What is "harmonization"?
The concept of bringing together data from different sources with varying levels of detail, naming conventions and columns and transform them into one single cohesive data set. By centralising your data in one place Clarisights enables you to unify your marketing data and create classifications to supplement your data even with dimensions that do not exist in your source data.
There are two product features in Clarisights that let you harmonize data across sources
On Clarisights for every data channel (except Custom Analytics) you can create simple logical rules using a no-code interface to form classifications relevant to your business logic.
There are a few default dimensions across channels and these exist in hierarchical levels most common ones being
Account → Campaign → Ad Group → Ad
Other common channel hierarchies are
Advertiser → Publisher → Site
Advertiser → Insertion Order → Line Item → Creative
Account → Campaign → Ad Group → Asset
Account → TV Channel → Spot
Account → Campaign → Ad Set → Ad
Custom Dimensions can exist only on a single level
When you create a custom dimension on Clarisights, you're essentially grouping the different Accounts, Campaigns, Ad groups, etc based on some defined rules to classify your data, and adding more attributes than the source provides to "enrich" your data. This means that the created custom dimension is an attribute of the object on that level. When using parameters from different levels in your custom dimension rules, the custom dimension will exist on the lowest common level.
The best way to visualize this is to imagine that the data for the different hierarchies exists on different tables. For eg: in the campaigns table for Facebook, each row contains a single campaign and all the attributes for that campaign. When you create a new custom dimension, say "Country" that has the different countries as values and the rules are based on campaign naming convention such as "Campaign contains GB" for United Kingdom, you are creating another column in the Campaign table that has values for each campaign based on the rules that you provide. As a result all the campaigns that fulfil the condition above would have the Country field value as United Kingdom.
When multiple such paths or hierarchies exist in the same channel, parallel levels cannot be used together and widgets that do use them will show no data available for one of the dimensions or show that no data is available.
Eg: The dimensions "Ad" and "Asset" both cannot be used together when using the Google Ads Channel as they exist parallel to each other in the same channel with no direct relationship.
As a result of this you cannot create custom dimensions with rules that use dimensions from two parallel levels in the same channel such as Asset and Ad levels in Google Ads channel.
Other Levels of Detail
There is one more type of level in the data coming from ad channels. These are called segments (aka Breakdowns). For example, if you have one campaign targeting multiple countries or genders it would not be feasible to make this a part of your campaign naming convention. In such conditions you may choose to use a dimension that segments the campaigns by another dimension like Country Breakdown, Gender Breakdown, etc based on the availability of such segments. These exist on a level under the Campaign level.
It's always a good idea to keep parameters you have control over for campaign optimization as part of your ad object name. To create dimensions for parameters you do not have control over during campaign management you can rely on the segments provided by the ad channel.
Setting Up Custom Dimensions
Approach custom dimensions with the question "how do we want to slice our data?"
Some example classifications that you can create using custom dimensions on Clarisights to group data in various ways
Brand vs Non-Brand
Other Custom Classifications
💡 Pro Tip: Having a dependable pattern in naming your Account, Campaign, Ad Group, Ads across channels to identify different parameters will make it massively convenient to manage custom dimensions and add more detail that the source data may not carry natively. EG: use "retargeting" in the campaign names for various channels to later track performance of retargeting campaigns across channels in Clarisights.
These example classifications can all be cross channel and usable by anyone in the workspace and example rules look like
After you have your main cross-channel dimensions, users may also require other custom dimensions to group their data that are more team-specific or relevant to a certain use case. Following a naming convention while creating these dimensions and adding relevant descriptions to provide context of where the dimension can be useful will keep the workspace clean and clutter free.
Example: the Display advertising team needs to slice their costs data based on a parameter "Network" which is a part of the campaign name. This could be a new custom dimension on Clarisights as
[DIS] Network with rules such as
The list of dimensions that you decide on does not need to be final, you can always create new classifications and change existing classifications. You can also reach out to your CSM with Clarisights to upload classification rules in bulk.
Onto normalizing metrics across channels and creating new KPIs to track using Custom Metrics.