Cloudera将售后团队统一归口管理
据SiliconANGLE报道，Cloudera已将售后团队统一归口管理，让客户从入门到续约期间都有单一联系人。首席客户官Patricia Bogoevici表示，调整后的任务是让团队与客户的业务目标对齐，并帮助客户更好地使用已经付费购买的技术。Bogoevici还表示，她本人接受的考核指标是客户如何从Cloudera中实现价值。SiliconANGLE披露，theCUBE是Cloudera EVOLVE26的付费媒体合作伙伴，但赞助方不控制相关报道内容。
此次调整让客户在入门到续约期间拥有单一联系人，同时要求售后团队与客户的业务目标对齐，并促进客户更好地使用已付费购买的技术。
Enterprise data platforms must turn AI pilots into measurable business returns while overcoming the data access, sovereignty and cost barriers that stand between experimentation and production.
The conversation is shifting from what AI can do to how companies make it pay off. One data platform provider has responded by folding its post-sales teams under a single leader, giving customers one voice from onboarding through renewal, according to Patricia Bogoevici (pictured), chief customer officer of Cloudera Inc. The mandate now is to align those teams with customers’ business objectives and help them make better use of the technology they have already paid for.
“When I look at things in terms of customers, for me, technology makes sense only when customers are using it,” Bogoevici said. “I am measured on how customers realize value with Cloudera.”
Bogoevici spoke with theCUBE’s Rebecca Knight at Cloudera EVOLVE26, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed moving AI into production, improving customer adoption and measuring business value. (* Disclosure below.)
Why enterprise data platforms shape AI’s path to production
The barriers customers face fall into three categories, starting with data access, according to Bogoevici. A study of more than 1,300 information technology specialists found that roughly 80% named data access as the biggest obstacle. Governance and sovereignty come next, because data sits scattered across silos with differing rules on where it can live.