Data cleansing is when you ensure that your data is up to date and the details you have are current for those on your database. It is estimated that dirty data costs the economy $3 trillion dollars a year. According to Experian, businesses lose 12% of their revenue due to bad data, meaning for every $1,000 you make you lose $120! Dirty data is no one’s fault as it happens due to a variety of reasons such as data not being updated regularly, incorrect information not been given at the start and clients not updating details when they change. Dirty data can be a time consuming data entry role and most often is a service best outsourced. Gen Leads have a team of cleansing experts that can combine all the various data sources you have, remove duplicates and all incorrect entries so that you can market to a clean database. Choosing to keep your dirty data can have a massive effect on your sales and marketing efforts making any lead generation strategy you have in place worthless. Wouldn’t you rather be talking to and selling to your customers rather than updating their details and losing their interest before getting to the real reason that you called! Bad data can result in bad decisions being made as your business doesn’t have the correct information to work off.


Data cleaning services include the process of detecting and correcting errors and inconsistencies from a data set in order to improve its quality. Our data cleaning services aim not just to clean the data, but also to bring uniformity to different data sets that have been merged from other sources. After cleansing, a data set should be consistent with similar data sets within the system. As a leader among cleansing companies in Australia, we provide a full suite of data cleansing services:

  • Import Data: Unclean data from your systems is imported into our cleansing system. Typically provided by yourselves in an Excel, CSV, or Tab-Separated Text file format.

  • Merge Data Sets: Data from multiple differently formatted sources (eg excel, csv, sql, sap, salesforce etc) is converted and merged into a common database.

  • Rebuild Missing Data: Wherever possible, missing information is recreated (e.g. Post codes, states, country, phone area codes, gender, web address from email addresses etc.).

  • Standardise Data:  Data is combined, separated or modified to ensure that the same type of data exists in each column. This step ensures that your contact’s first name, last name, email address, mobile phone number etc. are all in their respective columns.

  • Normalise Data: Similar data is normalised (e.g. mister, Mr., mr are all converted to Mr. Or street, st., strt. are all converted to St.). Telephone numbers are converted to their standard Telstra format, or otherwise as advised by yourselves. Email and web addresses formats are also checked, where provided, and reformatted as necessary.

  • De-Duplicate data: We use a custom-built fuzzy-matching algorithm to identify potential duplicates. Our methodology provides high accuracy matches with a tolerance for misspelling, missing values or different address orders. For mission critical data, these results are manually reviewed (by either ourselves or our client) and the database updated accordingly.

  • Verify & Enrich Data: Data is validated by voice to voice communication with the lead themselves. We call every lead on the database and verify the details which you need to ensure that your data is up to date.

  • Export Data:  Data can be exported in numerous formats for example, excel, csv, SQL database, XML, tiff, PDF, or as required. Typically, we return it in the same layout and format that we receive it.

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