How to Increase Sales With Salesforce CPQ & Data Integration

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Published on: January 19, 2022 Updated on: April 10, 2024 views Icon 366 Views

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  • Salesforce CPQ

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Sakshi Arora
Sakshi Arora LinkedIn

Assistant Manager- Content Marketing

Sakshi Arora is a seasoned content writer and marketer specializing in B2B topics such as marketing automation and website development. Leveraging her journalism background, she infuses her work with clarity and creativity, captivating audiences. Beyond her professional pursuits, Sakshi finds joy in writing about personal emotions, showcasing her introspective side and adding a unique touch to her portfolio.

Article Reviewed By: Rahul Saini LinkedIn

Table of Contents

One of the biggest challenges when scaling up a company is the increasing level of complexity in business operations. In addition, expansions often include introducing new product lines, better service packages, add-on benefits, and discounts. 

If you are not cautious about your strategy moving forward, you can muddle up existing deals or even turn away potential customers. That is why many companies opt for a CPQ (configure, price, quote) software implementation when venturing into the B2B environment. 

Salesforce CPQ is one of the most popular and effective solutions for SMEs and large corporations alike. However, to get the most out of Salesforce CPQ, you need to integrate it with your existing ERP system data. Better data to work with ensures that your CPQ solution functions seamlessly when you automate your sales process. 

If you are relatively new to the concept of Salesforce CPQ, here is a quick refresher. 

Salesforce CPQ is a robust sales tool that companies use to automate their sales processes. It allows them to generate accurate quotes pertaining to the sales quickly. Salesforce CPQ eliminates the need to generate and review quotes manually while eliminating the possibility of mistakes when sharing quotes with potential customers. 

Salesforce CPQ is part of the Salesforce Sales Cloud and helps sales teams configure products based on a customer’s requirements. Sales teams can also customize pricing and discounts before the quotes make their way to the customers.

The automation improves the sales process substantially, and if you integrate it with Salesforce CRO, you can complete the QTC (quote to cash) process from your Salesforce instance itself.

Now that you have a clear understanding of what Salesforce CPQ is and what it is used for, it is time you looked at how you can increase sales by integrating your data with Salesforce CPQ.

Let’s get started.

How You Can Increase Sales with Salesforce CPQ

  • Easy Product Configuration

You can use Salesforce CPQ’s robust configurator to manage complex product configurations. Moreover, you can improve the sales process with automated quotations, pricing, technical drawings, and product descriptions. 

  • Better Pricing Mechanisms

Pre-defined pricing hierarchies allow your sales teams to offer the best pricing to B2B customers for the entire range of products. Salesforce CPQ allows your teams to determine optimal discounts without sacrificing significant profit margins based on the quantity and volume of orders at hand. 

Also, Salesforce CPQ factors in several price adjustment features based on elements such as price overrides, markups, and discounts, thus giving you more control over customized pricing for B2B clients. 

  • Assisted Selling

Assisted or guided selling allows your customers to evaluate their business requirements and make purchases after taking factors such as operational costs, planned usage, pricing, and energy efficiency into the mix. 

  • Automated Proposal Generation

Automating the sales process allows your teams to close the proposals quickly and enables them to create comprehensive sales proposals without wasting time in manual calculations. 

This capability is further enhanced by offering e-signatures to approve the proposals legally and protect users from the risks associated with electronic transactions. In addition, parties involved in the transaction can ensure timely delivery of products and services within a customer’s budget using e-signature approvals. 

  • Robust Analytics

Salesforce CPQ’s analytics unlocks new data scan capabilities that factor in several business factors like price segmentation. As a result, it leads to optimized product offerings that are all in perfect sync with your client’s business needs. 

  • Lower Operational Costs

Salesforce CPQ can dramatically improve your sales teams' efficiency and help reduce costs involved within. With a natively integrated platform like Salesforce with Salesforce CPQ, you can enhance the internal company communications and reduce the overall operational costs from the revenue generated. 

  • More Transparent Sales Process

Salesforce CPQ provides you better visibility about revenue reports, top customers, and, most notably, the best-selling products on your roster. Moreover, it provides your sales teams with a better insight into the areas of the sales process that need improvement. In short, Salesforce CPQ gives you a bird’s eye view of all the sales activities and lets you improve your strategies with the business intelligence collected. 

Data Integration - Your Complete Guide for Seamless Data Management

Data integration is the process of combining and harmonizing data from different sources or systems into a unified and consistent format. In today's data-driven business landscape, where organizations gather data from multiple platforms, applications, and databases, data integration is crucial for effective data management and decision-making.

Within enterprises, data integration plays a pivotal role in ensuring that all departments and teams have access to accurate and up-to-date information. Whether it involves merging customer data from various touchpoints, consolidating sales data across branches, or synchronizing inventory figures with e-commerce platforms, data integration streamlines operations and enhances overall efficiency.

The benefits of data integration are manifold. Firstly, it provides a holistic view of data by breaking down silos and eliminating data fragmentation. This enables organizations to extract valuable insights, make data-driven decisions, and improve their overall competitiveness. Secondly, data integration enhances data accuracy and reliability by eliminating duplicate or conflicting information and ensuring data consistency across systems. Lastly, it promotes data governance and compliance, making it easier to adhere to regulatory standards and protect sensitive information.

Understanding Data Integration Tools

Data integration tools play a critical role in enabling organizations to streamline their data integration processes. These tools are designed to bring data from different sources together, ensuring that it is accurate, consistent, and reliable. In this section, we will dive into the world of data integration tools to understand their significance and functionality.

Overview of Data Integration Tools

Data integration tools provide a platform for connecting various data sources, such as databases, cloud applications, and legacy systems. These tools facilitate the smooth flow of data between different technologies, allowing organizations to consolidate and utilize their data effectively.

With data integration tools, businesses can eliminate the complexities associated with manual data extraction, transformation, and loading processes. Instead, these tools automate the data integration workflows, reducing the chances of human error and speeding up the entire process.

Key Features and Capabilities of Data Integration Tools

Data integration tools offer a wide range of features and capabilities that empower organizations to handle complex data integration tasks efficiently. Some notable features include:

  • Data Mapping: With data mapping capabilities, these tools allow users to define relationships between data elements from different sources. This ensures that the right data is mapped to the correct fields, creating a unified view of the information.
  • Data Transformation: Data integration tools enable users to transform data in various formats to ensure compatibility and consistency. From simple data conversions to complex data manipulation, these tools make it easy to achieve the desired data format.
  • Data Validation: These tools provide built-in data validation mechanisms to ensure data accuracy and reliability. They can perform checks on data integrity, data completeness, and adherence to predefined business rules, minimizing the risk of working with inaccurate or incomplete data.

Popular Data Integration Tools in the Market

The market is flooded with various data integration tools, each offering unique functionalities and advantages. Some of the popular data integration tools include:

  • Talend: Talend is an open-source data integration tool that provides a comprehensive set of features for connecting and transforming data across different systems.
  • Informatica PowerCenter: Informatica PowerCenter is a widely used data integration tool that offers a graphical interface, advanced transformation capabilities, and robust data connectivity options.
  • IBM InfoSphere DataStage: IBM InfoSphere DataStage is a powerful data integration tool that enables users to design, develop, and run integration tasks with ease. It offers a scalable and flexible architecture for handling large volumes of data.

These are just a few examples of the many data integration tools available in the market. Each tool brings its unique strengths and suitability, catering to different organizational needs and requirements.

Now that we have explored the world of data integration tools, let's move on to the next section, where we will dive into the enterprise data integration processes.

Best Practices for Effective Data Integration

Effective data integration is crucial for organizations to streamline their operations and gain valuable insights from their data. To ensure successful data integration, it is essential to follow key best practices and avoid common pitfalls. Additionally, real-life examples of successful data integration implementations can provide valuable insights and inspiration. Let's take a closer look at these best practices:

Key best practices for successful Data Integration

  • Define clear goals and objectives: Before initiating any data integration process, it is crucial to define clear goals and objectives. This will help guide the integration efforts and ensure that the right data is being integrated to meet specific business needs.
  • Establish data governance and quality standards: Implementing a robust data governance framework and ensuring data quality is essential for effective data integration. This includes establishing data quality standards, data ownership, and implementing processes to maintain data accuracy, completeness, and consistency.
  • Design a scalable and flexible integration architecture: Building a scalable and flexible data integration architecture is essential to accommodate future growth and changing business requirements. This may involve using modular components, adopting industry standards, and adopting technologies that support easy integration and interoperability.
  • Perform thorough data profiling and cleansing: Before integrating data, it is crucial to perform thorough data profiling and cleansing. This involves analyzing the data to identify any inconsistencies, errors, duplicates, or missing values. Cleaning and standardizing the data will ensure its accuracy and reliability.
  • Establish effective data mapping and transformation: Properly mapping and transforming data is critical for successful integration. This includes aligning data formats, resolving any schema conflicts, and ensuring data compatibility between different systems.

Common pitfalls to avoid in Data Integration

  • Lack of proper planning and documentation: Failing to plan and document the data integration process can lead to confusion, delays, and errors. It is important to define a clear roadmap, document integration processes, and involve key stakeholders to ensure smooth execution.
  • Insufficient data security and privacy measures: Data integration involves transferring and integrating sensitive data. Failing to implement proper data security and privacy measures can lead to data breaches and regulatory non-compliance. It is essential to establish secure data transfer protocols, access controls, and compliance with relevant data protection regulations.
  • Overlooking data validation and testing: Neglecting data validation and testing can result in inaccurate or incomplete integration outcomes. It is crucial to thoroughly validate and test data integration processes to ensure data integrity and avoid any potential issues that may arise during integration.
  • Ignoring ongoing monitoring and maintenance: Data integration is an ongoing process, and it is essential to establish regular monitoring and maintenance routines. This includes monitoring data quality, performance, and the overall health of the integration environment. Regular maintenance activities such as backing up data, optimizing performance, and resolving any issues promptly will help ensure smooth data integration operations.

Real-life examples of successful Data Integration implementations

Looking at real-life examples of successful data integration implementations can provide valuable insights and inspiration. Here are a few noteworthy examples:

  • Company X successfully integrated their customer data from various sources, including CRM systems, social media platforms, and e-commerce databases. This integration enabled them to create a unified customer view, resulting in improved customer segmentation and targeted marketing campaigns.
  • Organization Y integrated its supply chain data, including inventory, sales, and production data, to gain real-time visibility and optimize its supply chain operations. This integration helped them reduce inventory costs, improve order fulfillment, and enhance overall operational efficiency.
  • Company Z implemented a data integration solution that combined data from multiple financial systems, enabling them to generate accurate and timely financial reports. This integration streamlined their financial processes, increased data accuracy, and improved decision-making across the organization.

By following these best practices, avoiding common pitfalls, and drawing inspiration from real-life successful implementations, organizations can achieve effective data integration and unlock the full potential of their data.


When you implement Salesforce CPQ successfully, your company can leverage the capabilities to nurture customer relationships as it frees up the sales representatives. In addition, they won’t take much time adopting the new tool as they are already familiar with Salesforce CRM. 

Instead, the time saved battling the manual processes can be used to close more deals, reach out to more potential customers, and deliver accurate proposals every time. 

Once the team gains momentum, they can generate more quotes in a matter of minutes and not hours. In addition, it shortens the sales cycle, and the teams are able to configure offerings based on business rules and logic instead of guesswork.

Next Step? 

Do you want to implement the Salesforce CPQ solution with your Salesforce CRM in a matter of weeks, starting today? Then let an experienced team of hardcore Salesforce developers do it for you.

Growth Natives offers decades of collective Salesforce development experience with its team of specialists. Get in touch with us today for a quick Salesforce audit and let us help you get the most out of your business. 

Email us at or visit our website to learn more about our services.

Do you know of any other ways in which Salesforce CPQ can help companies increase their sales? Feel free to share your views in the comments or drop your opinions on our social media channels

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