Every customer is different and so is their journey. That's why having the same interaction for all the customer's won't help businesses. Every interaction should be different and that's where context and data come into the mix. Context and data play a very crucial role in customer engagement.
The developments in technology have allowed brands to learn more about their customers through data collection. Chatbots can collect data from their customers while interacting across various touchpoints. The only problem was making use of that data in real-time.
But contextual routing has changed everything. Contextual Routing has finally allowed brands to utilize their customer data to the fullest. They can now use data to automate and personalize the customer’s experience. This wasn't possible previously.
Brands can now use data of their customers on their own and route the incoming queries. Queries would be assigned to a specific agent based on their data. This helps in increasing the efficiency and accuracy of the company. Customers are assigned to agents that best suit their needs and who can assist them in providing a good overall experience.
A good example would be - If a query is coming from a Spanish client who can only interact in Spanish, he would be routed to an agent who can assist him in Spanish. This reduces customer frustration and in turn the percentage of unhappy customers.
What’s even better is that it enables customer service teams to set up how they want to route their customers. They don't need to rely on coding and heavy integrations, nor do they need developers to help them with the same. Most platforms have a drag and drop feature that has made it very easy to use.
APIs like Engati make it easy to collect and leverage your customer's information and deliver them a great experience. Machine learning can help API to analyze text and determine the intent using natural language understanding. It also turns free-form data into a structured format. NLP is often used to build accurate contextual models to get their customers to the right agents. With text and speech recognition NLP provides businesses with tools to provide a good customer experience.
Sentiment analysis is the process used to determine the sentiment of the language. It is used to determine whether it's a positive, negative, or neutral sentiment. These sentiment algorithms provide insights into the customer’s opinion on a specific topic. Automated sentiment analysis is a really powerful tool when it comes to gauging customers' opinions at scale. Brands no longer need to rely on humans to read and evaluate texts, these algorithms can do that by themselves. They can process and rate sentiments effectively and are smart enough to understand and can also speak in multiple languages make it a perfect choice.
Companies are leveraging NLP and Sentiment analysis to create Conversational assistants, aka chatbots. These chatbots can automatically help customers in real-time using past data. Businesses can use chatbot platforms to build a chatbot and then train them to help customers without human oversight. AI is used to learn the context and actual intent of a customer's text or voice message. Digital assistants can take immediate action just like a human could. These actions also generate tickets either by:
Engati is a conversational AI interface designed to bridge the gap between human agents and conversational bots.
Businesses can use AI to build an effective and efficient customer journey experience. They can enable customers to solve their issues faster. Capabilities like contextual routing and keyword mapping can help in creating better customer experiences. Contextual routing helps in resolving issues either directly by the bot themselves or by making the right questions reach the right agents. This saves a lot of time for your agents and customers and also ensures a good overall experience for your customers.
Companies can set contextual routing based on the attributes of their users. They can define rules and assign a particular set of customers or queries to a specific set of agents. Rule sets are created to assign queries to their respective agents who can solve them the best.
Now let's dive into the process of contextual routing for Live chat on Engati’s platform:
To add a rule set you just need to go to:
Configurations → Routing → Click on the Add ruleset button → Enter the name of the ruleset.
The attributes include:
Rules can be formed based on multiple conditions and expressions using AND/OR operators. The maximum number of conditions to be added per rule set is 8. These conditions can be added, edited, or deleted from the ruleset.
Companies can even check the box on assigning the conversation to the agent who previously managed the conversation for that particular user. If an agent is unavailable, the routing would be done according to the availability of the agent in that category.
Currently, companies can set up to 3 rule sets per product. Which can always be edited or deleted.
Engati is a one-stop platform for delighted customers. With our intelligent bots, we help you create the smoothest of Customer Experiences. And now, we're even helping you answer your customers' most complicated questions in real-time with Engati Live Chat. So, let's get started?Get Started Free