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Increasing marketing efficiency and optimizing lead scoring with Qlik AutoML
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
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.
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.
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
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