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What is quoting software?
Quoting software helps organizations accurately and efficiently predict costs and make estimates. Quote management applications can distribute quotes across a business, enable automatic pricing based on historical data, and easily integrate data such as customer profiles, case-specific terminology, and sales tax rates. Many quoting system tools directly integrate with accounting tools, enabling the automatic conversion of price quotes to invoices.
The benefits of quoting software
- Improve efficiency: Quoting software collects and analyzes data from multiple sources, including cost databases, emails, customer relationship management software, and past projects to generate quotes and create proposals. These systems eliminate cash transactions by allowing managers to transfer and receive funds online, while dashboard and reporting modules let managers track business performance and take corrective action. All of these functionalities combine to improve efficiency across organizations.
- Increase accuracy: Quoting tool helps organizations create automated proposals, reducing the chance for and instance of human error. These systems often include multiple tools to facilitate such automation, including email tracking, proposal generators, and cost monitors, helping businesses quickly create quotes and swiftly respond to requests for proposals (RFPs).
- Brand building: Quoting tool lets organizations send proposals that include customized logos, icons, and specific colors in line with their brand guidelines to ensure customers recognize their business. Consistent brand communication helps organizations build and maintain brand recall.
Typical features of quoting tool
- Contact management: Create and maintain contact records.
- Quote/Proposal creation: Create professional-looking, branded proposals and maintain a central repository of previous proposals.
- Third-party application integration: Integration with related third-party applications (e.g., CRM software, sales automation software, accounting software) to reduce data re-entry and improve workflow efficiency.
- Automated quoting: Automatically generate rule-based quotes for clients based on their requirements, stock availability, and supply and demand rates.
- Discount management: Configure rules for discounts based on amount/quantity ordered.
- Pricing management: Create rule-based pricing for stocks and manage prices according to changing demand.
Considerations when purchasing quoting tool
- Integration with other solutions: Bid professionals need quoting tool that can seamlessly integrate with their existing software and tech tools to accurately predict costs and generate quotes accordingly. The quoting system must be able to transfer and receive data from third-party solutions, such as cost calculators, bid estimators, predictive analytics, and dashboard solutions. Software buyers should only shortlist quoting solutions that integrate with their existing systems.
- Affordable cloud deployment: Cloud computing has transformed the technology landscape, and more and more vendors are moving their software infrastructure to the cloud. By adopting cloud-based deployment, users can reduce capital expenditures and obtain better asset security on a limited budget. Small businesses without sizable software budgets should shortlist quoting software options that don't exceed budgetary constraints.
Relevant quoting software trends
- Conversational bots will transform customer support: With mainstream adoption of chatbots and conversational technology, the rules of customer engagement will continue to transform. According to our research , almost seven out of ten small businesses are currently using or plan to use conversational technology within the next few years. As conversational customer support bots continue to become more popular, expect quoting tool vendors to take notice and begin offering such features.
- Predictive analytics and artificial intelligence (AI): Improvements in data management and data processing technology have enabled organizations to create machine learning algorithms that accurately predict the cost of goods sold and forecast sales. Expect this adoption to expand, as according to our research , 50% of businesses are interested in implementing AI tech within the next two years.