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Build Your own Chatbot to Transform Telecom Customer Service

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Build Your own Chatbot to Transform Telecom Customer Service



Customers rate telecom customer service poorly on feedback forms and Net Promoter Scores (NPS). This is no surprise for those who know how extremely complex the interplay of mobile devices and global wireless networks are. Customer support call centers are unfortunately where technological complexity thrives. Service agents have the impossible task of fixing all service or device problems thrown their way, all done remotely via a mere phone call!


Chatbots are becoming the preferred platform to deal with customer care interaction in many industries. It’s no surprise why – via a simple user interface, they can easily deliver answers and solutions. In this article, Olivier Engel, the EVP of Product Development at Sicap, investigates how mobile service providers can build a Customer Care Chatbot. Dan Code-McNeil, the Head of Sales at Ada, a global AI customer service leader provided insights for the story.


According to the analyst firm Gartner, chatbots will be integrated across 25 per cent of all customer service and support operations by 2020. This evolution is facilitated by the rapid improvement in bot platforms, natural-language processing and machine learning.


Telecom Customer Care Hits the Chatbot Sweetspot!


Thanks to the many chatbot platforms available, any company can now build a chatbot in no time! However, automating a customer service bot that scales to meet the needs of millions of customers can be challenging, without an experienced partner and AI powering your bot.


Smartphone owners encounter dozens of different kinds of problems, and the solution to their particular problem can differ, depending on the device and operating system involved. Today, call centers need support content for hundreds of solutions, depending on the particular problem in question.


Chatbots thrive in these environments, due to their ability to provide support to identify the customer’s specific problem and provide a personalized solution directed at that problem.


When a mobile service provider decides to begin a bot-building journey, the first step is to define the purpose, objectives and use-cases for the bot. In the customer care context, they may be used to accomplish customer requests – such as helping subscribers to configure Access Point Name (APN), Wi-Fi hotspot or an email account, instructing them on how to top up their prepaid balance and so on.


As the telecoms requirements can be complex, thorough research is recommended to find out what kind of problems your customers could encounter, which problems take time to solve, which device models cause the most inquiries and which are the frequently asked questions.


How Brainy does a Bot Need to Be?


The chatbot experience is only as good as the machine learning that powers it. It’s important to find an AI-powered platform that provides not just instant, but also intelligent support.


When a user asks a bot for help in repairing the Internet connection, the chatbot must understand what the user wants and provide the right response. Natural Language Processing (NLP) makes this possible.


Ada, a global leader in AI-powered customer service allows non-technical teams across telecommunication companies, build and deploy a scalable, intelligent customer service bot in less than a month, and this is available in more than 100 languages.


Dan Code-McNeil, Head of Sales at Ada, says that the company has enabled businesses to automate up to 70% of their customer service, with more than 80% recognition by using its AI powered platform, Ada.support.


The company’s proprietary machine learning and natural language processing model learns from hundreds of thousands of conversations taking place every day across their clients’ bots. This allows Ada to consistently improve the accuracy and capabilities of its AI, and to ultimately strengthen the customer experience.


Chatbots can also be built without Artificial Intelligence. The hard-coded rule-based approach is technically easier, but lacks the scalability, flexibility and intelligence of the AI-based solutions. The caveats can be substituted by suggestive questions, combined with quick-reply buttons and other components, aiding the conversation with a less intuitive bot. 


A Bot Framework or a Bot Platform?


Operators and MVNOs can build customer service bots in two ways.


Using a Bot Framework, such as Wit.ai or Chatscript requires software development resources, but they make the development faster and remove much of the manual work involved in building bots.   


Bot platforms, such as Ada.Support are complete online ecosystems, on top of which chatbots can be deployed and operated without software development skills. Many include a pre-integrated partner network. Ada partners with Zendesk, Genesys, and Live Person for a quick bot-to-agent handoff.  


Leverage Chatbot Communication Channels


Chatbots can leverage popular chat mediums such as Facebook Messenger, Twitter, Kik and Telegram in addition to website chat windows for customer communication.


The most frequently encountered problem at telecom call centers is a non-functional Internet connection, which makes SMS text messaging an important communication channel for chatbots.


How can you Integrate a Telecom Bot?


A bot is a seamlessly embedded component on a mobile operator’s end-to-end customer care flow. This requires integrations into several external systems.


Integrations to CRM and ticketing tools can enable a swift chatbot to live agent handoff. An Automatic Device Detection system (ADD) and Device Intelligence Data repository can provide vital handset related information to bots. Online Smartphone Support platforms provide ready-made help content tailored for different device models and operating systems. An SMS Center opens a back-up communication channel, which will work even without an internet connection. An Equipment Identity Register (EIR) provides bots with information about stolen devices. VoLTE Device Entitlement Server gives operators the ability to deliver users Voice-over LTE and Rich Communication Service (RCS) configurations through the bot.


In Conclusion


Chatbots have proven their benefits in the first line in telecom customer service; they save customers’ time, decrease support costs, and enable agents to deliver more meaningful human-to-human experiences. But, that’s not all. Ada and Sicap have already witnessed telecom operators creating new roles and teams dedicated to driving automation across the customer journey.


This could be the beginning for a user-friendly transformation towards a fully automated telecom customer service!


Sicap’s Smartphone Support Chatbot guide is available and free for all operators and MVNOs to learn more about the planning and building process. Click here to go to the webpage.


About the Author


Olivier Engel, EVP Product Development at Sicap has 14 years of engineering experience, with more than 10 years within the telecoms industry. Before joining Sicap, Olivier worked at Unilog IT Services and Logica. Olivier’s responsibility at Sicap is to ensure high-quality software development and delivery to all customers globally. Olivier holds a degree in Information Technology Engineering from Ecole Centrale de Lyon in France.


About Sicap


Sicap is a global telecommunication solution provider enabling Mobile Network Operators and Mobile Virtual Network Operators (MVNO) to deliver an all-encompassing customer experience. Its solution portfolio, which include Device and SIM Management, Customer Insight and Engagement, Device Knowledge and Mobile Security make the mobile world more profitable, manageable and secure. Sicap works with more than 80 mobile service providers in 76 countries. Its international team in nine locations ensures excellent customer service worldwide. All the solutions are available from the Cloud with a pay-as-you-grow pricing model to give its customers a quick deployment time, minimized upfront investment and low operational costs. For more: http://www.sicap.com

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