Combine related grouping values into categories in CRM analytical components

Combine related grouping values into categories in CRM analytical components

Hello everyone,

Analyzing large datasets can be challenging when dealing with numerous individual data points. It's often difficult to extract meaningful insights when information is scattered and ungrouped.

To address this, we're adding options to create categories for each grouping field in analytics components, which enables you to group related values for clearer and more insightful data analysis.

For example, let's say you're analyzing leads based on their sources and recognize that you've received leads from various channels, such as cold calls, advertisements, employee referrals, trade shows, and chats. To determine which leads were generated through active engagement versus passive engagement, you can categorize them as follows:

Active engagement: Cold calls, employee referrals, chats
Passive engagement: Advertisements, trade shows

This categorization helps classify records and analyze which sources involve direct interaction and engagement with potential leads (active) versus those that provided information or opportunities without direct interaction (passive).
Idea
How does this benefit you?
  • Simplified data analysis: Grouping similar data points reduces complexity and makes it easier to spot trends and patterns.
  • Enhanced visualizations: Categories make your charts and reports more readable and focused.
  • Custom groupings: You have the flexibility to define categories that make sense for your specific business needs.
You can create categories for two types of grouping fields:
  • Picklist fields
  • Numeric fields (currency, number, long integer, decimal, percent, formula, roll-up summary)
Let's look at categories for each of these grouping field types.

Categories for picklist fields



Imagine you have a picklist field called Country as a grouping field in a chart component. Analyzing each country individually can be overwhelming and time-consuming. Additionally, you might have business goals that require that you monitor or analyze these deals by grouping them into certain subcategories, such as regions/continents.
  • By creating categories, you can group countries into broader categories, like continental regions, or other custom categories based on your business needs.



    In this context, the Continent is set as the category field, with Asia, Europe, Africa, and North America set as its categories.



  • Instead of focusing on each country's performance, you can quickly see how the continents or regions are doing as a whole, which helps you make more informed decisions.

Categories for numeric fields



Another valuable enhancement to the category feature is the ability to categorize numeric fields, which enables you to organize numerical data into meaningful ranges that provide clearer insights and make analysis more intuitive.

Let's say you're working with an analytical component that includes the Deal Amount for all deals. Analyzing individual deal values can be overwhelming, especially with a large dataset. By categorizing deal amounts into ranges, you can quickly see which deals fall into higher or lower revenue brackets to make it easier to spot trends and act based on these insights.

For instance, you can create a category field called Deal size for the Amount grouping field. You can then group the values into categories such as Low-value deals for deals with amount below $15,000, Medium-value deals for deals ranging from $15,000 to $50,000, High-value deals for deals between $50,000 to $100,000, and Enterprise deals for deals exceeding $100,000.



When creating categories for a numerical field, range values are designed to be continuous to ensure no value unintentionally falls into the uncategorized "Others" section.



Alert
Points to be noted:
  • The category fields and categories you create are specific to an analytical component.
  • For a category field, you can add up to 10 categories and up to 20 values within each category.
  • The Others category includes grouping values that aren't assigned to any category, as well as records with no values for the field for which the category was created.
  • Category creation is supported for all types of analytical components except Anomaly Detector and Stage Component.
Info
Release plan:
These enhancements are currently available to all users across all DCs except the IN DC. The release status for the IN DC will be updated soon.
That's all for this enhancement. Please share your feedback in the comments. 


Thanks,
Nizamuddin




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