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Success stories powered by Unifonic: BIMA
技术
- 分析与建模 - 自然语言处理 (NLP)
- 应用基础设施与中间件 - API 集成与管理
适用功能
- 销售与市场营销
用例
- 对话机器人
服务
- 系统集成
挑战
BIMA 是阿曼最大的保险聚合门户网站，在竞争激烈的保险经纪市场中，它面临着确保良好客户体验、保护数据和保持合规性的挑战。该公司占该国汽车保险市场的 10%，每天处理约 500 份保单，需要一种更有效的方式与客户沟通。该公司的传统通信系统无法满足其营销和客户支持要求。
关于客户
BIMA 是阿曼最大的保险聚合门户网站，提供一系列产品，包括人寿、家庭和汽车保险。该保险经纪公司占该国汽车保险市场的 10%，每天处理约 500 份保单。保险购买者可以登录 BIMA 的公正门户网站，该网站汇集了 13 家保险公司的报价，并选择最适合他们的方案，从而节省大量金钱和时间。
解决方案
为了加强客户体验战略，BIMA 部署了 Unifonic 的 WhatsApp Business 解决方案，以满足其营销和客户支持需求。该公司还将 Unifonic 的聊天机器人用于客户服务和支持运营。BIMA 使用 Unifonics Chatbot Builder 配置了其机器人来处理交易的前半部分，这通常是为了帮助用户查找信息。BIMA 目前正在准备推出其 B2B 平台，并计划扩大 Unifonic 解决方案以支持其扩张计划。
运营影响
数量效益
相关案例.
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Tronergy's Transition to Alibaba Cloud for Enhanced Scalability and Performance
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SAP's Accelerated Deal Closure through Process Automation
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7-Eleven Philippines Enhances Customer Support with Freshdesk
7-Eleven Philippines, a pioneer of 24-hour convenience stores in the country, was facing challenges with its customer support system. The customer support was outsourced to an external vendor, which resulted in limited visibility into customer query patterns and performance metrics. The company had no transparency into the vendor's analytics and could not validate their reports. They also had no visibility into the volume of calls, number of abandoned calls, etc. due to the use of the vendor’s telephony solution. This lack of control and visibility into customer support led the team to decide to bring the entire function in-house. They began exploring helpdesk solutions that would enable them to build a strong in-house support team.
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MISA's Success in Achieving 50% Query Deflection Rate with Freshdesk
MISA, an online fashion retailer, faced a significant challenge in managing customer support and communication during the COVID-19 pandemic. The shift in consumer behavior towards online shopping led to an explosive growth in digital footfall, increasing MISA’s average number of orders from 30-50 a day to about 70-100 a day. This surge in orders resulted in higher support volumes, with customers frequently enquiring about their orders and delivery status. The team struggled to prioritize issues as their existing email systems ordered conversations based on the latest response rather than the urgency of the queries. Additionally, the shift to remote work due to the pandemic raised concerns about effective team collaboration and communication. MISA also faced the challenge of dealing with repetitive customer queries, which were time-consuming and redundant.
Case Study
Transforming Customer Service in Financial Services with AI Chatbots
The customer, a leading US financial services company and one of the largest credit card providers in the world, was facing challenges with their existing customer service model. They had over 8000 customer service agents handling queries on phone and digital channels, but their first foray into digital customer service in 2006, which involved live chat support on their website, was not as effective as they had hoped. Customers had to wait in a chat queue and could not switch tabs or leave the page without missing their turn and having to start over. The company wanted to improve this experience by adopting a more intuitive and familiar flow, similar to popular messaging applications like iMessage and WhatsApp. They also wanted to maintain the context of past issues the customer has faced to provide a more personalized experience.
