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CallMiner:2025年客户体验全景报告(中译版)(18页).pdf

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1、Table of Contents1.Introduction 2.Key findings3.Section 1:Making the most of every customer voice:solicited and unsolicited data4.Section 2:Harnessing CX data5.Section 3:The accelerating pace of AI maturity6.Section 4:Leveraging AI to deliver CX and employee experience(EX)outcomes7.Conclusion 8.Rese

2、arch methodology 9.Boilerplates1Todays customer experience(CX)landscape is more complex than ever.Customers engage with organizations across a growing range of channels from calls and emails,to live chat and social media and their expectations for speed,personalization,and seamless service are risin

3、g just as fast.But the promise of omnichannel hasnt necessarily lived up to the hype.The expectation was better CX,because organizations could meet customers where they are,on whatever channel they wanted.Instead,organizations potentially offered too many options,and the experience and service deliv

4、ered on each of those channels suffered.Further,organizations are facing an influx of CX data.And while CX data is widely collected,it can often be fragmented or underutilized,representing a major opportunity to drive smarter,more responsive experiences especially on the channels that customers want

5、 to engage on.Thats because collecting CX data is only the first step for organizations.The real challenge and opportunity lies in interpreting and transforming that data into valuable insights.In 2024,we found CX and contact center leaders believed artificial intelligence(AI)held the potential to t

6、ransform CX.Now in its fourth year,our report draws fresh responses from 700 CX and contact center leaders around AIs role in CX,and the impact its having on organizational strategies over time.Achieving true CX transformation demands a purposeful shift from simply collecting to actively gathering,a

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1. **CX数据利用不足**:62%组织未能充分利用CX数据,主要因手动分析(42%)、部门数据孤岛(45%)及缺乏分析能力(37%)。 2. **反馈收集趋势**:72%组织收集主动反馈(如调查),但37%仅依赖此方式;100%认为需通过个性化(61%)、自动化(57%)提升反馈质量。 3. **AI加速落地**:96%视AI为关键策略,80%已部分实施(2024年为62%),第三方方案加速 adoption(85% vs. 内部开发71%)。 4. **AI价值与挑战**:96%认为AI可提升员工潜力及效率,但67%缺乏治理结构应对风险;47%用AI提供实时指导,44%实现无偏见交互评分。 5. **行业差异**:BPO数据成熟度最高(仅47%未充分利用数据),金融与零售业领先AI全落地(41%/38%)。
数据如何变现? AI如何赋能CX? 反馈如何优化?
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