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Tencent Holdings · Beijing

# 企业微信-客户成功-行业解决方案专家（KA）（广州/深圳/上海）

Beijing Sales 

Listed on Tencent Holdings’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2098283644870377472)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 企业微信-客户成功-行业解决方案专家（KA）（广州/深圳/上海）

## Job description

### 对负责行业的行业解决方案负责
- 通过用户调研、数据分析等手段，梳理提炼行业的内部及外部业务链条、组织模式、高频场景等，基于企业微信的原生能力及开放能力，构建行业化解决方案，推进相应解决方案在客户项目中落地；

### 对核心KA客户的全生命周期负责
- 与BD团队协作完成行业覆盖与攻坚，负责客户需求沟通、方案宣讲、技术支持等工作，能快速捕捉重点行业客户业务痛点，推动核心客户的拉起拉活与商业化，整理形成核心客户案例场景进行复制推广；
- 对行业需求进行分析、评估，总结行业客户共性诉求，配合将客户需求整理成内部相关产品需求，推动产品竞争力持续提升。 Requirements
- 具备良好的产品能力基础，有一定的行业解决方案经验与企业IT技术能力，对于微信生态开放平台体系的接口能力及生态玩法有一定了解；
- 具备方案设计、咨询能力，有文档撰写功底，具有优秀的方案宣讲能力；
- 具备用户调研及数据分析能力，对商业信息的敏感，能够在客户推广和落地过程中对信息进行搜集、判断、整合，发掘行业场景机会，提升产品的行业价值；
- 有框架化思维能力，逻辑思考能力强，善于学习，有强自驱力，具备良好的独立工作能力，适应互联网行业勇于创新、快速变化的企业文化，适应频繁的出差；
- 具有3年以上B端项目工作经验者优先考虑；
- 该岗位支持多个城市，广州、深圳、上海、北京均可。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 12, 2026
- Last checked: Oct 19, 2026
- Listed for: 7 days
- Location: Beijing[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2098283644870377472)

## More jobs at Tencent Holdings

### [企业微信-商务拓展经理-互联网行业（广州/深圳/上海）](https://jobs.opennash.com/companies/tencent-holdings/jobs/8c7f829fcdac3d7ee1a4/)

Beijing

### [企业微信-商务拓展经理-工业行业（广州/深圳/上海）](https://jobs.opennash.com/companies/tencent-holdings/jobs/8236af1e295374990fa1/)

Beijing

### [智慧零售大客户销售经理/公有云销售](https://jobs.opennash.com/companies/tencent-holdings/jobs/3673a57e473d1d705f55/)

Beijing

### [腾讯云-北京云原生销售经理-泛互](https://jobs.opennash.com/companies/tencent-holdings/jobs/ad64aa7a7f0b9ef5a9de/)

Beijing

### [腾讯云-北京泛政销售经理](https://jobs.opennash.com/companies/tencent-holdings/jobs/b0fde196a0d54fa9c1a5/)

Beijing

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Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

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