Improve customer service with Chatbots
Digital ခေတ်မှာ Customer တွေဟာ လိုအပ်ချက်နဲ့ကိုက်ညီမယ့် ပစ္စည်းမဝယ်ယူခင် information တွေ အရင်ရှာဖွေတတ်ကြပါတယ်။ ဝယ်ယူပြီးနောက်ပိုင်း Feedback တွေကို ဖုန်းဆက်ပြောလေ့ရှိပေမယ့် ၂၀၁၀ မှာတော့ Social Media သုံးပြီး ဆက်သွယ်လာကြပါတယ်။ Social Media Page တစ်ခုက Feedback တွေ ၊ Inquiry တွေနဲ့ Sale ရဖို့ အထိ အရေးပါတဲ့ Communication Channel ကြီး ဖြစ်ပေမယ့် Message Reply ကြာတဲ့အတွက် Message တိုင်းကို (၂၄) နာရီလုံး ချက်ချင်းပြန်ဖြေပေးနိုင်တဲ့ Chatbot ကို စတင် အသုံးပြုခဲ့ပါတယ်။
ရင်းနှီးမြှုပ်နှံသူ ငါးသန်းနီးပါးနဲ့ ဒီဘီအက်စ် ဘဏ်ဟာ ၂၀၁၆ မှာ Facebook Messenger ကနေ Customer တွေအတွက် ဘဏ်နဲ့ပတ်သက်တဲ့ အမေးများတာတွေကို ဖြေကြားဖို့ Chatbot ကို ထည့်သွင်းခဲ့ပါတယ်။ ၂၀၁၇ မှာ Singapore Airline က ခရစ်(စ်) လို့ခေါ်တဲ့ Chatbot နဲ့ Pre Flight မေးခွန်းတွေကို ဖြေကြားခဲ့သလို Sephora ကလည်း Sephora Product တွေအကြောင်း စာနဲ့တစ်မျိုး ဗီဒီယိုနဲ့တစ်ဖုံ ဖြေကြားဖို့ Chatbot အကူအညီရယူခဲ့ပါတယ်။ Singapore မှာ ပထမဆုံး အဆင့်မြင့် တက္ကသိုလ် ဖြစ်တဲ့ Singapore Management University ဟာလည်း ကျောင်းသားရေးရာကိစ္စတွေအတွက် Chatbot ကို အသုံးပြုစေခဲ့ပါတယ်။
ဒီလိုမျိုး Chatbot က Customer လိုအပ်ချက်တွေကို အချိန်တိုအတွင်း ဖြေရှင်းပေးနိုင်တဲ့အပြင် ဖုန်းခေါ်တာတွေကိုလည်း လျော့သွားစေပေမယ့် ပုံသေ မေးခွန်းကိုပဲ ပြန်ဖြေနိုင်လို့ လူထက်တော့ သာလွန်ကောင်းမွန်တယ်လို့ မဆိုနိုင်ပါဘူး။ ဒါကြောင့် အချိန်အခါ အလိုက် အသုံးချတတ်ဖို့တော့ လိုပါတယ်။ #digitalmarketing
In today’s digital world, information are or should be easily accessible. Customers are looking out for information needed for purchase decision and are also willing to be more engaged than ever with the brands depending on their needs. However in Myanmar, many brands heavily rely on human representatives and hardly few companies are deploying monitoring mechanism for all these conversations to ensure consistency and correct advice. In the past, people could pick up the phone to provide feedback about brands but in Myanmar, we don’t know how many customer calls were ignored in the age of phone conversations.
In 2010, the social media made easy in relaying customer messages to brand replacing the previous conversations. Brand’s social media page became the main communication channel with brands for feedbacks, inquiries or even sales. For many brands, that is very important as there are a vast amount of information and sales to explore and increase. Although, it is easier to reply to customers through social media, it is normal that you might have to wait for the message reply from a brand in Myanmar for about 10 - 24 hours which piss off the customers usually by the time they get the reply. Plus employing customer care team is costly to the brands.
This problem could be easily solved (at least for the large part) by implementing chatbot. Unlike employees, chatbot provide instant replies 24/7 in time of needs, such as promotional period with high volume of inquiries. Many inquiries are simple and repetitive inquires to solve which is why many asian brands are opting chatbot nowadays as the first line of customer service to address simple queries.
DBS, a retail bank with over nearly 5 million clients in 2016 released a chatbot via Facebook Messenger that allows customers to ask about a range of subjects from branch locations and their account balance to making card payments. Singapore Airline launched chatbot called “Kris” in 2017 to handle pre-flight related inquiries for their facebook page. On the platform called Kik, Sephora chatbot offers tips and tutorials for many products. It can suggests top-rated products and also answers back users typed queries. To give you an example, you can type “L’Oréal Lipstick”, and the chatbot will instantly share the product reviews and ratings. Sephora’s chatbot can ask you a series of questions to know your preferences. Singapore Management University is the first institution of higher education in Singapore to launch a chatbot in the Student Services Hub, a one-stop center for services like payments, insurance, and locker rentals.
It is no doubt that the chat can reduce the wait-time to customer queries by the brands and reducing customer calls. However, chatbot at this point could not replace a human being, for some questions as even with machine learning, the chatbot can only learn as much as the data available. Therefore, business should know when to refer questions to a human.