What call center software provides AI-powered chatbot capabilities for automated customer support?

This the first thing to consider: does the provider actually have the capabilities you need? Most call centre platforms are integrating chatbot technologies because they have to to remain competitive. For some, moving more conversations to automated means results in a decrease in licensing and ultimately threatens their business model. Look for a provider that has proven capabilities to deliver because you don't want to end up 6 months down the road and hit a wall. Lastly, make sure you call centre provider can integrate with any chatbot platform on any channel and vice versa. You might find that the platform you need doesn't come from your call centre provide but is in fact a standalone platform that specialises in conversational AI

From my experience AI chatbots demands are very different from case to case. The main feature in the NLU feature which in my opinion is a must to deliver a quality product which can easily understand customer request, then based on actions needed to be performed other resources can be added e.g: a RAG system. At @Bluetweak we give our best to build a solution that fits your needs.

NLP can be a great boon to call centres for the below cases: - Routing to the right queue by understanding the user's intent through NLP - Trying to answer customers'questions through a voice bot powered by NLP. - Agent side Chatbots powered by NLP helps agents to quickly get answers for customers'questions.

You want to make sure your call centre provider can support customer facing NLU (natural language understanding) and LLMs (large language models). The former so that you can handle the static, process-oriented conversations well, and the latter so that you can create more natural interactions and leverage your own data to produce answers to questions. Be aware of any provider that tells you they have 'or own' LLM. They don't. They're fine tuned an open source model at best. Same goes for NLU. Broader questions should centre around the tools they have for training, testing and managing models.

From my experience predefined action steps are just the first layer of an AI chatbot solution, taking in consideration the various customers requests the chatbot should be able to generate an answer to the questions from an existing knowledge base.

The ability to offer self-service should be a core part of any chatbot platform, whether it comes from your call centre provider or elsewhere. You should be able to define workflows and processes here, as well as integrate with any backend system comfortably. This is table stakes. The biggest barrier you'll have to delivering self-service is your skills in designing effective conversations. You'll need expertise in conversation design and service design to deliver the most effective solution (?? like us). Ask for validation from your call centre provider that they have these skills if you plan on outsourcing the design and build to those guys. Not all do.

More often, Customers need to wait until the operation hours to get their simple questions answered. Empowering Customers to get the answers for their questions 24/7 through chat interface on websites/voice bots can result in great customer satisfaction.

Again, this is table stakes. What use is a chatbot that doesn't connect to anything? You want to make sure that it can integrate on both ends of the solution: On the front-end, you need to be able to deploy on any channel easily, so they'll need CPaaS capabilities. In the middle (at runtime and during conversations), you'll need to integrate with your line of business systems to deliver any kind of value (both pulling data out and pushing data in), and on the backend, you're going to need to get data out for analytics and also potentially for some custom processing where required. Most cater for the first two of these, not as many on the latter, so watch out for that.

Most of the times, customers have to wait when agents try to get the required information for the questions raised. They have to search multiple systems/knowledge bases to get the intended answers. Chatbots that can help agents to get the information automatically based on the user questions can be a great time saving option and also provides the right information. Agent facing Chatbots are a viable solution and if powered with LLM can be able to help them quickly to address customer queries resulting in customer satisfaction.

Empowering agents sounds great on paper, in reality there's more to it because, to do it well, you need to understand a LOT about the business, knowledge and processes. Therefore, it can take a while to get up and running. There are, as with chatbot capabilities, platforms that specialise purely on agent assist that are worth exploring. Ideally, you want your agent assist features to cover more than next-best-actions and knowledge search, you want the ability to create the same transactional agents as you have on the front end. Then, there's all kinds of conversational intelligence that are useful. Lastly, when handing over from a chatbot to an agent, make sure you pass the conversation to the right agent and carry over the context.

I think combining chatbots and agents is the best approach to meet the highest scores in customer satisfaction, chatbots can solve the request from the first level of support while in more complicated cases can support the agent by collecting the necessary information before handling the chat to an agent thus making the process more efficient.