Data Cleaning the Salesforce and Pardot Way – FREE Whitepaper

data cleansing

You have Salesforce and you’re getting ready to adopt Pardot. Or, maybe you just need to keep your data organized in Salesforce alone. Either way, data cleansing is crucial to your sales success.

After all, Salesforce associates data cleaning with a 29% increase in sales opportunities!

What does bad/messy data look like? You may have duplicates that need to be merged, missing field data, and/or unverified (and potentially incorrect) data. Any of these issues can prove extremely damaging to your sales process, especially when you start syncing with marketing automation like Pardot, Marketo, or Hubspot.

Our resident Salesforce experts (we offer personalized data cleansing!) recommend completing a Salesforce audit before integrating marketing automation as well as once a year as a maintenance best practice. This ensures that your Salesforce instance is running smoothly, efficiently, and accurately for your sales team.

When cleaning your data, here are qualities to strive for*:

Accuracy

  • The data was recorded correctly

Completeness

  • All relevant data was recorded

Uniqueness

  • Entities are recorded once

Timeliness

  • The data is kept up to date

Consistency

  • The data agrees with itself

Some common data problems to look out for*:

Changes in data layout / data types

  • Integer becomes string, fields swap positions, etc

Changes in scale / format

  • Dollars vs. euros

Temporary reversion to defaults

  • Failure of a processing step

Missing and default values

  • Application programs do not handle null values well

Gaps in time series

  • Especially when records represent incremental changes

With all of the available services out there, choosing the appropriate one for your instance can be tricky, especially if you aren’t familiar with the services available.

That’s why we made a whitepaper of recommended services that we and our clients have used.

Get the free whitepaper today! Just fill out the form below.

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*Exploratory Data Mining and Data Cleaning by Theodore Johnson