Data Scraping Projects on Vollna

I need a web scraper / data extraction to collect structured business data for all Supermarkets and Hypermarkets listed on 2gis.ae across the UAE.

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**Data Fields Required:**
- Business Name
- Contact Number (Landline)
- Mobile Number
- Email Address
- Full Address
- Emirate (Dubai, Abu Dhabi, Sharjah, Ajman, Ras Al Khaimah, Fujairah, Umm Al Quwain)
- Website URL
- Business Category / Sub-category (e.g. Supermarket, Hypermarket, Mini Mart)
- Social Media Handles (if listed – Instagram, Facebook, WhatsApp)

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**Deliverable:**
- Clean, deduplicated data in Excel (.xlsx) and CSV format
- One row per business location (not per brand)
- Separate column for each emirate for easy filtering
- No blank/junk rows; all columns properly labeled

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**Requirements:**
- Proven experience scraping directories or similar listing sites
- Share sample output (10–20 rows) before full delivery for quality check
- Turnaround: within 3–5 business days

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**To Apply, Please Include:**
A sample scrape from 2GIS or a similar directory
Your estimated record count (how many listings do you expect?)
Your fixed price quote for this project

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Skills: Web Scraping, Data Mining, Scrapy, Data Scraping, Data Extraction

I have about 5000 business names with about 100 columns of other data for each in 12 CSV files (much of the information I do have is unimportant but I can delete the columns I don't need- the information might be handy to find the things I do need). I need to extract information as well as add to this. Some businesses have the owner's name already, many do not, and sometimes it will say it's the owner's name but it's incorrect - so all will need to be checked) with an accurate email addresses for the owner, (preferraby not just the info @ business. com). I need to:

-pare down the business names to those that meet my requirements:

-turn these into one google sheet
-add current, accurate business addresses
-confirm that the business is still in operation
-not a franchise, large corporation or chain unless it is a local chain
-locally owned, $95k - 8M in revenue (many have this information already - this will need to be checked)
-more FT employees than just the owner
-have a website or a physical location I can visit
-check phone number accuracy
-the accurate, current business address
-business social media addresses
-owner social media addresses
-add a brief business description

Once it is pared down to maybe 500 businesses, these will need to be mapped for me to visit the business. I have a great deal of publicly available information, but it will need to be accurately webscraped and confirmed. I should be able to get in my car, pick a section of town and go from business to business knowing the name and email address of the owner. Some of the information in the files is outdated, addresses have changed, business is owned by someone else etc. So all of it needs to be updated, confirmed, and email addresses and other information above added.

I need somone I can call on occasionally for various tasks like this, this is a good starting point. Confidentiality and accuracy is paramount.

Many thanks

Skills: Data Processing, Data Entry, Excel, Web Scraping, Web Search, Data Cleansing, Data Scraping, Data Analysis, Google Sheets, Data Management

If this task can be completed, along with payment I will provide a very positive review along with potential future works with higher budgets.

So I am looking for an experienced scraper/data engineer to collect 1-minute OHLCV price data through ChartExchange for roughly 5,000 stock tickers, ideally going back up to 5 years where available.

Required fields:

Open
High
Low
Close
Volume
Timestamp

The data should be pulled from ChartExchange chart pages, using the ticker URL pattern. For example:

https://chartexchange.com/chart/nasdaq-aapl/

The chart should be set to OHLC and 1 Minute data. I have a list of the roughly 5,000 tickers that would need to be swapped into the URL in place of aapl.

This will be a large-scale scrape, so I need someone skilled with batching, retries, rate-limit handling, clean storage, and reliable CSV/Parquet output.

Please apply only if you have experience with large-scale financial data scraping and can deliver a clean, scalable, well-organized solution.

I have about 5000 business names with about 100 columns of other data for each in 12 CSV files (much of the information I do have is unimportant but I can delete the columns I don't need- the information might be handy to find the things I do need). I need to extract information as well as add to this. Some businesses have the owner's name already, many do not, and sometimes it will say it's the owner's name but it's incorrect - so all will need to be checked) with an accurate email addresses for the owner, (preferraby not just the info @ business. com). I need to:

-pare down the business names to those that meet my requirements:

-turn these into one google sheet
-add current, accurate business addresses
-confirm that the business is still in operation
-not a franchise, large corporation or chain unless it is a local chain
-locally owned, $95k - 8M in revenue (many have this information already - this will need to be checked)
-more FT employees than just the owner
-have a website or a physical location I can visit
-check phone number accuracy
-the accurate, current business address
-business social media addresses
-owner social media addresses
-add a brief business description

Once it is pared down to maybe 500 businesses, these will need to be mapped for me to visit the business. I have a great deal of publicly available information, but it will need to be accurately webscraped and confirmed. I should be able to get in my car, pick a section of town and go from business to business knowing the name and email address of the owner. Some of the information in the files is outdated, addresses have changed, business is owned by someone else etc. So all of it needs to be updated, confirmed, and email addresses and other information above added.

I need somone I can call on occasionally for various tasks like this, this is a good starting point. Confidentiality and accuracy is paramount.

Many thanks

Skills: Data Processing, Data Entry, Excel, Web Scraping, Web Search, Data Cleansing, Data Scraping, Data Analysis, Google Sheets, Data Management

We are building one revenue engine for an entire portfolio of brands, and we need the person who feeds it. You find the leads. You clean the data. You turn HubSpot into a database our sales team actually trusts.

ABOUT CIULLO, INC.

Ciullo, Inc. is a holding company that operates a portfolio of brands across healthcare and technology. This is a long term role with one team, even though the brand you support will shift over time. Our first focus is Nsure, a revenue cycle optimization company that helps healthcare providers recover revenue they are currently losing. You can see what Nsure does at https://www.nsurecorp.com. Once Nsure is in strong shape, you move with us into the rest of the portfolio.

ABOUT ROLE

This is not pure scraping, and it is not pure data entry. It is both, and it sits next to our sales team every day. You own a list from first research through final handoff, and you take real pride in clean data.

WHAT YOU WILL DO

• Build The List. You research and build highly targeted prospect lists, starting with healthcare providers and the decision makers who own revenue cycle outcomes at Nsure.
• Clean The Data. You verify, deduplicate, and enrich every captured lead so the record is accurate and complete.
• Own HubSpot. You manage properties, segmentation, imports, and ongoing hygiene so the database stays solid.
• Feed The Team. You hand sales lists that connect, so callers reach the right person with the right context.
• Join The Huddles. You show up live, share what the data is telling you, and adjust targeting based on what sales learns.
• Scale Across Brands. You carry this same playbook into the other brands in our portfolio as we grow.

WHAT YOU MUST BRING

• Lead Generation Experience. You have built lists that produced real pipeline, ideally inside the medical or healthcare vertical for this first phase.
• Data Hygiene Discipline. You treat a clean, well structured database as a craft, not a chore.
• HubSpot Fluency. You know list building, property management, imports, segmentation, and deduplication cold.
• Eastern Time Availability. You reliably work United States Eastern Time business hours and join live huddles.
• Range. You are comfortable moving across different industries and brands as our focus shifts.

BONUS POINTS

• Healthcare Background. You have worked with revenue cycle management, medical billing, or healthcare technology companies.
• Tooling. You are skilled with ZoomInfo, Apollo, Definitive Healthcare, or LinkedIn Sales Navigator.
• Multi Brand Experience. You have supported more than one business line at the same time.

HOW WE MEASURE SUCCESS

We judge this role on the quality of the lists you deliver, the accuracy of the data inside HubSpot, and the conversation rates our sales team sees when they start dialing. A smaller list of verified, well targeted contacts will always beat a large list of guesses.

HOURS AND BUDGET

This is an ongoing hourly engagement with a budget range of $20 to $30 per hour, set by experience and the depth of healthcare list building you bring. We expect 20 to 30 hours per week to start, worked within United States Eastern Time. There is real room to grow into a larger role across the portfolio for the right person.

TO APPLY

Answer these in your proposal. Short and direct beats a long cover letter.

1. Describe a healthcare or medical lead list you built from scratch. Who was the target and how did you verify the data?
2. How do you keep a HubSpot database clean and well structured once leads start flowing in?
3. Which sourcing and enrichment tools do you rely on, and why?
4. Can you confirm that you can work United States Eastern Time and join live team huddles?

To prove you read this in full, start your proposal with the words "Clean List."

Data Scraper Needed for New Zealand Trade Business Leads

Job Description:

We are looking for an experienced data scraper / lead generation specialist to build a targeted list of trade and construction business leads in New Zealand.

The work will involve collecting publicly available business information from online directories, business listings, trade websites, Google search results, and other compliant public sources.

We are looking for New Zealand leads across trade categories such as:

* Builders
* Electricians
* Plumbers
* Carpenters
* Landscapers
* Painters
* Roofers
* Tilers
* Concreters
* HVAC
* Earthworks
* Renovation companies
* Other trade and construction-related businesses

**Data required where available:**

* Business name
* Contact name
* Email address
* Phone number
* Website
* Trade category
* City/region
* Country: New Zealand
* NZBN if available
* Source URL
* Social media links if available

Important requirements:

* New Zealand leads only
* Data must be collected from legal and publicly available sources only
* No private, restricted, hacked, or non-compliant data sources
* Must include the source URL for each record
* Emails should be cleaned and verified where possible
* Duplicates must be removed
* Data must be delivered in CSV or Google Sheets format
* Leads must be organised by trade category and location

Ideal candidate:

* Has previous experience scraping business directories or trade/business listings
* Can handle large datasets
* Understands data cleaning, deduplication, and email validation
* Can provide a small sample before starting the full job
* Communicates clearly and can work to agreed milestones

To apply, please include:

1. Examples of similar lead generation or scraping work you have completed
2. The tools or methods you use
3. How you remove duplicates and verify emails
4. Your estimated cost per 1,000 clean New Zealand leads
5. How many clean New Zealand leads you can deliver per week
6. Confirmation that all data will be collected from public and compliant sources only

We are looking for someone reliable for ongoing work if the first batch is successful.

J’ai un PDF de 50 à 100 pages dont je dois extraire uniquement les textes vers un fichier Excel clair et bien structuré.

Votre mission comprend :
• Copier fidèlement chaque bloc de texte dans les colonnes appropriées.
• Organiser la feuille : entêtes cohérents, formats unifiés, suppression des doublons.
• Effectuer un nettoyage de base : accents corrects, espaces superflus retirés, casse homogène.

Je recherche quelqu’un de rapide et méticuleux ; la précision prime, car la moindre erreur se répercutera sur les rapports que j’utilise ensuite.

Pour candidater, mettez en avant votre expérience pertinente en extraction de données PDF → Excel, vos méthodes de contrôle qualité et le délai dans lequel vous pouvez livrer le fichier final. Aucune mise en forme avancée n’est requise : une feuille Excel propre, prête à l’analyse, me suffit.

Skills: Data Processing, Data Entry, Excel, PDF, French Translator, Data Scraping, Data Extraction, Data Visualization, Data Analysis, Data Management

### Project Overview
We are looking for a skilled professional to help us with [briefly describe the main goal of the project, e.g., developing a custom script / designing a logo / fixing bugs in a web application].

### Scope of Work & Deliverables
The selected freelancer will be responsible for:
- [Deliverable 1, e.g., Writing clean, documented Python code]
- [Deliverable 2, e.g., Creating 3 initial design concepts for review]
- [Deliverable 3, e.g., Troubleshooting and testing the final output]

### Required Skills & Experience
- Strong experience with [Key Skill 1, e.g., Python / React / Photoshop]
- Good communication and attention to detail
- Ability to meet deadlines

### Project Timeline & Budget
- **Estimated Duration:** [e.g., 1 week, 2 weeks, ongoing]
- **Budget:** [e.g., Fixed price of $X / Hourly rate]

If you have relevant experience, please share a few examples of your past work. Looking forward to your application!

**Project description:**
I need a Google Sheet of active freight brokers operating in the Dallas-Fort Worth metro area, built from FMCSA's public carrier database. This is a one-time research and data filtering task.

**Data source:**
FMCSA "Carrier" dataset at: https://data.transportation.gov/d/6qg9-x4f8
Direct download (text/plain CSV): https://data.transportation.gov/download/6qg9-x4f8/text/plain
Last updated: May 8, 2026.

**Filter criteria (apply ALL):**
1. State = TX
2. Entity Type = Broker (NOT motor carrier, NOT freight forwarder)
3. Operating Authority Status = AUTHORIZED FOR PROPERTY (or AUTHORIZED FOR HHG). Skip NOT AUTHORIZED, OUT OF SERVICE, and PENDING.
4. Physical address in DFW metro. Include any of these cities: Dallas, Fort Worth, Plano, Irving, Arlington, Garland, Lewisville, Frisco, Carrollton, McKinney, Mesquite, Grand Prairie, Denton, Flower Mound, Allen, Richardson, Rowlett, Coppell, Southlake, Grapevine, Bedford, Euless, Hurst, Keller, Mansfield, Burleson, Cedar Hill, DeSoto, Duncanville, North Richland Hills.
5. Bonus filter (preferred but not required): Authority granted before 2015.

**Required output columns (Google Sheet, exactly in this order):**
1. Legal Name
2. DBA Name
3. USDOT Number
4. MC Number (with "MC-" prefix)
5. Physical Address
6. City
7. State
8. ZIP
9. Phone (if available in source)
10. Authority Type
11. Operating Authority Status
12. Authority Granted Date
13. MCS-150 Last Update Date
14. Insurance On File (Y/N)
15. Bond Status (if available)

**Quality requirements:**
- Only AUTHORIZED status entries included
- Deduplicate by MC Number
- Sort by Authority Granted Date (oldest first)
- Tab 1: filtered results. Tab 2: brief notes on any filtering decisions you made.

**Deliverable:**
Single Google Sheet shared to my email (provided upon hiring). Estimated 100–300 rows.

**Budget:** $40–$60 fixed price
**Timeline:** 48 hours from project start

**Skills required:**
- Intermediate Excel or Google Sheets
- Ability to download and filter large CSV/TXT files
- Familiarity with FMCSA data is a plus but not required

• **To apply, please answer this question in your proposal:** What is the difference between USDOT Status and Operating Authority Status in FMCSA data?
• Describe your recent experience with similar projects

We are seeking a detail-oriented **Lead Generation Specialist** to research and compile a targeted list of active podcasts that interview, review, or feature independent authors.

The purpose of this project is to identify relevant podcast opportunities for an independent author promoting a newly released urban mystery and political thriller novel. Priority should be given to podcasts covering:

* Independent and self-published authors
* Author interviews
* Books and literature
* Mystery, crime, thriller, and noir fiction
* African American literature and storytelling
* Urban culture and history
* Publishing and creative entrepreneurship

This is a research and lead-generation assignment only. Outreach to the podcasts is not required unless added as a separate project.

## Required Information for Each Lead

Each verified podcast lead must include:

1. Podcast name
2. Host or primary contact name
3. Contact email address
4. Official website
5. Instagram profile
6. TikTok profile
7. Facebook page
8. X/Twitter profile
9. YouTube channel
10. Podcast platform link, such as Apple Podcasts or Spotify
11. Contact or guest-submission page
12. Primary topic or podcast category
13. Brief explanation of why the podcast is a good fit
14. Date of the most recent episode
15. Any available guest-application instructions

If a particular social media account cannot be located, it should be marked **“Not Found”** rather than left blank.

## Lead Qualification Requirements

All submitted podcasts must:

* Be active or have published an episode within the past 12 months
* Regularly feature authors, books, publishing professionals, or related creative guests
* Have publicly available contact information or a clear guest-submission process
* Be relevant to independent authors or the book’s target readership
* Have legitimate websites, podcast listings, or active social media profiles
* Not be duplicates
* Not be generic or unrelated entertainment podcasts

Do not submit scraped, outdated, unverifiable, or automatically generated contact information.

## Deliverable

Provide the completed research in a clean Google Sheet or Microsoft Excel spreadsheet.

The spreadsheet should be organized into clearly labeled columns and separated into the following priority levels:

* **Priority A:** Strong match and clearly accepts author guests
* **Priority B:** Relevant podcast that appears open to guest pitches
* **Priority C:** Potential fit, but guest requirements are unclear

Please submit an initial sample of **five verified leads** so the research quality and targeting can be reviewed before completing the full list.

## Preferred Qualifications

The ideal freelancer will have:

* Experience with podcast, influencer, media, or author lead generation
* Strong online research and data-verification skills
* Experience using Google Sheets or Microsoft Excel
* Familiarity with podcasts, publishing, books, or literary marketing
* Excellent attention to detail
* The ability to distinguish strong promotional opportunities from low-quality listings
* Clear written English

Experience researching podcast guest opportunities for authors, entrepreneurs, filmmakers, or creative professionals is strongly preferred.

## Proposal Requirements

Please include the following in your proposal:

* A brief description of your lead-generation experience
* Examples of similar podcast, media, influencer, or author research projects
* The research tools or methods you use
* The number of verified leads you can provide
* Your estimated cost per lead or total project rate
* Confirmation that email addresses and podcast activity will be manually verified

Please begin your proposal with the words **“Author Podcast Leads”** so we know you reviewed the complete job description.

Accuracy and relevance are more important than volume. We are looking for qualified podcast opportunities—not a large list of unverified names.

I care more about the right 200 contacts than the wrong 2,000.

I'm looking for a sharp lead researcher to build me a list of decision-makers at iGaming companies (crypto, sweepstakes, bgaming, affiliate sites) and AI companion / Girflriend / chat app companies.

What you'll do:
Find founders, CMOs, marketing managers, and growth leads at companies in these two niches. Collect their Telegram handle (Or Whatsapp number), LinkedIn, and company website into a spreadsheet I'll provide.

The hardest and most important part: finding their Telegram username (Or whatsapp number). Most of these people list it in their X bio, Telegram channel admin lists, or affiliate directories. You need to actually verify each handle is real — not guess.

To apply — find me 1 free sample lead and include it in your cover letter

Pick one person who fits (founder, CMO, or marketing lead at a crypto casino, iGaming affiliate site, or AI companion app). Send me:

First Name, Last Name

Role + Company

Company Website

After starting the contract I will also require:

Telegram handle (or Whatsapp number) (@username) — verified
LinkedIn URL

One line on where you found the Telegram handle (X bio, channel, directory, etc.)

No sample lead in the cover letter = I won't read the application. This filters people who actually know how to do the work from people who copy-paste templates.

If your sample is solid, I'll move you to a paid test: 10 verified leads for $20. If that's also good → ongoing role at agreed rate (hourly or per-lead).

Ongoing target: 20–30 verified leads per day, 5 days/week.

Also include in your cover letter:

One sentence on why you'd be good at this

Project Title: Urgent: 100k Verified Food Service Leads (Ontario & Quebec) – 24hr Turnaround
Job Description:
I need a high-volume, high-precision B2B contact list for the food service and hospitality industry in Canada. This is a pilot project for a major liquidation brand; success here will lead to immediate follow-up projects for the rest of Canada and the United States. For every imaginable food service category
1. Target Geography:
Ontario, Canada
Quebec, Canada (Must include French-language categories: Boucherie, Épicerie, Traiteur)
2. Target Channels (Independent & Small-to-Mid Corporate):
We are looking for decision-makers (Owners, GMs, Chefs, Purchasing Managers) in:
Independent Restaurants & QSR
Cafes & Delis
Butchers & Meat Supermarkets
Catering & Banquet Halls
Ghost Kitchens & Commercial Bakeries
Note: Avoid national corporate headquarters. We want independent operators.
3. Required Data Fields (CSV Format):
Business Name
Contact Name (First & Last)
Job Title
Verified Business Email (Direct emails preferred over info@)
Phone Number (Format:proper north american style
City & Province
4. Quality Control:
Zero Duplicates: List must be cleaned.
95%+ Deliverability: Must be verified via NeverBounce or ZeroBounce.
Sample Required: Provide a 50-lead sample for Ontario/Quebec before the contract is awarded.
5. Timeline:
The full 100,000-lead file must be delivered within 24 hours.

I need a clean, fully-checked .xlsx file that lists every Euromillions draw from the very first one in 2004 right up to the most recent result. Each row should show:

• Draw date
• The five main numbers and two Lucky Stars (the complete winning combination)
• Winning jackpot amount

That will come to roughly 1,000+ draws, so accuracy and reliable sourcing are essential.

Alongside the raw data, please set up a simple way for me to spot combinations that have never been drawn. A helper sheet with a formula, pivot, or light VBA routine is fine—whatever is fastest and keeps the workbook lightweight. The goal is that, at a glance, I can enter or paste any five-plus-two combination and instantly see whether it has appeared before.

Deliverables
1. Euromillions-draws.xlsx containing the full historical data and the two extra columns requested.
2. A built-in search or flag system that pinpoints “never-drawn” combinations without the need for external tools.
3. A brief read-me tab explaining the data sources you used, the update method, and how to use the search feature.

If something is unclear, let me know before you start scraping or compiling so we both stay aligned.

Skills: Visual Basic, Data Processing, Data Entry, Excel, Data Scraping, Data Visualization, Data Analysis, Data Management

We’re looking for a detail-oriented data mining specialist to build a high-quality, targeted contact list of businesses relevant to the fencing and property services industry.

This is a one-off project with the potential for ongoing work if completed successfully.

Scope of Work:
You will research and compile a clean, accurate database of fencing contracor businesses with a focus on the areas of Sydney of Prestons/Kingsgrove/Auburn + 30km radius of these areas. Must Include accurate data of:

Company Name
Email Address (verified)
Phone Number
Location (Address + Postcode)
Industry (IE Fencing Contractor; Handyman etc)

Target Business Types:
Please focus on businesses that fall under (or closely relate to) the following categories:

Fencing Contractors
Gate installation
Landscaping companies (landscaper / landscaping)
Gardeners, yard services, pool service providers
Property maintenance / property services / home improvement

Please Note - These must be local fencing contractors, landscapers, home handymen, pool builders etc - not fencing suppliers or large building companies

Requirements:

Strong experience in data mining, lead generation, or web research
Ability to source accurate and up-to-date contact information
Use of reliable tools and methods (manual research, scraping tools, directories, etc.)
Deliver data in a clean, well-organized spreadsheet (Google Sheets or Excel)
Remove duplicates and ensure consistency

Nice to Have:

Experience working with construction or trades-related industries
Ability to verify emails (low bounce rate required)

Deliverables:

A spreadsheet containing a minimum of 2500 qualified leads
Clearly labeled columns and consistent formatting
No duplicate entries
Will be cross refenced to existing database of contacts

Startup Prospect Research Project

Objective

Identify early-stage startups in the San Francisco Bay Area that may benefit from outsourced or fractional marketing leadership. The goal is to build a targeted prospect list for outreach.

Target Companies

Focus on companies that meet most of the following criteria:

* Located in the San Francisco Bay Area/San Jose/Silicon Valley
* 5 to 50 employees
* Seed, Pre-Seed, or Series A stage
* Raised funding within the last 24 months
* Technology, SaaS, AI, creator economy, fintech, beauty tech, fashion tech, consumer brands, marketplace businesses, or related industries
* Founder-led organizations
* No VP of Marketing, Head of Marketing, CMO, Marketing Director, or marketing team listed on LinkedIn
* Limited marketing presence or evidence that marketing is being handled by founders

Research Sources

Use:

* Crunchbase
* Wellfound (AngelList)
* Y Combinator directory
* LinkedIn
* Company websites
* Public funding announcements
* News articles

For Each Company, Provide the Following Information

Company Name

Website URL

LinkedIn Company Page

Industry Category

Headquarters Location

Number of Employees

Funding Stage

Amount Raised (if available)

Most Recent Funding Date

Founder Name(s)

Founder LinkedIn URL(s)

CEO Name

CEO LinkedIn URL

Email Address of Founder or CEO (verified whenever possible)

Alternative Contact Email

Company Contact Form URL

Short Company Description (2-3 sentences)

Product or Service Description

Why This Company May Need Marketing Support

Examples:

* Founder is doing all marketing
* No newsletter
* No email capture strategy
* No content marketing
* No marketing leadership
* Weak LinkedIn presence
* Recently funded and growing
* Hiring salespeople but not marketers
* Website messaging is unclear
* No thought leadership content

Website Assessment

Score from 1-10 and include notes on:

* Website quality
* Clear messaging
* Lead generation capability
* Newsletter signup availability
* Blog or content presence
* Calls-to-action
* Founder visibility

LinkedIn Assessment

Score from 1-10 and include notes on:

* Founder activity
* Company page activity
* Thought leadership content
* Audience engagement

Priority Ranking

Classify each company as:

Tier 1:
Strong prospect. Appears to have budget and clear need for marketing support.

Tier 2:
Potential prospect. Some signs of need but less urgent.

Tier 3:
Low priority. Limited fit or unclear opportunity.

Output Format

Create a spreadsheet with all fields above.

Additionally, create a separate tab called “Top 50 Prospects” containing only Tier 1 companies ranked in order of outreach priority.

Goal

Deliver a list of at least:

* 50 researched companies
* 23-30 Tier 1 prospects
* Verified founder or executive contact information whenever available
* Brief notes explaining why each company is a strong fit for startup marketing services

Objective: Source verified, callable B2B contact lists of Australian trade businesses in defined regions and sectors, delivered in clean batches my team hands straight to our calling centre. The whole value is callable accuracy — a number that rings the right business beats ten that don't.
Target (per batch, I'll specify each round):

Sectors: roofers, electricians, plumbers (more added later)
Regions: NSW growth corridors — e.g. the Western Sydney Aerotropolis precincts, South West & North West Growth Areas (Leppington, Austral, Marsden Park, Box Hill, Riverstone), plus regional hubs (Wagga Wagga, Parkes, Coffs Harbour). Exact suburb list provided per batch.
Prefer established operators (signs of active trading), not dormant listings.

Required fields (CSV / Google Sheet, fixed column order):

Sector · Business name · Phone (the number that actually rings) · Suburb + corridor · Google rating · review count · website (URL or N) · listing status (operational/claimed) · source URL
Optional if available: ABN, email, contact name

Quality bar — this is what I'm paying for:

Every phone number current and correct, verified before it goes on the list (tell me your method).
Deduplicated by business across all sources — no business twice.
Permanently closed / non-operational listings excluded, not padded in to hit a count.
Australian numbers only, correctly formatted.
No guessed or fabricated numbers — sourced only from real public listings.
Flag which numbers look like personal mobiles vs business lines, so we can run compliance checks our end.

Sourcing rules: Legitimate public sources only (Google Business listings, public directories, industry listings). No login-gated or paywalled scraping that breaches a platform's terms — I don't want exposure on how the data was gathered.
How we work:

Start with a paid sample: ~150 records, one sector, one corridor. I review quality before anything scales.
On approval, weekly batches of [volume TBD], handed to my team on a shared sheet.
Payment per validated batch — not upfront for unverified bulk.
Quick daily or every-other-day check-ins with me/my team.

Before we start, four questions:

Have you sourced Australian trade or local-business leads before? Send 10–20 sample rows (de-identified is fine).
How do you confirm a phone number is current before it makes the list?
How do you dedupe and catch closed businesses?
Your daily throughput of verified records, and your rate?

You will watch 15 driving videos. Have google street view up at the same time and locate and list each and every turning the car takes manually - either by street name signs or google maps. Every road must be time stamped eg. Turned left onto homesdale road, turned right onto soho avenue, second left at the roundabout towards Ruislip road.

If you can list when they turn at traffic lights and when they park or which exit they take at the roundabout. All manually watched make sure the road names are not made up or guessed and the route links up to one big loop back to destination. Each video will be a YouTube video 20-30 mins long. Thank you

Hello!

I'd like to hire you for a job. I need lead generation in the week 200 leads at least. I need leads for finance their startup project seek money fonanivla help any project from 5 to 50$m and above.

I'm new on this platform please let me know how does this work.

Anthony M.

We are seeking a detail-oriented Data Enrichment Specialist to enhance our email database. The role involves verifying and updating email addresses, ensuring accuracy and relevance. The ideal candidate will have experience in data mining and entry, with strong attention to detail and communication skills. This is a part-time role with a short-term engagement.

• How do you approach difficult conversations with customers?

Your Responsibilities:

Building high-quality, targeted B2B lead lists based on specific criteria.

Setting up and managing automated cold email outreach sequences.

Requirements:

Proven experience in B2B lead sourcing and CRM/email tool management.

Ability to work independently and deliver high-accuracy data.

Strong communication and reliability.

I have a raw list of 61,060 company names/leads. I need a B2B data scraping expert to enrich this list and find executive contact info. The task involves handling a large dataset, indicating the need for proficiency in data management and possibly automation tools.

We need you to start tonight.
You will be sending the requests out between 11pm est and 9am est. Anytime between works.

Using the Cars From Home dealer outreach process in the loom video here you will send an online request to 25 car dealers in proximity to our client.

Please watch this 14 minute training and send a proposal if you believe you’re the right fit.
https://www.loom.com/share/80a0423b85a74c928755e64a0462a5ed

Simple task anyone can do you have to copy paste msg 100 per day and share a doc ,i will share it with you how to do

We need to gather 935 mobile numbers for the pre-defined contacts list

We are Sales Rocket, a UK-based AI automation agency helping businesses respond to leads faster using AI voice agents, missed-call recovery, out-of-hours call handling, and appointment-setting automation.

We are looking for a strong cold caller / prospecting specialist to help us generate qualified sales opportunities with UK businesses.

This is not generic telemarketing. You will be speaking to business owners, sales managers, lead generation companies, solar/home improvement firms, agencies, local service businesses, and other companies that rely on inbound leads.

The goal:
Book qualified discovery calls for Sales Rocket by identifying businesses that are losing revenue through slow lead response, missed calls, poor follow-up, or lack of out-of-hours coverage.

What you will do:

•⁠ ⁠Prospect UK businesses using agreed target sectors
•⁠ ⁠Call decision-makers and qualify interest
•⁠ ⁠Pitch the problem clearly: missed leads, slow response times, poor follow-up
•⁠ ⁠Position Sales Rocket’s AI voice agents and speed-to-lead automation
•⁠ ⁠Book qualified sales calls into our calendar
•⁠ ⁠Update CRM or tracking sheet with call outcomes
•⁠ ⁠Provide daily activity reports
•⁠ ⁠Help refine scripts based on real call feedback

Ideal candidate:

•⁠ ⁠Strong English-speaking ability
•⁠ ⁠Confident on the phone
•⁠ ⁠Experience cold calling UK businesses
•⁠ ⁠Comfortable speaking to owners, directors, and sales managers
•⁠ ⁠Understands B2B lead generation
•⁠ ⁠Can handle objections without sounding robotic
•⁠ ⁠Organised with CRM or spreadsheet tracking
•⁠ ⁠Results-driven, not just “hours worked” driven

Bonus if you have experience with:
•⁠ ⁠AI tools / automation
•⁠ ⁠SaaS sales
•⁠ ⁠Solar, home improvement, finance, legal, medical, or local service businesses
•⁠ ⁠Appointment setting for agencies
•⁠ ⁠GoHighLevel or CRM systems

You must be able to:

•⁠ ⁠Work from a clear call script but sound natural
•⁠ ⁠Track every call properly
•⁠ ⁠Qualify prospects before booking them
•⁠ ⁠Avoid wasting our time with poor-fit leads
•⁠ ⁠Communicate clearly in written English
•⁠ ⁠Be available during UK business hours

We will provide:

•⁠ ⁠Offer positioning
•⁠ ⁠Call script
•⁠ ⁠Target sectors
•⁠ ⁠Lead criteria
•⁠ ⁠Objection-handling guidance
•⁠ ⁠Calendar booking link
•⁠ ⁠CRM / tracking structure
•⁠ ⁠Training on the Sales Rocket offer

In your application, answer these:

1.⁠ ⁠What B2B cold calling experience do you have?
2.⁠ ⁠Have you called UK businesses before?
3.⁠ ⁠What industries have you booked appointments for?
4.⁠ ⁠How would you open a call to a UK business owner about missed leads?
5.⁠ ⁠What is your expected hourly rate or appointment-setting fee?

We are looking for someone practical, sharp, reliable, and commercially minded.

If you can book qualified meetings consistently, there is long-term work available.

We are looking for an experienced Web Scraping and Data Extraction Specialist to build multiple scraping tools for different data sources.

The ideal candidate should have strong experience in web scraping, web crawling, data mining, and automation, with the ability to collect and structure data from websites and social media platforms.

The work may include extracting historical web data, posts, comments, hashtags, engagement metrics, media files, product listings, articles, and other publicly available online data.

Responsibilities:

* Build reliable scraping tools for different websites and platforms.
* Extract, clean, normalize, and store structured data.
* Work with social media data, including posts, comments, captions, media, hashtags, and engagement signals.
* Handle historical data collection and recurring scheduled scraping.
* Use APIs where available and scraping tools where needed.
* Use AI tools and platforms to improve productivity, speed up research, assist with data classification, and support automation workflows.
* Ensure accuracy, stability, and proper error handling.
* Respect legal, ethical, and platform usage limitations.

Required experience:

* Strong experience with Python or JavaScript scraping tools.
* Experience with tools such as Playwright, Puppeteer, Scrapy, Selenium, Apify, or similar.
* Experience handling dynamic websites, pagination, rate limits, and anti-bot challenges.
* Good understanding of APIs, proxies, data storage, and automation.
* Ability to structure collected data into clean formats such as JSON, CSV, or database tables.
* Experience scraping or collecting data from social media platforms is highly preferred.
* Comfortable using AI platforms and tools to improve development speed, research, debugging, data analysis, and workflow automation.

We are looking for someone who can work independently, understand the target data requirements, and deliver clean, reliable, and maintainable scraping solutions.

We are seeking a skilled freelancer to scrape product names and images from several URLs. The ideal candidate will have experience in web scraping and data extraction, ensuring accuracy and efficiency in handling product information. This project requires attention to detail and the ability to manage data effectively.

Hi,
I need an experienced Python web scraper developer to extract data from a Hungarian industrial B2B e-commerce website. I will share the exact target URL and credentials in private chat with the selected freelancer.

The target website has approximately 8,000 products and a very deep category tree with approximately 1,000 categories/subcategories. Quality and perfection are my top priorities for this data extraction.

IMPORTANT NOTE: The website requires a username and password login to see the product prices. Your script must be able to handle session login/cookies to extract the data. I will provide temporary login credentials in private chat.

CRITICAL REQUIREMENT: I am only interested in hiring a freelancer who can deliver a complete and flawless data extraction. Every single product, full description, and every single image must be scraped without any missing data.

You will need to deliver TWO separate Excel files based on my specific template layouts, and multiple ZIP files containing the product and category images.

---

### SYSTEM RULES & LOGIC FOR COMPATIBILITY:
The script must follow these exact logic rules to match my e-commerce system layout:

#### 1. Product Sheet & Variant Grouping Logic:
- Parent-Child Mapping: Many products have multiple variants listed in a table. Each variant must become a separate row in the Excel. You must define the main product as the "Parent" and map the variants as "Children" by creating a Parent SKU column. The variants must point to their parent's SKU.
- SKU Generation & Cleaning: Take the original product code and strip out all spaces, commas, and slashes to make a clean, alphanumeric SKU. For example, a code like ABC-123/XYZ must become ABC-123XYZ. This clean SKU must be used in the SKU column and for image renaming.
- Manufacturer: Create a Manufacturer column and hardcode the site's brand name (I will provide the brand name in private chat) for all rows.
- Canonical URLs: Create a Canonical URL column. For all child/variant rows, this column must map back to the Parent product's SEO URL to avoid duplicate content issues.
- Category Page Visibility: Create a column for category page visibility. Hardcode the Parent row as 1 (visible on listing pages) and all Child/Variant rows as 0 (hidden from listing pages).
- Mandatory Price Columns: The import requires both Net Price and Gross Price columns. Prices must contain raw numbers only without currency symbols or spaces. Calculate the Gross price using 27% Hungarian VAT (Net x 1.27).
- Discount Prices: If you detect promotional prices, map the original price to the standard column, and the promotional price into the discount price column. Otherwise, leave blank.
- Descriptions & Link Cleaning: Extract descriptions keeping their original HTML source formatting (tags like p, ul, li must remain intact). Crucially, your script must clean or convert any relative internal links into absolute URLs pointing back to the source domain.
- Image Links & Versioning: Map the product image URLs into the image link column (separate multiple images with a vertical bar). Create an image version column and hardcode its value as 1 for all rows.
- Image Renaming: Main images must be renamed as the clean SKU (e.g., ABC-123XYZ.jpg). Additional images must use: [Clean_SKU]_altpic_[num].jpg (e.g., ABC-123XYZ_altpic_1.jpg).
- Status & Stock Columns: Hardcode Status as 1 (active), Stock Management as 1, Quantity as 0, and Purchasable if out of stock as 1.

#### 2. Product Filter Parameters Sheet / Logic:
- Extract technical parameters from the product specification tables as clean Key-Value pairs mapped to the parameters column, so I can use them as filters.

#### 3. Category Sheet Logic:
- Hierarchical Order: In the Excel rows, Parent Categories MUST be listed above/before their Child/Subcategories. This is critical because there are around 1,000 categories to map.
- ID Generation: Dynamically generate unique, incremental numeric IDs for each category and subcategory (e.g., 1001, 1002) and include Category ID and Parent ID columns to map the tree correctly.
- Category Image Renaming: Category images must be downloaded and renamed strictly using the newly generated Category ID (e.g., 1001.jpg) and bundled into a separate ZIP (Max 50MB).
- SEO Friendly URL: Generate an SEO URL for each category without any accents or special characters.
- SEO Tags: Populate TITLE tag and DESCRIPTION META tag columns using the category texts.
- Visibility Switches: Hardcode the values as 1 for visibility columns.
- Category Formatting: For multi-level categories, separate the levels using the vertical bar character.

#### 4. Product Image Renaming & ZIP Splitting Rules:
- Max 10 Images Limit: A maximum of 10 images per product is allowed (1 main image + 9 additional images). Do not extract more than 10 images per variant.
- ZIP File Size Limit: There is a strict 100MB limit per uploaded ZIP file for images. Your script must automatically split the downloaded images into multiple separate ZIP files, ensuring each ZIP file stays under 100MB.

#### 5. General System Rules:
- Language & Encoding: Hungarian language text. UTF-8 encoding is strictly mandatory. No broken characters allowed.
- File Size Limit: There is a 20MB upload limit for the Excel file. If the final Excel exceeds 20MB, deliver it as a compressed ZIP file.

---

**How to apply:**
- Please provide your fixed-price quote for the entire project.
- Confirm experience scraping login-protected websites.
- Confirm your script can handle the custom SKU stripping, Parent-Child mapping, HTML link cleaning, sequential Category ID mapping, Key-Value parameter extraction, the Max 10 images limit, and the automatic 100MB ZIP file splitting logic dynamically.
- Propose any ideas or improvements on how to make the data extraction cleaner or more robust.
- Tell me which libraries you would use (Playwright/Selenium preferred).

I need an expert to find 5 commercial businesses in the UK that are perfect candidates for commercial solar panel installation. For each business, I need a spreadsheet with:
Company Name
Owner/CEO First Name
Verified Business Email Address
LinkedIn Profile Link
Budget: $10

I've got a website with data published as Power BI, I need someone to scrape the data for me today as it'ill no longer be available tomorrow. Thank you

Book: Navigating ASEAN: Proven Strategies for Consumer Goods from Scholar-Practitioners

Rudolf Tjandra & Amalia E. Maulana | Palgrave Macmillan, 2025

Category: Business & Economics / International / Asia-Pacific

Summary:
Navigating ASEAN challenges the uncritical application of Western management frameworks to Southeast Asian consumer markets. Written by two scholar-practitioners with combined decades of executive and academic experience across the region, the book offers a grounded, analytically rigorous alternative — one built from the inside out rather than imposed from without.
The argument moves across brand strategy, consumer behaviour, organisational transformation, and market entry, anchored consistently in the specific conditions of ASEAN economies: high-context cultures, compressed urbanisation, fragmented retail infrastructure, and the outsized role of trust networks in commercial decision-making. The tone is neither polemical nor reverential toward existing literature. It is forensic.
Genre and Comparable Titles
Business strategy / international management. Comparable in ambition to Pankaj Ghemawat's Redefining Global Strategy and Jean-Pierre Lehmann's writing on Asian capitalism, though more operationally grounded. Closer in register to practitioner-academic hybrids than to pure management theory.
Core Arguments for Reviewer Engagement
The book makes three principal claims reviewers should test:
First, that ASEAN is a meaningful strategic unit — not merely a geographic convenience — and that consumer goods companies which treat it as such outperform those that default to country-by-country improvisation.
Second, that the practitioner-as-theorist is a legitimate and underutilised epistemological position in management scholarship, particularly for emerging market contexts where emic knowledge carries material strategic value.