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Sales Performance: Are you a laggard or a leader?
1.
Sales performance: Are you
a laggard or leader? Take our online self-assessment to see how you rate. Visit www.qlik.com/salesassessment to learn more. How leaders take control with analytics Does your approach to sales analytics measure up? Traits of laggard organizations Traits of leader organizations By connecting data from a variety of data sources, including CRM, marketing automation, and finance systems, Qlik® provides greater visibility across the entire sales cycle, allowing sales to better plan and improve performance. 1 Theme extracted from Aberdeen paper 2 http://www.forbes.com/sites/mckinsey/2013/07/22/big-data-analytics-and-the-future-of-marketing-sales/ 3 Aberdeen Group, Sales Analytics: Data-driven forecasting for better quota attainment © 2015 QlikTech International AB. All rights reserved. Qlik®, QlikView®, Qlik® Sense, QlikTech®, and the QlikTech logos are trademarks of QlikTech International AB which have beenregistered in multiple countries. Other marks and logos mentioned herein are trademarks or registered trademarks of their respective owners. 57% of revenue leaders have strong or pervasive use of sales analytics compared with only 41% amongst revenue laggards. Leaders recognize the critical link between sales analytics and sales performance – and use it as a competitive advantage. 56% of leaders have their employees using analytics in a self-service manner. 36% 57% 41% Leaders rate their speed of decision-making capabilities to be 36% greater than laggards3 . Gut-based, “happy ears” forecasts are driven by commissions and incentives rather than actionable data1 A lack of quality data, even though data is growing 40 percent per year worldwide2 Reliance on incomplete data sourced using the wrong tools results in decision making blind spots and missed opportunities End-of-quarter decision-making 'make-the-number' frenzy, where all deals are treated equally Only business analysts have access to data and the ability to produce insights Have a strong or highly pervasive use of analytics Have a high degree of trust in their data and let it guide their decision making Share operational data across business functions and take actions based on statistical insights Engage with BI on a weekly or frequent basis Enable their employees to use analytics in a self-service capacity
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