As the company reviewed its pricing structure, several operational and system-related challenges emerged that were impacting the efficiency and accuracy of the quoting process:
Price changes exposed limitations in existing systems
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The review of the pricing structure was followed by a series of price increases. This process revealed that the existing CPQ setup was not flexible enough to easily accommodate pricing updates and product adjustments.
As pricing and product data evolved, maintaining consistency across systems became increasingly difficult and time-consuming.
Overly complex product and pricing structure
The original configuration of the CPQ environment was more complicated than necessary for everyday sales operations.
The way products and pricing were structured created unnecessary complexity for internal teams, making routine tasks such as updating configurations and preparing quotes more difficult than they should have been.
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Reliance on external price books and manual cross-referencing
Sales teams frequently had to consult external price book documents hosted on a company portal and then manually verify the same information in the CRM system.
This dual-system workflow created inefficiencies, slowed down the quoting process, and increased the risk of discrepancies between documented pricing and system data.
Key Business Challenges
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Fragmented product information
Product details and part numbers were not fully centralized in one place.
Sales representatives had to search through separate resources to confirm full part numbers and product configurations, which complicated the quoting process and created friction during sales cycles.
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Difficulty navigating large product catalogs
Users often faced extensive lists of product options that were not always clearly tied to specific base products.
Because options for multiple products appeared together, it was difficult for sales teams to quickly identify which options were relevant for a particular configuration.
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Limited ability to restrict product options by model
The existing system did not effectively limit product options to the models they were designed for.
As a result, users were exposed to options that did not apply to the product they were configuring, increasing the likelihood of errors and making the configuration more confusing.
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Time-consuming product selection process
Without intuitive filtering mechanisms, such as selecting products based on attributes like horsepower or voltage, sales teams had to spend additional time manually searching through product data to identify the correct configuration.