The term data washing machine also known as contact washing machine started with Eloqua (now Oracle Marketing Cloud). It was a term used for the process of cleaning your data as it was coming into your marketing database, prior to it going to Salesforce or another CRM. The process is automated based on different business rules to try to get the data in a good shape prior to it being used. The reason for creating a data washing machine is to make sure data is all normalized, enriched, verified and stamped when it is coming from multiple sources.

While typically a contact washing machine is created in your marketing automation tool, the process can be used for other data types. Here are some common use cases to include when building your very own data washing machine:

  • Date and Source Stamp – When uploading data which can come from a web form, a manual upload or a connection to a different system it is important to record the source and the date that the data has appeared in your system. While, for most automated sources of data this is a given, it may need to be added as an additional stamp when someone uploads data directly into your database or marketing automation tool.
  • Standardization of Data – Different data sources can capture the same information differently. Having a look up table translating all of the different variations automatically, can not only help you with your lead scoring and segmentation but make it easy to run analysis. Example of standardizing data includes: state and country fields, industry and title fields as well as other custom fields. For data standardization look up tables, you can hire a data standardization company to help create your look ups!
  • Formatting Data – Depending on data source, you may need to convert a certain data fields into the proper format. This is typical for date formats, you may have one source reporting the date created as DD/MM/YYYY while another as MMM-DD-YYYY, unifying it to one standard format will help with filters and drill down analysis in the future.
  • Data Validation – Some data points may need validation or verification prior to making it to your CRM. You may install an automatic address verification process or an automat email validation step in your contact washing machine to ensure that only the correct data makes it.
  • Data Enhancement/Enrichment – You may have a scenario where you are purchasing third party data to complete your data. This could include things like psychographic information, appending contact information and adding other third party data points.
  • Duplicates – Duplicate records should be flagged and records should be updated instead of creating a new record. Duplicates can be matched by email or unique identifier. While no program is perfect, having some basic duplicate checks can help decrease duplicates significantly.
  • Bogus Records – Finally you may wish to add a step to exclude bogus or incomplete data from your CRM. This will ensure only the highest data quality records make it into your CRM. Bogus records can be tricky to uncover and should be reviewed periodically in case a legitimate record has been flagged as bogus.

Data washing machines work great on any new data that is being uploaded to your marketing automation tool or CRM. However, what about historical data? Historical data should be data cleansed to ensure that it is consistent with your latest washing machine processes, you can run your historical data through it, however, it is recommended to hire a third party data cleansing provider to help get your data quality to top shape!

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