Robust Data Collection Increases Circulation of Real Estate Periodicals

28k potential customer records collected from six different counties for marketing campaigns.

Project Overview

Business Need for Real Estate Data Collection

The limited subscription database was the biggest challenge for the real estate periodic publisher. It was hindering their activities of mailing list creation and hence their ability to reach out to a wider customer base. To expand their circulation and obtain specific insights for customized marketing campaigns, they sought a partner to assist them in data collection for real estate periodicals with following objectives:

  • Collecting contact details, geography, county information, and more from disparate data sources including MLS sites, county websites, and property documents.
  • Extract data from real estate documents and standardize the dataset for normalcy and prepare it for further processing.
  • Customer records data collection followed by cleansing, verifying, and validating the database to make it accurate, comprehensive, and up to date.

Challenges of Customer Records Data Collection

Data collection of customers interested in real estate periodicals from disparate data sources posed several challenges, including:

  • Effectively scanning over 10 million property documents to be further used for extracting customer information like owner name, capture contact data, property details, and other property information.
  • Hiring and managing data professionals with domain knowledge of the geographical aspects involved in categorizing the collected data appropriately.
  • Developing a robust and agile data cleansing workflow to handle handling the substantial amount of unstructured data and preparing it for seamless integration into a CRM system.

Solutions and Results

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The aggregation process resulted in the compilation of over 28,000 potential customer records, encompassing multiple demographic data points from six different states and counties. To address the task of data collection for real estate periodicals, and create a marketing-ready, insightful database, a combined approach utilizing both manual and automated methods was implemented.

This framework covers data collection, collation, cleansing, and database creation, supported by a multi-tiered quality assurance process to ensure data accuracy and consistency.


  • A dedicated team of over 500 data collection experts were deployed to work on the project. They operated in shifts to efficiently aggregate data from various geographies and time zones, effectively managing fluctuating workloads.
  • Preparedness to handle volume fluctuations of up to 30% without compromising productivity or the quality of deliverables.
  • Custom scraper bots were leveraged to extract data from websites, and these bots were trained to bypass captcha codes when encountered.
  • To ensure uniformity and adherence to the client’s naming conventions, the database underwent standardization, including tasks such as formatting zip codes, conducting spell checks with capitalization for owner names, removing duplicate entries, and updating incomplete records.
  • Following a predetermined schedule, data was gathered and aggregated from diverse sources, including MLS websites, sales deeds, mortgage papers, and county websites.

Quality checks:

  • Implemented logical data controls and used rule-based validation algorithms to verify and validate every item within the records.
  • Thorough multi-layered quality assessments conducted by senior quality control personnel, following a predefined checklist and quality standards.

Business Impact

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