Qlik > 实例探究 > Increasing marketing efficiency and optimizing lead scoring with Qlik AutoML

Increasing marketing efficiency and optimizing lead scoring with Qlik AutoML

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公司规模
Large Corporate
地区
  • America
国家
  • United States
产品
  • Qlik AutoML
  • BigSquid.ai’s Kraken
技术栈
  • Machine Learning
  • Data Analysis
  • CMS
实施规模
  • Enterprise-wide Deployment
影响指标
  • Productivity Improvements
  • Customer Satisfaction
技术
  • 分析与建模 - 机器学习
  • 分析与建模 - 预测分析
适用行业
  • Professional Service
适用功能
  • 销售与市场营销
用例
  • 补货预测
  • 质量预测分析
服务
  • 数据科学服务
关于客户
Naylor Association Solutions is a company that empowers professional associations to deliver greater value, engage with its members, and increase non-dues revenue by providing a variety of services. They help their customers with things such as member communications by delivering magazines, newsletters, or directories to association members. They also help associations provide career solutions for their members, plan and execute trade shows and events, association management software (AMS), and assist association members to maintain certifications.
挑战
Naylor Association Solutions was facing a challenge in their marketing-sales processes, particularly in lead scoring and qualification. The company was using a CMS that required account executives to fill out nearly 30 different data fields, which were then used by the marketing automation platform for scoring and qualification. This process was time-consuming and frustrating for the salespeople, who viewed many of the fields as unnecessary. On the other hand, the marketing team couldn't provide a better justification for the data other than they needed it for their processes.
解决方案
Naylor Association Solutions decided to adopt machine learning to improve efficiency in lead scoring, lead generation, and data analysis. They evaluated several options, including self-service platforms, providers that would build a 100% custom algorithm for their specific use case, and automated machine learning solutions like BigSquid.ai’s Kraken. They chose BigSquid.ai due to the ease-of-use of the platform and rapid time to value. The implementation of this solution allowed Naylor to optimize lead scoring and significantly reduce the number of fields required in the CMS, saving their salespeople from gathering unnecessary data and wasting time filling in unnecessary fields.
运营影响
  • Naylor has identified several areas of ROI that extend beyond the traditional measurable results of dollars saved or loss decreased.
  • Working with the customer service and data science teams at BigSquid.ai, Naylor has been able to optimize lead scoring and significantly reduce the number of fields required in the CMS.
  • This has saved their salespeople from gathering unnecessary data and wasting precious time filling in unnecessary fields.
  • Marketing has become more efficient. Through the insights gained from using Kraken, Naylor has realized their ideal target customer is slightly different than what they originally believed and with this new information are able to create highly targeted messaging.
  • They now have greater clarity on which leads are more likely to “close-won” and which are worth the extra time and resources to nourish. Marketing is now able to contribute a higher volume to the sales pipeline than before.

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