1.) Webpage: https://mmi.run/l/login 2.) Login/PW 3.) Click on “Real Estate Tab”, we are focused on; 1.) R.E. Agent Rank, 2.) R.E. Office Rank, 3.) R.E. Office Search. 4.) Select the following dropdowns, 1. Time Frame (we are using 12 months for now but could expand out further) 2. Narrow by County or Zip (we are using County as this results in higher data) 3. State (we are focusing on California for this 1 st data mining session) 4. County (we have already done Ventura, Santa Barbara, Riverside, San Bernardino, Orange, Los Angeles, San Diego and want to expand to all 58 Counties in California). Minimum Transaction Count (this is the minimum number of homes eit her listed “LS” or sold “BS” by each agent count. We want all agents that have bought or sold a minimum of 5 transactions in the last 12 months. We may lower this number to get a list of all agents in a particular county). 5.) Here are the raw results for Los Angeles County: As you can see, we are only able to copy and paste into an excel format. We are only able to copy and paste 25 records per page. 6.) When you select Bill Ruane, it opens a new window with additional information, We are trying to make sure we have the correct Phone, Email, Office Name and Street Address. Sometimes the agent may work for ReMax but be in a different location. There is also a small Google Icon next to the Agents name that with a back link to Google. We use these to try and find the most up to date contact information. It is very important our contact information be current. It sounds very “scam -ish” when you call someone and do not have the correct information. We are professionals and need our contact information to be the same. 7.) As you can see when I click on the Google link it takes me to Bill Ruane Google page, I can now determine that the information is correct and up to date. This is not always the case, and we might have to do additional data mining to make sure w e are 100% accurate. 8.) Below is the formatted data we are looking to receive, I have attached excel spreadsheet of the recent compiled data. We are missing probably 50% of the phone, address, city, state, zip information. We want as much as possible for marketing purposes. This is a slow process for me as I am not skilled at excel. There are approximately 215k agents in California, we in interested in maybe 35% of those for data. We then would like to continue this in Texas 148k and Florida with 223k. Probably looking at a “price per” type of contract rather than hourly compensation. We can discuss, pricing and details of timelines as we progress. Hello We are trying to build a Real Estate Agent Data Base for Direct Marketing. We are looking for someone that can scrape large amounts of data quickly and then convert to manageable data sheets. The person would have to be proficient in web scraping software such as Python, Scraper AI or any other rapid web scraping tools. We are using MMI.io website to gather our data and compile our list. We are using excel spreadsheet and need the following amount of information. Units Sold Past 12 Months//$$ Volume//First, Last Name//Company//Phone//Email// Address//City//State//Zip The website provides about 50% of all data needed. The remaining information we need must be gathered via a Google back link located within the website or simply outside of website via Google page. Do you have program that can help scrape pages and compile data into spreadsheet? Presently have about 300k records, we want to pull all Real Estate Agent data for California, Texas and Florida (or any other States we choose). This would probably be an ongoing project and we would probably want to pay on “other than” and hourly basis to be determined. Below are links to the website and Youtube videos on how the website works. I have a detailed document if you wish to see that explains in detail how the website and process works. Let us know your thoughts and ideas to see if we are a good fit! Thank you for your time. Curtis Puckett https://mobilitymi.com/ https://www.youtube.com/watch?v=gZ2R_1khvTU&pp=ygUGbW1pLmlv https://www.youtube.com/watch?v=n7v7nbSDVyo&pp=ygUGbW1pLmlv https://www.youtube.com/watch?v=Of1EE0HfgCI&pp=ygUGbW1pLmlv
