Data Research: Compile Non-Hotel Lodging Operators in Bogotá, Colombia

We work with lodging operators in Bogotá, Colombia, and need a clean, verified list of non-hotel lodging providers in the city — specifically apart-hotels (apartahoteles), furnished-apartment buildings, and companies that manage multiple short-term rental units. We are not looking for traditional hotels. The core of this project is straightforward but requires care: Colombia's tourism registry (Registro Nacional de Turismo / RNT) is public and already classifies lodging by type, which gives us an authoritative starting list. Your job is to pull and filter that data, expand it with additional public sources, remove duplicates, and enrich each operator with verified contact information. The deliverable is a single, clean spreadsheet. Accuracy and no duplicates matter far more than volume. What You Will Deliver One spreadsheet (Google Sheets or Excel) containing a deduplicated list of non-hotel lodging operators in Bogotá, with these columns per operator: Identity Operator / property name Legal name (razón social) — from RNT where available NIT — from RNT where available RNT registration number and status (active / not registered) Type & Source Lodging type (apartahotel / vivienda turística / managed apartment portfolio) Where you found it (RNT / Booking.com / Google Maps / Instagram / other) Size (where available) Number of units or rooms Number of employees (from RNT) Location Neighborhood (zona) Address Google Maps link Contact (verified) Phone WhatsApp Email Website Instagram handle Owner or manager name (where findable) Two additional tabs with the raw source data (RNT export, and platform/Maps results) so we can trace where each row came from. Scope of Work — How to Build the List 1. Primary source — the RNT (start here) Colombia's Registro Nacional de Turismo is a public dataset on the national open-data portal (Datos Abiertos Colombia), dataset ID thwd-ivmp. Full download: https://www.datos.gov.co/api/views/thwd-ivmp/rows.csv?accessType=DOWNLOAD Filterable API: https://www.datos.gov.co/resource/thwd-ivmp.csv Live registry for verification: https://rnt.confecamaras.co/establecimientos Filter the data to: Municipality = BOGOTA D.C. Category = ESTABLECIMIENTOS DE ALOJAMIENTO TURÍSTICO Subcategory = APARTAHOTEL and VIVIENDA TURÍSTICA (exclude HOTEL) Status = ACTIVO This gives the registered operators with their legal name, NIT, and size. Note: the open dataset may not be fully current, so verify status against the live registry for the properties that matter. 2. Booking.com Search Bogotá, filter property type to Apartments and Aparthotels (this excludes hotels). Add any operators not already captured from the RNT. Capture name, address, and rating. 3. Google Maps Search each Bogotá neighborhood for terms like apartamentos amoblados, apartahotel, aparta suites, and furnished apartments Bogotá. Add net-new operators and pull address, phone, website, and Google Maps link. Target neighborhoods: Chapinero, Usaquén, Zona T / Parque 93, Chicó, Rosales, Santa Bárbara, Virrey, La Cabrera. 4. Instagram and operator websites Many local furnished-apartment brands market mainly on Instagram and run several buildings under one company. Check relevant Bogotá geotags and hashtags, and operator websites, to catch these and pull contact info (often a WhatsApp number in the bio). 5. (Optional) Airbnb / AirDNA If you have access to AirDNA or AllTheRooms, use it to identify operators managing multiple Airbnb units in Bogotá. This is a bonus, not a requirement — do not purchase a subscription for this project. 6. Deduplication The same building often appears under several names (e.g. "Apartamentos X," "Apart Hotel X," "X Suites") and with inconsistent address formatting. Match records by NIT first, then by name and address. Deliver one clean row per unique operator — duplicates are the main thing we will check for. 7. Contact enrichment For each unique operator, find and verify: phone, WhatsApp, email, website, Instagram, and owner/manager name where possible. Use whatever tools you normally work with. Contact details must be real and current, not guessed or generic placeholder addresses. Data Quality Requirements These are non-negotiable and will be checked before final payment: No duplicate operators. One row per unique business. All links must work. Dead or wrong URLs count as errors. Contact info must be verified. No fabricated emails, no generic info@ placeholders unless that is genuinely the operator's published address. Non-hotels only. Any traditional hotels in the final list are errors. We will spot-check a random sample of rows. If more than 10% contain errors (duplicates, dead links, wrong or fabricated contacts), we will request a revision before payment. Skills & Experience Required Proven experience building verified lead / data lists (please show a sample) Comfortable working with open-data / CSV exports and filtering large datasets Ability to read Spanish (the RNT data and most sources are in Spanish) Strong attention to detail and deduplication discipline Familiarity with contact-research and email/phone verification tools Nice to have: prior work with Colombian or Latin American business data; experience with Google Maps / Places data; familiarity with AirDNA. What We Provide These instructions, including the exact RNT dataset and filters The target neighborhood list and column schema Prompt answers to questions during the project We do not provide our internal tools or API keys — please use your own methods and tools. Milestones & Timeline We prefer a fixed price split into milestones so we can confirm quality early: Milestone 1 — Sample (small): RNT pulled and filtered, plus the first ~50 fully enriched rows in the final format, for our approval. This confirms format and quality before you build the full list. Milestone 2 — Full list assembled: All sources compiled and deduplicated into the master sheet. Milestone 3 — Enriched and verified delivery: Contact enrichment complete, quality checks passed, final files delivered. Target timeline: [set your window, e.g. 2–3 weeks]. Please propose your own if you see a faster or more realistic path. Budget We are open to fixed-price proposals with the milestone structure above. In your proposal, please tell us your total price and what it's based on (list size, verification depth, hours). We value accuracy over raw volume, so price for quality. (For your own planning: leave the budget open to bids to compare, or set a fixed number. This type of multi-source, verified, deduplicated list typically lands as a fixed-price project; the range varies widely with list size, verification depth, and freelancer location. Get 3–5 quotes before deciding.) Proposals that don't address deduplication and verification will not be considered.