Updated: Nov 7
If you've ever tried to contact customer service, you're likely familiar with the frustration of navigating through lengthy IVR recordings, enduring minutes of waiting with background music, and being directed to various agents or lines. Most customers are only willing to wait for a maximum of two minutes to connect with an agent. When this time limit is exceeded, customer satisfaction takes a nosedive. It's time to reconsider the traditional IVR systems, which often result in customers having to repeat themselves to the call handler.
In the realm of customer contact, the 80/20 rule is king. Approximately 80% of customer contacts are made through phone calls. Contact centres grapple with challenges such as high call wait times, long hold times due to undertrained staff or staff shortages, and extended wrap times during which agents resolve issues after the caller has hung up, making them unavailable to answer new calls.
To tackle these challenges and usher in a paradigm shift towards more cost-effective solutions, automation is the key. Artificial intelligence (AI) plays a pivotal role in this transformation. By interfacing with contact centre solutions, AI takes charge of initial inbound calls and triages them effectively, enabling us to reduce reliance on expensive contact centres, which require personnel to answer calls, often suffering from high churn rates and costly training overheads. The focus of this paradigm shift is on managing customer perceptions and reducing contact centre overhead by avoiding long wait times, minimising on-hold durations, and freeing up agent time from wrap-up activities for more productive tasks.
AI can help automate inbound call routing and issue resolution before contact centre involvement. By analysing customer queries for intent, tone, and sentiment, AI can route customers to chatbots for routine inquiries or directly to the most suitable agent for quicker resolutions, significantly reducing wait times.
A well-implemented AI-powered routing system can:
Automatically classify customer messages based on their intent, sentiment, and complexity.
Offer self-service solutions from a knowledge database.
Route customers with routine queries to chatbots for resolution.
Collect relevant data for agents to expedite issue resolution.
Now, let's delve into three scenarios illustrating how AI technology can benefit contact centre routing.
**Scenario 1: Self-service Solutions**
Imagine a customer with an enquiry that can be easily resolved by accessing related articles and FAQs. AI can direct customers to a knowledge database, where they can type in free-format questions and get relevant information. By incorporating a chatbot that offers personalised solutions based on customer search patterns, these queries can be resolved before even reaching any contact centre agents. This not only relieves the burden on contact centre agents but also provides customers with a self-serve option, ultimately reducing the volume of phone calls.
**Scenario 2: Enhanced Customer Engagement**
In the scenario where a customer has a Level 1 enquiry and requires assistance from contact centre agents, the traditional approach often involves placing customers on hold with background music, leaving them in a state of waiting. However, here's an opportunity for a more customer-centric approach: leveraging AI chatbots to engage with customers during this waiting period.
Instead of subjecting customers to music in the background, why not use this time to employ AI chatbots that can interact with your customers and better understand their queries? These chatbots can engage customers in a conversation, collect relevant data about their issues, provide preliminary assistance where possible, and collect valuable feedback on their experience.
This not only keeps your customers engaged but also makes them feel heard and valued during their time in the queue, significantly reducing the likelihood of call abandonment. Furthermore, it equips contact centre agents with crucial information, enabling them to provide faster and more informed assistance when they do engage with the customer. Over time, the feedback collected by AI chatbots can enhance overall efficiency.
**Scenario 3: Urgent Assistance**
In urgent situations, where real-time agent assistance is essential, AI chatbots can be programmed to escalate conversations when certain trigger words or phrases are detected. For example, in housing associations, when issues such as anti-social behaviour, mould, or violence are involved, the chatbot can escalate the case to live agents, placing them on top priority.
Outcomes for using AI to route your contact centre demand:
Slash your contact centre operational costs significantly.
Provide immediate response and resolution from chatbots for routine queries.
Help agents focus on helping other customers, reducing their workload.
Achieve shorter queues.
In conclusion, implementing AI-driven automated omnichannel routing not only enhances customer satisfaction but also significantly reduces operational costs for contact centres. This results in shorter queues, improved efficiency, and a more seamless customer service experience. Embracing AI and omnichannel routing is a win-win for both businesses and their customers.
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