Academic literature on the topic 'Configure Price Quote (CPQ)'
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Journal articles on the topic "Configure Price Quote (CPQ)"
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Vijay, Kumar Musipatla. "Revolutionizing Sales: How Augmented Reality (AR) is Transforming Configure, Price, Quote (CPQ) Systems." European Journal of Advances in Engineering and Technology 12, no. 5 (2025): 14–22. https://doi.org/10.5281/zenodo.15607114.
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Augmented Reality (AR) is revolutionizing sales by transforming Configure, Price, Quote (CPQ) systems, enhancing how businesses configure products, determine pricing, and present proposals to customers. Traditional CPQ processes often rely on static models and manual pricing adjustments, leading to inefficiencies and limited customer engagement. By integrating AR, companies can offer interactive visual product configurations, real-time pricing adjustments, and immersive demonstrations, resulting in a more dynamic and personalized sales experience. This paper explores the impact of AR on CPQ systems, focusing on visual product configuration, interactive pricing, and quote generation, enhanced proposals, and product demonstrations. Reviewing existing literature and industry applications, this study highlights the advantages of AR-driven CPQ processes and presents a framework for integrating AR into sales strategies. The findings suggest that AR can significantly enhance customer decision-making, reduce sales cycles, and increase conversion rates, positioning it as a crucial tool in modern sales optimization.
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Umababu Chinta, Prof.(Dr.) Punit Goel, and Er. Om Goel. "The Role of Apttus CPQ in Modern CRM Systems: Implementation Challenges and Solutions." Darpan International Research Analysis 12, no. 3 (2024): 312–25. http://dx.doi.org/10.36676/dira.v12.i3.91.
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The advent of Configure, Price, Quote (CPQ) solutions has significantly transformed the landscape of Customer Relationship Management (CRM) systems, enhancing their ability to streamline sales processes, improve accuracy, and boost overall efficiency. Apttus CPQ, a prominent player in the CPQ market, offers a robust solution that integrates seamlessly with modern CRM systems to address complex pricing and quoting challenges. This research paper explores the role of Apttus CPQ in contemporary CRM environments, focusing on its implementation challenges and potential solutions. Apttus CPQ provides an advanced framework for managing product configurations, pricing strategies, and quote generation processes. By automating these critical aspects, Apttus CPQ aims to reduce manual errors, accelerate sales cycles, and improve the accuracy of quotes. Its integration with CRM systems, such as Salesforce, leverages existing customer data to generate accurate and customized quotes, enhancing the overall sales experience. However, despite its advanced capabilities, the implementation of Apttus CPQ presents several challenges that organizations must navigate.
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Reddy, Premkumar. "Challenges and Solutions: Implementing Machine Learning in Salesforce CPQ for Sales Efficiency." International Journal of Research In Science & Engineering, no. 46 (October 15, 2024): 13–24. http://dx.doi.org/10.55529/ijrise.46.13.24.
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The application of ML in Salesforce Configure, Price, Quote (CPQ) systems brings value to improve the efficiency of sales. Nevertheless, this integration experiences several issues. One problem is data management, which has always been an issue for ML, as such systems need large amounts of clean data to generate reliable predictions and use them for automation. Quite often, Salesforce CPQ working with dynamic price, multiple configurations, and real-time quoting addresses different data sources that are hardly consistent. Another issue is the adaptation of specific ML techniques to the requirements of the specific CPQ processes depending on the utilized data and the related development skills, as well as the high computational processing power. Furthermore, real-time performance for quote generation while processing machine learning models may complicate the efficiency of its sales. Some of the solutions to such challenges are the use of strong data integration techniques that enhance data on different platforms to ensure quality data is produced. It is also beneficial for organizations relying on Salesforce CPQ optimization to leverage custom KPIs and tailor machine learning models to improve precision in forecasts and better configure proposals. To complement MLOps performance, it is recommended to implement basic MLOps frameworks alongside cloud-processing power to cut through the latency hurdle as the solution adapts to scale. In addition, considering the integration of the ML models with existing automated Salesforce, one can develop predictive analytics for faster, less time-consuming quotes, lesser human input and fewer mistakes. By using these solutions within Salesforce CPQ driven by machine learning, organisations can unlock the ability to progress through cycles at a faster rate, contain accuracy in software configuration, and optimise operational processes.
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Jordan, Michelle, Gunnar Auth, Oliver Jokisch, and Jens-Uwe Kühl. "Knowledge-based systems for the Configure Price Quote (CPQ) process – A case study in the IT solution business." Online Journal of Applied Knowledge Management 8, no. 2 (2020): 17–30. http://dx.doi.org/10.36965/ojakm.2020.8(2)17-30.
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Software systems for the Configure Price Quote (CPQ) process of complex product portfolios have emerged in the sales function of companies recently. A flexible quote of complex products, in particular for a Business-to-Business (B2B) customer requires a wide variability of product features and configurations, along with the ability to deliver competitive quotes in short time. The CPQ system aims to reduce the process time, to increase the process quality by integrating information and data stored in several enterprise systems with codified explicit and implicit knowledge from individuals. As in most of the knowledge management systems, the openness of the knowledge holders to share and codify their individual knowledge is a critical success factor. In this case study, we look at the CPQ system implementation of a multinational Information Technology (IT) solution provider from a process perspective and with regard to both the technical and organizational challenges in a holistic approach. The article starts with an introduction to CPQ systems based on works from the Knowledge Management (KM) domain. After outlining our research methodology, we present the case together with a generalization of the CPQ implementation process. Our findings from the investigated scenario indicate positive influence of 1) the internal promotion of CPQ systems as technology innovation for motivating expert knowledge holders to collaborate; 2) an active preparation of the organizational environment for the upcoming changes; and 3) a hybrid agile implementation process.
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Ganesh Bollina. "Transformative impact of salesforce CPQ: A cross-industry analysis." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1410–17. https://doi.org/10.30574/wjaets.2025.15.3.1069.
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This article examines the implementation and impact of Salesforce Configure, Price, Quote (CPQ) solutions across diverse industries. Through analysis of five case studies spanning video telematics, healthcare equipment, technology, renewable energy, and Software as a Service sectors, this article identifies key patterns of transformation in sales processes, operational efficiency, and business outcomes. The article reveals critical success factors, including appropriate implementation partner selection, balanced customization versus standardization approaches, and thoughtful integration with existing systems. Results demonstrate that properly implemented CPQ solutions can significantly enhance quote accuracy, reduce approval times, centralize critical data, and improve overall sales performance regardless of industry-specific challenges. The insights provided offer valuable guidance for organizations contemplating CPQ implementations, highlighting the importance of viewing such initiatives as business transformation efforts rather than merely technical deployments.
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Karnani, Bihag. "THE EVOLUTION OF CPQ (CONFIGURE, PRICE, QUOTE) SYSTEMS: AI INTEGRATION AND REVENUE IMPACT." INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY 8, no. 1 (2025): 3370–87. https://doi.org/10.34218/ijrcait_08_01_242.
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Gautam Wadhwa. "Optimizing Q2C Efficiency with Salesforce CPQ: A Strategic Tagging Framework Approach." Journal of Information Systems Engineering and Management 10, no. 38s (2025): 1247–57. https://doi.org/10.52783/jisem.v10i38s.9331.
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The Quote-to-Cash (Q2C) process serves as a vital revenue-generating function for modern enterprises, yet it is often disrupted by inefficiencies in product configuration, pricing accuracy, and cross-departmental collaboration. This paper explores how Salesforce CPQ (Configure, Price, Quote) combined with a strategic tagging framework can streamline and optimize these workflows. By employing a mixed-methods research approach—including qualitative interviews with Salesforce architects, detailed hypothetical case studies, and in-depth technical analysis—we identify and validate the measurable impact of tagging on the Q2C lifecycle. Our findings reveal that organizations leveraging tags within Salesforce CPQ experience a 30–40% reduction in quote generation time, a 25% improvement in quote accuracy, and notable gains in collaboration between sales, legal, and finance teams. Tags, used as metadata elements, provide a scalable and intelligent way to classify products, pricing rules, and contracts, enabling dynamic logic, smarter automation, and improved user experience. The paper also introduces practical frameworks and best practices for implementing tags across Q2C operations, with specific applications in contract management and enterprise-level sales engagements. Ultimately, this research offers Salesforce administrators, CPQ developers, and business stakeholders a structured blueprint for reducing operational friction and driving greater agility in the revenue cycle.
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Venkata, Saiteja Kalluri. "AI-Powered Supply Chain Optimization: Integrating CRM, CPQ, and ERP for Enhanced Decision-Making in Boiler Manufacturing." Recent Trends in Cloud Computing and Web Engineering 7, no. 2 (2025): 8–17. https://doi.org/10.5281/zenodo.15239363.
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<em>In today’s competitive manufacturing landscape, the integration of Artificial Intelligence (AI) into traditional enterprise systems offers a promising pathway to optimize supply chain performance. This paper explores the convergence of Customer Relationship Management (CRM), Configure-Price-Quote (CPQ), and Enterprise Resource Planning (ERP) systems through AI to streamline operations in the boiler manufacturing industry. By leveraging predictive analytics, real-time data synchronization, and intelligent automation, the proposed AI-powered framework enhances decision-making across procurement, production, sales, and customer service. The study uses a case-based approach and simulation models to demonstrate efficiency improvements in lead time, quote accuracy, inventory control, and customer satisfaction. Results indicate a 22% reduction in order processing time and a 17% increase in on-time delivery rates, showcasing the potential of intelligent integration for industry-wide adoption.</em>
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Gopi, Krishna Kalpinagarajarao, Ranjith Gopalan Dr., and Swetambra Saloni. "Automating Subscription Billing with scalable CPQ solution." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 11, no. 2 (2023): 1–7. https://doi.org/10.5281/zenodo.14183838.
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The recurring revenue model enables scalability for subscription businesses, but it presents unique challenges, especially in retention. A seamless billing experience is crucial, as issues like delayed payments, invoicing errors, and complex subscription management can drive customers away. Manual billing is inefficient for recurring models due to difficulties with proration, mid-cycle changes, and compliance. A CPQ (Configure, Price, Quote) system simplifies subscription management by automating billing, renewals, revenue recognition, and offering customizable pricing options. These systems also help capture upsell and renewal opportunities, reducing revenue leakage and involuntary churn from failed payments. Oracle’s subscription management solutions address these challenges through automation, accurate pricing, and seamless integrations across billing, finance, and CRM systems. This unified approach enhances cash flow, provides valuable insights into customer behavior, and supports complex billing models. By implementing a robust CPQ solution, businesses canachieve scalable growth, minimize churn, and improve customer satisfaction.
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Reddy, Premkumar. "Machine Learning Applications in Salesforce CPQ Transforming Sales." Journal of Artificial Intelligence, Machine Learning and Neural Network, no. 46 (October 23, 2024): 27–38. http://dx.doi.org/10.55529/jaimlnn.46.27.38.
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This paper aims to understand the innovative disposals of machine learning applications on Salesforce Configure, Price, Quote (CPQ) applications more precisely how these innovations are revolutionizing software development. Salesforce CPQ is an ideal solution for organizations that want a modern tool to help them with their sales processes, and adding machine learning elements significantly improves the system. For example, the study analyses different cases where and how machine learning algorithm is utilised in the application of the following areas: pricing strategy, product configuration and sales forecasting. Upon collection of historical data, machine learning models are able to make computations of patterns that enables businesses to make quick analysis of the best strategies to use in an offer of various prices to the customers in an effort to enhance customer satisfaction. Furthermore, the application of I/A in the context of CPQ decreases the time engaged in manual configurations, liberating software development teams to work on other priorities essentially. These difficulties and strategies are enumerated in the paper: data quality issues and the impossibility of the Machine learning successful implementation without cooperation with other departments, specifically with Salesforce CPQ teams. In addition, it shares its vision on the tendencies in application of machine learning in CPQ systems with reference to software development paradigms. Finally, the scope of this research is as follows: The study will examine how the utilization of machine learning applications in Salesforce CPQ has changed traditional software development practices in today’s dynamic market environment by increasing efficiency and accuracy effectively, improving competitiveness within the market.
Dissertations / Theses on the topic "Configure Price Quote (CPQ)"
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Ahmed, Besam. "Design Automation of a Vacuum Chamber : Creating Rules for Configurator." Thesis, Uppsala universitet, Industriell teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-354480.
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The report is a degree project for the bachelor's level in Mechanical Engineering atUppsala University. The thesis was carried out at Scienta Omicron AB in Uppsala,Sweden and it is provided a basis determining rules for a vacuum chamberconfigurator that will be used by Scienta Omicron AB.Scienta Omicron AB wants to automate its vacuum chamber design to increasecompany productivity and profitability within this product line. This degree projectdescribes a basis for a configurator that will be used by the company later.This degree project begins by interviewing Scienta Omicron's R&D manager and theDesign Team to understand the company's needs and the reasons behind the desireto change the company's current process. After discussion with the company, aproject plan for the thesis is established to ensure that all parts of the thesis areperformed in time with good quality.The report presents briefly the theory of vacuum technology, especially regardingultra-high vacuum that is used by Scienta Omicron and several methods are used toachieve the project. The report ends with recommendations for Scienta Omicronwith the intention of continuously improving the result of this thesis i.e. implementingthe new process.An intensive study of vacuum chambers manufactured by the company is carried outby reviewing the company's email conversation between the design department andcustomers as well as chamber drawings in order to understand the design conceptand its limitations.As a part of the project, a requirement specification of the thesis has beendetermined and concept generating performed, resulting in two concepts," clashmodels" and" matrix". These enable the design and implementation of a vacuumchamber configurator by an external company specializing in customer productconfiguration.The chosen concept is clash models because it facilitates the implementation of theconfigurator later. A third-party company, Animech, which will implement the rulesdetermined in this thesis when constructing the configurator which will be used bySOAB. The configurator will be a tool that replaces the design team and gives themtime resources to develop new solutions and products.
Conference papers on the topic "Configure Price Quote (CPQ)"
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Ashokkumar, K., P. S. K. Kiriti, and O. Sai Sri Ram. "Custom Configure Price Quote." In 2019 Fifth International Conference on Science Technology Engineering and Mathematics (ICONSTEM). IEEE, 2019. http://dx.doi.org/10.1109/iconstem.2019.8918801.
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