4 minute read
KEEPING IT C ONTAINED: Building AI Chatbots to Deliver Exceptional CX
/ By Doug McNeilage /
Artificial intelligence (AI) is changing the customer engagement landscape. As consumer expectations grow and budgets shrink, companies can’t hire their way to great CX. So, AI presents significant opportunities for companies to excel at customer engagement while delivering ROI.
Organizations are using AI in the contact centre in several impactful ways – from generating after call work to knowledge suggestion – and one area with proven business value is chatbots (as long as they’re well-designed).
Done right, this technology can quickly answer customer queries, automate tasks and, ultimately, ease the burden on customer service agents through increasing containment.
What Value do Chatbots Bring to Customer Engagement?
A well-built chatbot, or Intelligent Virtual Assistant (IVA), anticipates customers’ needs and provides actionable assistance, meaning that people can resolve their issues within a digital or voice conversation without any escalation to a human agent.
Intelligence accessed through API connections also enables chatbots to offer personalized customer experiences and answer questions differently for each customer (‘When is my auto loan due?’ or ‘Are calls to Mauritius included in my plan?’) as well as acting as a triage and routing tool for brands.
However, even if you have a sophisticated chatbot, there are still issues that are best handled by a human agent. In these cases, the bot should be able to detect when a conversation needs to be escalated and handover the customer to the best available agent to help resolve their issues with context.
Steps to Take When Building an AI Chatbot for Customer Service
1. Understand the goal: The aim of an AIpowered chatbot should be to effectively resolve customer inquiries, while also reducing agent workload. Analysing the most common customer intents is the best place to start. This will help brands understand where introducing automation will have the biggest impact.
2. Train the bot: Your IVA is only as good as the data it’s trained on. The most useful behavioural data comes from customer and agent interactions collected from across every engagement channel, as well as surveys or other feedback mechanisms. By using large language models to process this behavioural data bots can be trained and made more conversational.
3. Analyse and optimize: Build a systematized method of gathering feedback and measuring performance to ensure your bot is continually improving. To constantly optimize the IVA, it’s vital to know how accurately it can recognize a customer’s intent, as well as whether the advice or direction provided is also successful.
Open and Rich Data Is Vital for Effective Containment
The key component that's knitting these functions and experiences together is engagement data. Containing a conversation within a bot interaction is the end point in a successful AI strategy. Getting to this point requires bots to understand customer behaviour and trends, which is only possible when interactions across every engagement channel are recorded, analysed and acted upon.
This builds a deep understanding of customer needs and expectations, meaning a more personalized and efficient service is delivered by a company’s IVA. It’s also key for companies to operate on an open platform which ensures all applications that work alongside containment bots and contribute to exceptional CX are powered by rich data and continually improving customers’ experiences.
How to Choose an IVA Partner
Because there are several hundred bot providers in the marketplace, you need to be wise when choosing a partner to work with. Many, maybe even most, chatbot providers are technology firms with experience in areas such as linguistics and machine learning.
Building an IVA is about so much more than just the technology; a partner with the experience in your chosen area can make it more straightforward to hit the ground running with models specific to your business. This helps you find the best use cases, integrate the IVA into common backend systems, give you a strong leg up in industry-specific dictionaries and concepts, and provide you with best practices that are actually relevant to your specific situation.
Douglas McNeilage is the in-country lead and regional director for Verint, South Africa.
