment leads for personalized outreach.
Segment audiences based on enriched data for targeted campaigns.
Enrich existing customer base with expanded profiles to construct campaigns or just understanding individuals and groups better.
datasources
linkedin
yellow pages
yelp
industry reports and publications
Researchers:
A researcher is an academic, independent , or company personel doing research.
Find relevant grants and funding opportunities.
Stay updated on current research trends and emerging topics.
Access and summarize research papers and publications.
Network with other researchers and institutions.
build lost of similar profiles with their blog, published papers etc
datasources
Academic databases (Google Scholar, PubMed)
Grant databases (Grants.gov, NIH RePORTER)
Research journals (Arxiv, pubMed, nih.gov)
linkedin
Recruiters:
I don’t really want to get into this messy field, but passive talent mining is becoming big.
Source candidates by enriching profiles with detailed background information.
Identify passive candidates who might be a good fit for open positions.
Analyze industry hiring trends and salary benchmarks.
Enhance candidate engagement with personalized communication.
datasources
linkedin
glassdoor
github
stackoverflow
Investors and Venture Capitalists:
I’m not interested in this field, and don’t understand it enough, but they are likely high paying audience.
Identify emerging startups and investment opportunities.
Gather detailed financial and market data about potential investments.
Monitor industry trends and competitive landscapes.
Track performance metrics and milestones of portfolio companies.
datasources
Crunchbase
SEC filings (EDGAR)
pitchBook.
Journalists and Content Creators:
Discover trending topics and emerging stories.
Gather background information and data for articles.
Identify experts and sources for interviews.
Monitor social media and other platforms for real-time updates.
datasources
News aggregators (Google News, Feedly)
Social media platforms (Twitter, Reddit)
Press release distribution sites (PR Newswire, Business Wire)
Consultants:
Likely paying audience there too. A consultant is highly paid per hour to guide other professionals. Seeking contracts, would like to find new leads and server its clients better or create campaigns.
Enrich client data for deeper insights and analysis.
Identify industry benchmarks and best practices.
Track regulatory changes and industry developments.
Provide data-driv5ooen recommendations to clients.
datasources
Industry reports and white papers (McKinsey, Gartner)
Market research databases (Statista, IBISWorld)
Product Managers:
Similar to marketers but drive products specifically. They need to understand markets and trends, competitors. This use case overlaps a lot with marketers and sales
Gather user feedback and sentiment analysis from various sources.
Identify market needs and gaps through enriched data.
Track competitor product launches and updates.
Inform product development with data-driven insights.
datasources
Customer feedback platforms (Trustpilot, G2)
Social media platforms (Twitter, Reddit)
Competitor websites
Academic Institutions:
Typically a university, engaging in research, users would either be academic staff or administration.
Identify funding and grant opportunities for research projects.
Track academic trends and emerging research areas.
Enrich student and faculty profiles with detailed information.
Facilitate collaboration with other institutions and researchers.
datasources
Academic databases (Google Scholar, JSTOR)
Grant databases (NSF, NIH)
University and institutional repositories
ResearchGate, LinkedIn
E-commerce Businesses:
Owner or business developer of an e-commerce. Not Amazon or Lazada obviously.
Small to mid size e-commerce usually have personal data about their customers since they have to deliver and take payments. This could expand into far more than just a name and address.
Enhance customer profiles with detailed demographic and behavioral data.
Track competitor pricing and market trends.
Identify potential suppliers and partners.
Segment customers for personalized marketing and recommendations.
datasources For customer profile linkedin and other relevant sites , but for marketing data that may be pretty tricky yet interesting to provide trending products from:
X
Reddit.
Nonprofit Organizations:
They typically look for funding. Data measure impact, more specifically back up their impact. Also on the look out for trends and opportunities for action, partership.
Identify potential donors and funding opportunities.
Enrich donor profiles with detailed information.
Track social and community trends relevant to their mission.
Monitor the impact of their initiatives with enriched data.
Track similar and selected set of other non profits.
Discover related other non profit
Event Planners and Conference Organizers:
They need guest speakers to stand out, and identify leads to target for promoting their events.
Identify potential speakers and influencers.
Gather detailed profiles of attendees and participants.
Track industry events and trends for better planning.
datasources
Event listing sites (Eventbrite, Meetup)
LinkedIn
X
Industry publications
Government Agencies: Probably know too little and would be terrible to deal with government workers as clients.
Gather data for policy-making and public services.
Monitor trends and public sentiment on various issues.
Track regulatory changes and their impact.
Freelancers and Gig Workers:
Similar to job seeker, but seeks project opportunities, gather client feedback, and track industry rates and demand.
Find project opportunities and freelance gigs.
Gather client reviews and feedback.
Track industry rates and market demand.
Datasources:
Upwork
Freelancer.com
Glassdoor
Human Resources Professionals:
Monitor employee satisfaction, benchmark compensation, and track industry HR trends. Looks for talent and evaluate competencies and relevance
Monitor employee satisfaction and engagement.
Seeks info about candidates
Evaluates candidates
Benchmark compensation packages.
Track industry HR practices and trends.
Datasources:
Glassdoor
Payscale
SHRM
LinkedIn
Startups and Entrepreneurs:
Identify investors, gather market insights, and track startup trends, competitors.
Identify potential investors and funding opportunities.
Gather insights on market entry strategies.
Track startup ecosystem trends and competitors.
Datasources:
Crunchbase
AngelList
PitchBook
TechCrunch
Educators and Trainers:
Identify training opportunities, gather course feedback, and track industry skill demands.
Identify potential training opportunities.
Gather feedback on courses and training programs.
Track industry demand for skills and competencies.
Datasources:
pluralsight
LinkedIn Learning
Glassdoor
Legal Professionals:
Track regulatory changes, gather case law, and monitor industry legal trends.
Track regulatory changes and compliance requirements.
Gather detailed case law and legal precedents.
Monitor industry legal trends and litigation outcomes.
Datasources:
Westlaw
LexisNexis
Government regulatory websites
Industry legal publications
Pretty scary, but in fact there is a lot of commonality in what all these personas need. So abstract the problems and data enrich the following set of entities with data points to cover multiple use cases.
If a consultant isn’t interested in the company’s financials, I don’t see why he wouldn’t be but, he may dismiss that metric and we will stop mining for it.
A marketer doesn’t care who works at his clients organisations? Fine, metrics that don’t get looked at don’t get mined after a while, and stop showing all together.
The point is, we don’t need to care, we abstract the problems and we measure what users care about to refine the capabilities of the platform.
Entities and Data Points¶
1. Profile¶
Data Points:
Name
Contact Information (Email, Phone)
Job Title
Company
Location
Skills
Experience
Education
Publications
Social Media Links (LinkedIn, X, GitHub, Telegram, Reddit)
Use Cases:
Job Seekers: Improve CVs, identify colleagues, network.
Marketers/Sales: Identify decision-makers, enrich fed CRM people data.
Researchers: Network with researchers in similar fields.
Recruiters: Source candidates, analyze backgrounds.
Investors: Identify startup founders, key personnel.
Journalists: Find experts and source influencers.
Consultants: Enrich client profiles, identify industry leaders, other consultant to partner with.
Product Managers: Identify user feedback sources, experts in the fields, industry leaders to follow.
E-commerce: Segment customers. plenty more.
Nonprofit Organizations: Identify potential donors, partners.
Event Planners: Identify speakers, influencers.
2. Company¶
Data Points:
Name
Industry
Revenue
Number of Employees
Location
Key Personnel (link profiles)
Past Personnel (link profiles)
Products/Services
Competitor Information
Customer Feedback
Market Position
Recent News and posts across socials
Financial Data
Use Cases:
Job Seekers: Company insights, culture, benefits.
Marketers/Sales: Potential clients, competitors, market position.
Researchers: Network with institutions, find industry trends.
Recruiters: Analyze industry trends, identify hiring practices.
Investors: Detailed financial and market data.
Journalists: Background information for articles.
Consultants: Industry benchmarks, client analysis.
Product Managers: Competitor analysis, market needs.
E-commerce: Identify suppliers, competitors.
Nonprofit Organizations: Track similar organizations.
Event Planners: Identify sponsors, speakers’ companies.
3. Job Opportunity¶
Data Points:
Job Title
Company (link to Company entity)
Location
Salary Range
Job Description
Required Skills
Application Deadline
Employment Type (Full-time, Part-time, Contract)
Use Cases:
Job Seekers: Identify job opportunities, improve applications.
Recruiters: Source candidates, analyze job market trends.
4. Lead/Opportunity¶
Data Points:
Lead Name
Company (link to Company entity)
Contact Information
Lead Source
Industry
Potential Value
Stage in Sales Cycle
Use Cases:
Marketers/Sales: Identify and track new leads, segment for outreach.
Consultants: Find new business opportunities.
5. Research Publication¶
Data Points:
Title
Author(s) (link to Profile entity)
Abstract
Keywords
Publication Date
Source/Journal
Citations
Full Text/Link
Use Cases:
Researchers: Access and summarize research, identify trends.
Academic Institutions: Track emerging research areas, facilitate collaboration.
6. Funding/Grant Opportunity¶
Data Points:
Grant Title
Funding Organization
Amount
Deadline
Eligibility Criteria
Application Process
Use Cases:
Researchers: Find relevant grants, funding opportunities.
Academic Institutions: Identify funding for research projects.
Nonprofit Organizations: Find funding opportunities.
7. Market Trend/Industry Report¶
Data Points:
Trend Name
Description
Impact Analysis
Industry (link to Company entity)
Key Metrics
Report Date
Use Cases:
Marketers/Sales: Track market trends, competitor activities.
Investors: Monitor industry trends, competitive landscapes.
Consultants: Provide data-driven recommendations.
Product Managers: Identify market needs, gaps.
Journalists: Gather data for articles.
8. Event¶
Data Points:
Event Name
Date and Time
Location
Organizers (link to Profile and Company entities)
Speakers (link to Profile entity)
Attendees (link to Profile entity)
Agenda
Use Cases:
Event Planners: Track industry events, identify speakers.
Marketers/Sales: Identify networking opportunities.
Researchers: Network with other professionals.
Consultants: Find speaking opportunities, industry events.
10. Supplied¶
Data Points:
Name
Description
Provider (link to Company entity)
Type (Product, Service)
Price
Availability
Ratings and Reviews
Use Cases:
Job Seekers: Identify relevant courses or tools for skill enhancement.
Marketers/Sales: Find productivity tools, marketing services.
Researchers: Discover relevant software, datasets.
Recruiters: Recommend tools for candidates or new hires.
Investors: Identify innovative products/services in the market.
Journalists: Explore new tools for reporting.
Consultants: Identify tools and services to recommend to clients.
Product Managers: Assess competing products.
E-commerce: Identify new products to sell.
Nonprofit Organizations: Find tools to improve efficiency.
Event Planners: Source event management services/products.
11. Project Opportunity¶
Data Points:
Project Title
Description
Client
Budget
Deadline
Required Skills
Use Cases:
Job Seekers: may want to jump onto a project
Consultants: may want to jump onto a project
Researchers: may want to take up a project
Academic Institutions: Track placements, facilitate collaboration.
12. Training Program**¶
Data Points:
Program Title
Provider
Duration
Cost
Curriculum
Reviews and Ratings
Use Cases:
All may want to skill up
13. Regulation/Compliance Requirement¶
Data Points:
Regulation Title
Description
Jurisdiction
Effective Date
Compliance Requirements
Related Cases
Use Cases:
All Who doesn’t pay taxes and may be elligible to benefits
14. Client Review/Feedback¶
Data Points:
Reviewer (nick)name
Review Date
Rating
Comments (sumrized)
Reviewer Profile Link
Use Cases:
All this ties to companies and products, so all
15. Funding Source¶
Data Points:
Source Name
Type (e.g., Angel Investor, Venture Capital)
Investment Range
Criteria
Contact Information
Use Cases:
Researchers always on the look out
Founders often on the look out
Academic Institutions always on the look out
16. Skill/Competency¶
Data Points:
Skill Name
Description
Industry Relevance
Certification/Training Programs
Demand Trends
Courses (link to Courses)
Use Cases:
All this ties any worker, to skill up via courses
It is still scary, but doable. We start somewhere, and we expand.
Matrix Table¶
Now that we’ve described the use cases and focused on the entiries to gather, we can map the likely relevance to personas.
Entity |
Data Points |
Job Seekers |
Marketers |
Researchers |
Recruiters |
Investors |
Journalists |
Consultants |
Product Managers |
Academic Institutions |
E-commerce Businesses |
Nonprofit Organizations |
Event Planners |
Government Agencies |
Freelancers and Gig Workers |
Human Resources Professionals |
Startups and Entrepreneurs |
Educators and Trainers |
Legal Professionals |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Company |
Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
Industry |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Revenue |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Number of Employees |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Location |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Key Personnel |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Products/Services |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Competitor Information |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Customer Feedback |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Market Position |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Recent News |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Financial Data |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Job Opportunity |
Job Title |
✔️ |
✔️ |
||||||||||||||||
Company |
✔️ |
✔️ |
|||||||||||||||||
Location |
✔️ |
✔️ |
|||||||||||||||||
Salary Range |
✔️ |
✔️ |
|||||||||||||||||
Job Description |
✔️ |
✔️ |
|||||||||||||||||
Required Skills |
✔️ |
✔️ |
|||||||||||||||||
Application Deadline |
✔️ |
✔️ |
|||||||||||||||||
Employment Type |
✔️ |
✔️ |
|||||||||||||||||
Lead/Opportunity |
Lead |
||||||||||||||||||
Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Company |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Contact Information |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Industry |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Revenue |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Key Decision Makers |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||
Research Paper |
Title |
✔️ |
✔️ |
✔️ |
|||||||||||||||
Authors |
✔️ |
✔️ |
✔️ |
||||||||||||||||
Publication Date |
✔️ |
✔️ |
✔️ |
||||||||||||||||
Journal |
✔️ |
✔️ |
✔️ |
||||||||||||||||
Abstract |
✔️ |
✔️ |
✔️ |
||||||||||||||||
Event |
Event Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||||
Date |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Location |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Organizers |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Speakers |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Attendees |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Agenda |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||
Social Media Post |
Post Content |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Author |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||
Date |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||
Platform |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||
Engagement Metrics |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||
Supplied |
Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
Description |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Provider |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Type |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Price |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Availability |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Ratings and Reviews |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|
Project Opportunity |
Project Title |
✔️ |
|||||||||||||||||
Description |
|||||||||||||||||||
✔️ |
|||||||||||||||||||
Client |
✔️ |
||||||||||||||||||
Budget |
✔️ |
||||||||||||||||||
Deadline |
✔️ |
||||||||||||||||||
Required Skills |
✔️ |
||||||||||||||||||
Training Program |
Program Title |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||
Provider |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||
Duration |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||
Cost |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||
Curriculum |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||
Reviews and Ratings |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||
Regulation/Compliance |
Regulation Title |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||||||
Description |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Jurisdiction |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Effective Date |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Compliance Requirements |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Related Cases |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Client Review/Feedback |
Reviewer Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||||||
Review Date |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Rating |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Comments |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Client Profile Link |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Funding Source |
Source Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||||||
Type |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Investment Range |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Criteria |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Contact Information |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||||||||
Skill/Competency |
Skill Name |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
||||||
Description |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||
Industry Relevance |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||
Certification/Training Programs |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
|||||||
Demand Trends |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
✔️ |
9. Social Media Post¶
Data Points:
Post Content
Author (link to Profile entity)
Date
Platform (Twitter, Reddit, etc.)
Engagement Metrics (Likes, Shares, Comments)
Use Cases:
Job Seekers: Monitor company culture and updates.
Marketers/Sales: Track real-time trends, customer sentiment.
Journalists: Discover emerging stories.
Product Managers: Analyze user feedback and sentiment.