Overview
What You Need To Know
The organization was using Salesforce CPQ, every product, pricing rule, and configuration was playing an important role in daily operations. Before moving to Revenue Cloud, they required a simple way to understand what existed, what needed attention, and what was ready to move forward.
Why It Matters
As CPQ environments grow, managing thousands of products, rules, and records can become difficult. Small changes made over time can create duplicate data, overlapping logic, and unused configurations that make future improvements harder to plan.
What HIC Did
HIC created DataColor.AI CPQ Analyzer to help organizations understand their existing CPQ environment before migration. The solution brings product analysis, rule evaluation, and data quality checks together, giving teams a clearer view of their system.
Overview
What You Need To Know
The organization was using Salesforce CPQ, every product, pricing rule, and configuration was playing an important role in daily operations. Before moving to Revenue Cloud, they required a simple way to understand what existed, what needed attention, and what was ready to move forward.
Why It Matters
As CPQ environments grow, managing thousands of products, rules, and records can become difficult. Small changes made over time can create duplicate data, overlapping logic, and unused configurations that make future improvements harder to plan.
What HIC Did
HIC created DataColor.AI CPQ Analyzer to help organizations understand their existing CPQ environment before migration. The solution brings product analysis, rule evaluation, and data quality checks together, giving teams a clearer view of their system.
About the Company
DataColor.ai helps businesses make better use of their data by bringing AI, automation, and trusted data solutions together. They work with organizations to simplify complex technology challenges and turn data into real business value.
About the Company
DataColor.ai helps businesses make better use of their data by bringing AI, automation, and trusted data solutions together. They work with organizations to simplify complex technology challenges and turn data into real business value.
Challenges Faced
Complex Product Relationships
The company was struggling with complex product relationships as the CPQ environment had various product bundles with each having different levels of parent and child relationships, making it difficult to understand the configuration.
Too Many Product and Price Rules
While the business was growing, many product rules and price rules were added. Lately, this created an issue of duplication, similar, and unnecessary rules, and managing the CPQ setup became even more challenging.
Data Quality Issues
Due to several issues, the company was having duplicate records, outdated data, and unused fields across the CPQ environment, and manually finding those issues was way too complicated and required significant time.
No Clear Migration Plan
Prior to migrating from CPQ to Revenue Cloud, the company needed a clear 360 view of everything to plan accordingly. For instance, which records could be moved directly, which required cleanup and additional changes, etc.
Challenges Faced
Complex Product Relationships
The company was struggling with complex product relationships as the CPQ environment had various product bundles with each having different levels of parent and child relationships, making it difficult to understand the configuration.
Too Many Product and Price Rules
While the business was growing, many product rules and price rules were added. Lately, this created an issue of duplication, similar, and unnecessary rules, and managing the CPQ setup became even more challenging.
Data Quality Issues
Due to several issues, the company was having duplicate records, outdated data, and unused fields across the CPQ environment, and manually finding those issues was way too complicated and required significant time.
No Clear Migration Plan
Prior to migrating from CPQ to Revenue Cloud, the company needed a clear 360 view of everything to plan accordingly. For instance, which records could be moved directly, which required cleanup and additional changes, etc.
Challenges Faced
They were facing issues with
- Complex Product Relationships
- Too Many Product and Price Rules
- Data Quality Issues
- No Clear Migration Plan
The company was struggling with complex product relationships as the CPQ environment had various product bundles with each having different levels of parent and child relationships, making it difficult to understand the configuration.
While the business was growing, many product rules and price rules were added. Lately, this created an issue of duplication, similar, and unnecessary rules, and managing the CPQ setup became even more challenging.
Due to several issues, the company was having duplicate records, outdated data, and unused fields across the CPQ environment, and manually finding those issues was way too complicated and required significant time.
Prior to migrating from CPQ to Revenue Cloud, the company needed a clear 360 view of everything to plan accordingly. For instance, which records could be moved directly, which required cleanup and additional changes, etc.
Solutions Offered by HIC
CPQ Bundle Analyzer
HIC created CPQ Bundle Analyzer to help the company get a clear view of their complex product bundles as the CPQ environment had multiple levels of parent and child products. It shows the complete product hierarchy and related product rules, making it easier to understand the configuration and review the product relationships.
CPQ Rule Analyzer
We implemented CPQ Rule Analyzer to analyze the Product Rules and Price Rules available in the CPQ environment. The solution identifies duplicate, overlapping, and redundant rules, which helped the company find unnecessary configurations and understand which rules required changes before migration.
CPQ Data Quality Analyzer
We developed CPQ Data Quality Analyzer to check the overall data quality across the CPQ environment. It helped the company find duplicate records, unused fields, and outdated data across Products, Pricebook Entries, Quote Fields, Quote Line Fields, and Rules before starting the migration process.
Migration Readiness Insights
To give the company a complete 360-degree view of their CPQ environment, we combined product analysis, rule analysis, and data quality checks into one centralized dashboard. This helps them understand which records can be migrated directly, which require cleanup, and which need additional changes.
Solutions Offered by HIC
CPQ Bundle Analyzer
HIC created CPQ Bundle Analyzer to help the company get a clear view of their complex product bundles as the CPQ environment had multiple levels of parent and child products. It shows the complete product hierarchy and related product rules, making it easier to understand the configuration and review the product relationships.
CPQ Rule Analyzer
We implemented CPQ Rule Analyzer to analyze the Product Rules and Price Rules available in the CPQ environment. The solution identifies duplicate, overlapping, and redundant rules, which helped the company find unnecessary configurations and understand which rules required changes before migration.
CPQ Data Quality Analyzer
We developed CPQ Data Quality Analyzer to check the overall data quality across the CPQ environment. It helped the company find duplicate records, unused fields, and outdated data across Products, Pricebook Entries, Quote Fields, Quote Line Fields, and Rules before starting the migration process.
Migration Readiness Insights
To give the company a complete 360-degree view of their CPQ environment, we combined product analysis, rule analysis, and data quality checks into one centralized dashboard. This helps them understand which records can be migrated directly, which require cleanup, and which need additional changes.
Solutions Offered by HIC
The solutions which we offered to them
- CPQ Bundle Analyzer
- CPQ Rule Analyzer
- CPQ Data Quality Analyzer
- Migration Readiness Insights
HIC created CPQ Bundle Analyzer to help the company get a clear view of their complex product bundles as the CPQ environment had multiple levels of parent and child products. It shows the complete product hierarchy and related product rules, making it easier to understand the configuration and review the product relationships.
We implemented CPQ Rule Analyzer to analyze the Product Rules and Price Rules available in the CPQ environment. The solution identifies duplicate, overlapping, and redundant rules, which helped the company find unnecessary configurations and understand which rules required changes before migration.
We developed CPQ Data Quality Analyzer to check the overall data quality across the CPQ environment. It helped the company find duplicate records, unused fields, and outdated data across Products, Pricebook Entries, Quote Fields, Quote Line Fields, and Rules before starting the migration process.
To give the company a complete 360-degree view of their CPQ environment, we combined product analysis, rule analysis, and data quality checks into one centralized dashboard. This helps them understand which records can be migrated directly, which require cleanup, and which need additional changes.
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