Data Management
Digital Transformation
Salesforce
Data Seeding

3 CPQ Data Seeding Challenges and How To Overcome Them

Mike Melone
|
Sr. Content Marketing Manager, Own from Salesforce
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Even in today’s digital age, producing accurate pricing is still a challenge for many organizations. Outdated quoting and ordering systems rely on manual entry, resulting in quoting and pricing inefficiencies and underwhelming customer experiences. 

The solution? CPQ software. CPQ, or Configure, Price, Quote software, is a sales tool companies can use to provide accurate pricing with any given product configuration scenario. CPQ applications take into account optional features, customizations, quantities, and discounts, allowing sales reps to quote prices quickly and accurately.

While CPQ was originally used in industrial manufacturing to configure complex product sets, it's quickly catching on in industries like Telcom, Media, and High Tech. As organizations continue to move to the cloud and streamline operations and costs, CPQ is no longer cost prohibitive. 

According to a recent Global CPQ Software Market report, the CPQ software market is predicted to grow by $1.65B between 2022 and 2026. Salesforce CPQ in particular is one of the most popular CPQ software tools available. Hosted within the Sales Cloud platform, Salesforce CPQ seamlessly integrates with the Salesforce CRM platform to help customers manage all of their customer data in one place. 

But before you assume that implementing Salesforce CPQ will consist of just a few clicks and you’ll be good to go, you should consider a few things first. In this post, we’ll outline some common challenges with managing CPQ data, and how customers can use Own to streamline CPQ development changes.

Three common CPQ data seeding challenges and how to mitigate them

Here are three challenges you’re likely to face when it comes to configuring your CPQ data and how Own Sandbox Seeding can help:

1. Maintaining data relationships

Unlike other Salesforce packages, the majority of CPQ configuration is stored as data, so migrating changes to CPQ between environments involves data and metadata. While metadata can be moved relatively easily between environments, the number of data relationships between CPQ objects makes it difficult and time-consuming to deploy changes between environments.

For example, a single price rule can be used on multiple products and can create multiple records that require you to maintain the relationships when seeding environments. And it’s not just pricing that can be a challenge to manage. Products themselves can become very complex when needing to make changes to bundles, nested configurations, product rules, attributes and much more.

Solution: Make data integrity a priority

When sourcing a third-party data seeding solution, make sure that you can seed directly from production, maintaining all of your data relationships. This is possible with Own Sandbox Seeding. With this capability, you can get an accurate representation of your live production environment–without compromising your data integrity (or your sanity). It’s particularly important for CPQ price rules, as it maintains complex relationships between environments that are required for accurate, timely estimates. 

Let’s say you’re a wearable device software company deploying CPQ. Your unique suite of products have various attributes that help define the price based on the product configuration. Between sizing, distribution region, and connectivity, it’s a lot to keep track of–not to mention the fixed rules and dependencies that must be honored to produce accurate pricing. With Own Sandbox Seeding, you can ensure that these critical (and complex) relationships are preserved, filling your testing environment with representative data–and your team with confidence. 

Maintaining relationships doesn’t have to be a heavy lift, if you have the right solution.  With Sandbox Seeding, you can create, configure, and recycle CPQ templates. Rather than having to start from scratch every time you seed, you can get right to work, trusting specific data will go where it needs to when it needs to. 

2. Keeping data fresh

CPQ data changes all the time. Whether it’s Price Rules, Summary Variables, Product Rules, Quote Templates, or other configurations, Admins are constantly forced to keep up with changing requirements. While it’s easy to assume that your sandbox is filled with fresh, new data, this is not the case. 

A full sandbox, which has all of your metadata and production data, refreshes monthly, meaning you’ll have to wait 29 days for up-to-date data. A partial sandbox also has its limitations; you can only store a limited amount of data, without the option of deciding what that data is. 

For many Salesforce CPQ customers, integrating a billing solution like Salesforce Billing to their org is a next logical step in managing all selling and billing on one platform. An integration like this one will certainly require CPQ data to be reconfigured, so being able to quickly refresh your sandbox is key.

Regardless of what developer sandbox you are using, working with outdated or stale data will impact your CPQ capabilities– particularly if your product offerings change regularly or you rely on real-time pricing on dynamic promotions. This can also become an issue if you are integrating with other enterprise systems, as you can easily find yourself working with stale data. 

Solution: Seed what you want when you want 

It’s no surprise that working with fresh data will keep you at the top of your CPQ game.  But, you don’t have to limit yourself to the refresh capabilities provided by your CRM platform to achieve it. With Sandbox Seeding, you can own your CPQ development cycles. Sandbox Seeding allows you to incrementally seed new data into your sandbox to appropriately test. With a variety of seeding methods to update, add new, or clear specific records, Sandbox Seeding makes data adaptability a reality, supporting your data–and your business objectives– changing needs. 

3. Keeping data confidential

Due to the complexity of CPQ data and all of the possible features available for a given product configuration, many organizations choose to use an outside partner to help them with the initial implementation. While this is typically recommended, it’s worth pointing out that by doing this, you’re giving more people outside of your organization access to your data.

Providing unauthorized access to confidential information can be a huge liability for a company, and can easily happen easily when testing with real data. 

Solution: Anonymize sensitive data with ease

Having the most up-to-date data in your sandbox shouldn’t come at the expense of its safety. Own Sandbox Seeding allows you to anonymize sensitive data, keeping your confidential information out of harm's way. And the protection capabilities don’t stop there. With Sandbox Seeding, you can apply custom CPQ templates to mask sensitive information before it’s seeded to its destination. With the ease of reusable templates, your data’s present and future safety is never at risk–regardless of what you’re working on when. 

Streamline CPQ development cycles with Own

If you’re like most organizations deploying CPQ, you have an extremely complex configuration, involving lots of different criteria to take into consideration. Because of all of the complex relationships between the data, implementing new products or making changes using manual data load processes can be difficult and time-consuming. 

To ensure your CPQ development cycles are both efficient and effective, it’s critical to have systems in place that honor your data’s unique needs. With Own Sandbox Seeding, you can.  From reusable templates for specific use cases to data anonymization and relationship maintenance, Sandbox Seeding enables your team to get right to work when innovation strikes. Not even CPQ can put a price on that. 

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Mike Melone
Sr. Content Marketing Manager, Own from Salesforce

Mike Melone is a Sr. Content Marketing Manager at Own. With a passion for storytelling and expertise in SaaS data protection, Mike shares his insights to help organizations safeguard their critical data.

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Data Management
Data Management
Data Management
Digital Transformation
Salesforce
Data Seeding

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