[Checklist] Improving Target Accuracy with SQL Utilization

basic information

The time required for creating lists and extracting data manually is significantly reduced, allowing sales representatives to focus more on their core tasks. By being able to list only highly accurate companies, unnecessary approaches are eliminated, improving the cost-effectiveness of sales activities. With the ability to set targets based on data analysis, a scientific sales system that does not rely on personal intuition or experience can be established. By combining customer attributes and behavioral history, it becomes possible to extract lists under complex conditions, enabling the identification of potential high-quality customers. The use of SQL for data extraction and utilization becomes ingrained throughout the organization, enhancing the speed of decision-making for data-driven sales strategies. The definitions of leads generated by the marketing department and targets pursued by the sales department are unified through data, facilitating smooth interdepartmental collaboration. 【Strengths and Features】 ■ Practical guidance on the use of SQL directly linked to sales results ■ Systematization of high-precision target extraction through SFA/CRM data utilization ■ Provision of SQL query templates to eliminate dependence on individuals

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Is your company being robbed of valuable time by "wasteful data extraction tasks"? 'PROBiZZ' is currently offering a free resource on the "Secrets to Improving Efficiency" through SQL utilization. This document thoroughly explains specific examples of SQL queries that dramatically enhance targeting accuracy and successful case studies that have improved sales efficiency. Let's transform your company's data utilization into a "system that directly connects to sales results" using the insights from this resource. Download the document and achieve a dramatic improvement in sales efficiency through SQL utilization.

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Applications/Examples of results

- An IT company that took several hours to create a target list, reducing the sales representatives' activity time, implemented a measure to build an automated extraction system using SQL under the guidance of 'PROBiZZ', shortening the list creation time to one-tenth and increasing sales activity time. - A manufacturing company that could not analyze the characteristics of past customers and had ambiguous target selection executed a measure to introduce an analysis that extracts commonalities of good customers using SQL with the support of 'PROBiZZ', enabling approaches based on a high-precision target list and improving the order rate by 12%. - A service company that was not fully utilizing the data accumulated in its SFA and had data utilization that was personalized implemented a measure to share SQL query templates across the organization under the guidance of 'PROBiZZ', establishing a system to standardize data utilization, allowing anyone to make data-driven decisions.