Build a cohesive omnichannel strategy by standardizing profile data
Many of the customization features in Klaviyo rely heavily on the data stored as custom profile properties. Without Klaviyo Advanced KDP, it is difficult to maintain consistency across profile properties when it comes to details like capitalization, abbreviations, spacing, and overall data formatting consistency. With data pulling into Klaviyo across many integrations, managing the consistency of profile property values becomes increasingly complex. This is critical for driving an impactful omnichannel strategy. After all, you're trying to build a cohesive story for your customer across multiple platforms, wouldn't it make sense to have that same cohesive story reflected in your internal channels?
The data transformation tool is a point-and-click feature that allows you to set transformation rules that will run automatically when new data is ingested to Klaviyo. You can set formatting rules including remove quotes, remove spaces, remove special characters, and capitalize the first letter of every word. You can also set standardization rules to replace specific values with other values.
Once a transformation is saved, it's constantly running and will automatically transform any new values that come in.
Set up key transformations
Profile properties differ from account to account. The data in your Klaviyo instance will look entirely different from the data in another account. However, there are likely a few basic profile properties that you rely on very regularly for segmentation, targeting, and dynamic personalization. We recommend getting started with transformation rules for the key profile properties that you use most often:
Format first name
Apply a formatting rule to the $first_name property to capitalize the first letter of the name.
Revise date format
Ensure birthday properties are formatted as dates for use in segments, flows, and campaigns. Select Format birthdays as a pre-built transformation to store birthdays in a consistent date format (ex: February 17th, 2009 will become 02/17/2029).
Standardize a custom property
Select a custom property that you use regularly for segmentation or dynamic content personalization. If you collect profile property information through sign-up forms or surveys, it’s highly likely that the values in those fields are pretty inconsistent. Here are a few examples:
- Shoe size: could be written “7” or “7.0”
- Pet type: could be written “Dog”, “dog”, or “puppy”
- Do you live in an apartment? (or any other true/false question): answer could be “True”, “true”, “yes”, “Yes”, or “1”
Set a standardization rule that looks for any applicable value, and replaces it with the standardized version code. The example above shows a standardization rule for the $gender property.
Adjust segments and templates that utilize those properties
Once you have transformed your frequently-used custom properties, revise any segment definitions that included the original version of the property and switch the criteria to include the transformed version instead. You should see an increase in segment size once you start using the transformed property that more accurately aggregates profiles.
Do the same for any saved email templates, flow filters, or splits in your account that may include properties like First Name, or dynamically display logic based on transformed properties. Use only the transformed versions of these properties moving forward.
Merge up to 10 profile properties
The Merge transformation allows you to combine multiple custom profile properties into 1, allowing you to effectively use the data in segments and templates. The order of the properties included in the transformation determines how the values are prioritized during the merge, with items at the top of the list having the most priority. In the example above, Interest will be the primary property that gets set on profiles as part of this merge. You can combine up to 10 properties with a single Merge transformation.
Use a pre-built data transformation to standardize country names
Use a Klaviyo pre-built transformation to standardize country names to clean your data for better and faster segments and flow filters.