Editor’s Note: Andrew shares insights on chatbot technology for customer service and benefits bots can bring. If you’re looking to improve your customer service with a bot, ScienceSoft offers CRM-based chatbot development as a part of our Dynamics 365 and Salesforce services, as well as custom chatbot development.
Chatbots are popular across multiple domains, including banking, real estate, travel, education, healthcare, retail and more. Nowadays, it’s hard to imagine an online interaction without a chatbot involved in some capacity. To translate this statement into figures, the chatbot market is currently valued at $17.17 billion and is projected to reach $102.29 billion by 2025. ScienceSoft’s experience proves this popularity too, as we’ve done chatbot projects for various purposes, for example, a vacation bot for an intranet. So, let’s focus on what makes a good chatbot, and how you can use one to aid your customer service.
When working with ScienceSoft’s clients seeking to improve their customer service, I often hear the same story about around 80% of support requests being rather trivial. Such queries can be easily resolved by looking through self-support materials, yet people choose to contact a live chat and get help in a dialog form. In such a situation, our clients come face to face with a dilemma: they have to expand their team of support agents, which will increase their support costs. Otherwise, their customers are likely to experience a long waiting time and/or a poor quality of received responses. To solve this dilemma, I always recommend opting for a chatbot. It allows optimizing support expenses while helping retain an excellent level of support due to the following benefits:
With a bot, customers can receive answers to their queries really fast. In my experience, a well-trained bot can maintain an average chat time of 5 seconds dealing with basic requests. And this speed is possible 24/7, so customers can receive quality support at any given time. Mainly due to those factors 30% of US consumers rated chatbot interactions as “very effective” already in 2017.
Implementing a support bot can decrease the ticket volume by 70%, allowing your support agents to focus on more complex cases and resolve them faster. In addition, dealing with complex queries provides your agents with an actual challenge, which help them avoid burnout from repetitive tasks.
There are two aspects that make a customer service chatbot truly effective: solid customer service processes and Natural Language Processing (NLP).
Well-established customer service processes serve as a base for a chatbot and make it easier for a trainer to create a working algorithm for the bot to function. And NLP enables the bot to recognize and communicate in a human language by analyzing the incoming text requests. With enough training and data collected during interactions, such bots may continuously self-improve by recognizing more and more speech patterns.
Here is what Tatiana Lebedzeva, Head of Business Analysis at ScienceSoft, says about NLP technology augmenting chatbots:
Chatbot technology has developed dramatically in recent years, and the capabilities of chatbots have advanced enormously. Now, they can manage impressive loads and have gone far enough in imitating human conversation. Modern chatbots are the programs with powerful AI able to support almost natural dialogs and hold long, meaningful conversations.
Currently, all the major customer service platforms, such as Dynamics 365 Customer Service, offer chatbot solutions or chatbot integration capabilities. When a bot can draw from CRM data, it helps facilitate its training and improve its efficiency. Among popular platform-based chatbot options are:
In case you run a customer service solution devoid of chatbot functionality and migrating to other platform feels like a stretch, custom chatbot development is the way to go. I advise the following cloud services for building your customer service chatbot:
To achieve the best results with a customer service chatbot, I recommend you to go iteratively. Start with the bot resolving simple queries, periodically verify it with sample dialogues to mark areas where additional bot training is required and slowly add more complex tasks to the list. Following this simple formula guarantees that your bot will deliver a steady ROI while improving your services. And to measure chatbot success, you can use KPIs similar to those of your service agents, for example, First Call Resolution. If you are ready to give a try customer service automation with a chatbot, we at ScienceSoft are ready to help.
Looking for a way to improve your customer experience? Our specialists in customer experience management provide a full cycle of consulting and CX optimization.