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What is call routing?
In the customer engagement and experience domain, call routing refers to the distribution of inbound and outbound communication amongst the call center agents. Call routing is the dominant way of handling all incoming traffic in traditional call centers.
An ACD (automatic call distributor) is used for routing the traffic to the agents based on rules. However, these rules are not constant for all businesses and often are applied on a case-to-case basis.
For example, the ACD can be customized in its simplest form of FCFS (first come, first serve), in which the call with the highest wait time is prioritized and routed to the next available agent. In a slightly more complex scenario, the rules can dictate ACD transfer all post working hours calls to an offshore call center.
Call centers often use an IVR (Interactive Voice Response) system to filter the incoming traffic by asking the customer to provide information. The ACD directs the customer to the most relevant available agent based on the information shared by the customer.
However, with the introduction of new technologies such as cloud contact center, data analytics, AI/ML, and NLP-enabled chatbots, there is a need to relook at the strategy for effective traffic monitoring and intelligent call routing methods.
Call Routing Methods:
The call centers employ multiple methods of routing based on the nature of the business. A few common yet effective call routing methods are listed below:
IVR
Routing by IVR is the most common form of routing. As explained above, IVR can filter the incoming traffic based on location, language, or query type and assign the call to the most relevant agent. There is no requirement for data storage, and hence IVR is simple and effective.
Direct
Direct routing is a method in which the Brand has a direct relationship with the end consumer. For example, in the hospitality industry, the customers are often given different phone numbers for making reservations for accommodation and events.
While it is an effective way of reducing the steps in which a customer reaches the agent for query resolution, it may lead to confusion if the customer query concerns two different departments.
Skill-based
With modern call center software, you can match an incoming customer query to the most qualified and relevant agent. This method impacts important KPIs such as FCR (first call resolution) and average call wait times.
This setup needs data storage, integration, and analytics that identify the caller and a few more data points before transferring to an agent for resolution.
For example: if the system identifies a caller as a long-term customer whose account is about to expire. Also, the past few CSAT/NPS scores were below a threshold, and the intelligent skill-based routing can transfer this call to an agent who has a good record in nurturing and retaining customers. This way, the organization can improve metrics such as FCR and reduce churn due to agent mismatch.
Caller ID
This method entails attaching a caller ID with a customers’ contact number. It helps in identifying new and old customers in an instance. New customers match with agents trained in lead generation, while old customers match with agents with information integrated from CRM. This information could include last transaction details, customized offers, returns, and more.
Intelligent Call Routing with Data
All intelligent call routing methods use data to overcome the challenges faced by customers while communicating with customer services. The data helps in two ways: finding the actual intent of the caller and matching it with the most relevant available agent. For implementing an intelligent call routing mechanism, you must capture 3 types of data:
1) Caller Data:
Caller Data is the data from the DNIS (dialed number identification service) or ANI (automatic number identification). It allows the call center to identify the caller before routing it to an agent.
2) Caller Input Data:
Caller Input Data is the most important data to capture for intelligent routing. The caller provides inputs through IVR by choosing options through the number pad or voice. The inputs enable the system to understand the caller’s intent and help with effective routing.
3. Customer Profile Data:
Customer Profile Data is the historical data and can include purchase history, account details, last conversation, active service tickets, billing history, agreements, etc. Access to customers’ historical transaction and communication data helps the agent quickly understand the customer’s queries.
Demand segmentation and strategies for Omnichannel routing.
Once you have the data sources integrated and a single platform for interpreting the customer data, one effective way to increase all KPIs is to segment the demand (inbound traffic) based on the complexity of tickets and frequency of customer queries. The customer data should also include inbound traffic details from other channels like SMS, emails, chatbot requests, social media, etc.
Once you have plotted your inbound call traffic, you can use the above chart to segment the traffic and use relevant strategies:
a) For High Frequency and High-Ticket Complexity: The call center must have all the data sources aligned and integrated to provide a holistic view of the customer and its problems. This view can help the agent in resolving such queries.
b) For High Frequency and Low-Ticket Complexity: Such transactions are pretty simple. Digital self-service tools should be employed to resolve such tickets. It reduces the burden on agents and improves the avg call wait time.
c) For Low Frequency and High-Ticket Complexity: Such tickets can be directed to experienced agents or supervisors as these are rate but complex tickets. Again, skill-based routing is an effective way to handle such tickets.
d) For Low Frequency and Low-Ticket Complexity: Such tickets can be outsourced to part-time agents that require minimum training and supervision. In addition, virtual contact center options can be implemented for further cost reduction.
Conclusion
According to a survey from Salesforce – 83% of customers expect to engage with someone immediately when contacting a company. In such cases, call routing methods and strategies can direct your customers to the most relevant and available agents.
As we advance, technology will play a higher role in finding newer ways of call routing. For example, AI and ML algorithms can further help the agents understand customer sentiment before starting the conversation and enhance the customer experience.
Author Bio:
Shambhavi Sinha is an SEO Expert & technical blogger at Ameyo. She has been writing for 4 years. She is into technology and writes tech-based stuff. Her aim is to provide knowledge to users by sharing tips and tricks about new technologies, DIY, and knowledge about Call Center Software
