According to market research, the conversational AI market is expected to reach $18.4 billion in 2026 at a compounded annual growth rate of 21.8 percent. Because of the pandemic year, maintaining business continuity with clients is critical, and conversational AI may be a helpful tool in an organization's customer service armory. Aside from cost savings, conversational AI elevates the customer experience to a whole new level.
In this blog, we are going to cover what Conversational AI is and how it can be used to guard customer experience during network outages.
What is Conversational AI
Conversational AI is a subset of artificial intelligence that use neural networks and machine learning to aid in the development of valued apps capable of interacting with clients via natural language. The technology focuses on holding a conversation while taking into account the variations in natural language inputs, allowing it to achieve genuine human interactions. At the consumer level, examples of conversational AI include smart speakers that accept natural language instructions and provide the desired response.
Cascading Impact of Network Outages
Many service providers in the connectedness industry deal with a significant number of calls related to network outages in this age of speed and consistency. Customers are dissatisfied because they are unable to predict these outages and notify them in advance.
If proactive outage notifications are not received quickly, they have a cascading effect:
- A significant increase in contact center calls lengthens client wait times.
- NPS scores are lowered when customers are dissatisfied.
- Contact center operating expenses are increasing.
- Customers are more likely to switch if their reputation suffers.
To address these hurdles and boost NPS, service providers must auto-identify outages and proactively schedule alerts. They require a sophisticated central platform capable of orchestrating seamless interactions between the contact center and customers. This is accomplished through the use of a "Two-way Conversational AI Framework", discussed later in this blog.
Why Conversational AI
Organizations that include conversational AI in their customer experience mix may offer what their consumers want rapidly while maintaining company continuity. Down below are a few reasons why conversational AI is needed.
- There is no learning curve because the contact is based on natural language, which eliminates the need for training.
- Conversational AI operates around the clock, unlike call centers, which have set hours of operation.
- A lot of low-hanging tasks and mundane day-to-day queries are prime candidates for automation saving costs and improving the overall customer experience.
- Conversational AI can be made available on multiple channels, such as mobile phone, web, IVR, smart speakers, or even smartwatches, making it device/technology-agnostic.
- In the backend, an organization's data may be dispersed across many lines of business. If a conversational AI layer is built on top of it that accepts natural language input, the consumer gets a unified front-end experience.
- Enterprises may modify backend systems and provide a layer of abstraction to guarantee that any intentions to transfer to another technology do not negatively impact end users.
- Conversational AI also eliminates the strict synchronous communication structure.
Conversational AI Framework for network outages
The Two-way Conversational Framework involves the following steps to generate seamless discussions between the contact center and customers:
- The first step is to create a single outage monitoring dashboard to record and categorize important events. This is achieved by constructing an Outage Monitoring Dashboard. This solution collects outage information from multiple monitoring systems, capturing node/device specifics. RPA BOT retrieves information about the afflicted nodes from the Outage Monitoring Dashboard and inserts the extracted facts into the outage database, where they may be checked, scheduled, monitored, and alerted to consumers.
- Second steps include scheduling notification. Validate outages automatically with the following entities:
- Outage Database: Use the RPA BOT to monitor the outage database and record the Impacted Node ID/Device name. Using RPA BOT, validate the retrieved information based on preset criteria. Use the extraction BOT to update the database and send a notification to the Notification BOT. To proceed, use the Notification BOT to retrieve the necessary information from the outage database.
- CRM Information System: Use RPA BOT to get client contact information from the CRM database depending on additional information collected from the Monitoring tool, such as Customer Name and Customer Contact Number.
- Technicians on the Field: Validate the outages by sending alerts to the appropriate stakeholders and obtaining confirmation, such as confirming an outage with a technician from a certain location. Following validation, utilize the RPA scheduler to arrange and assign RPA BOTs to inform impacted consumers depending on technology (copper, fiber, cable), impact frequency, and geographic area.
- The third and the final step is to use a conversational AI BOT to notify and engage consumers. After the outage has been recognised, integrate RPA BOT with the conversational AI engine to provide alerts to consumers. It keeps end users up to date on the progress of the service disruption and resolution. If the consumer has more questions, the bot may hold two-way dialogues utilizing conversational AI.
Benefits of Conversational AI during Network Outages
The effective application of the intelligent network outage prediction and two-way conversational AI framework can bring the following benefits to service providers in the different industry:
- Outage-related calls will be reduced by 54%.
- The cost of operations can be reduced by 25%.
- Increase agent output.
- NPS improvement
Conversational AI is bringing new opportunities to sectors such as customer experience, user engagement, and information access. Conversational AI is about more than simply obtaining technology; it is about having the proper collection of talent, designers, and technically skilled individuals to create the ideal experience. Adhering to recommended practices while deploying conversational AI can result in excellent results.