Content Marketing Manager Synthetix
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How AI and NLP enhance CX through times of crisis

3rd Sep 2020
Content Marketing Manager Synthetix
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CX needn’t suffer in times of crisis, nor should companies settle to merely survive, they can in fact thrive through hardship by implementing tools and techniques that utilise Artificial Intelligence (AI) and Natural Language Processing (NLP).

AI Chatbots Support Customer Service Teams

It’s no revelation that during times of crisis, uncertainty grows, causing panic and dramatic surges in customer query volume. Whilst some customer queries are pressing and warrant human understanding, a large portion of these queries include routine questions, which don’t require agent assistance to be resolved.

The combination of huge contact volumes paired with contact channels that lack AI-powered intelligence results in phone lines and other agent-assisted channels becoming inundated with contact – an inefficient use of agent time. This only snowballs when the customers who need human assistance to resolve their complex or sensitive issues cannot reach an agent because of congested phone lines and your CSAT begins to suffer.

AI-powered chatbots support customer service by automating routine queries. Utilising NLP, chatbots analyse each component of a customer’s routine query including keywords, search intent, grammar and popularity to deliver the most relevant results. This significantly reduces the customer service backlog, giving agents the capacity to effectively deal with customers who need help.

Chatbot visibility is also key to freeing up bandwidth for customer service teams. AI chatbots can be configured to be the first thing that customers see on a specific page, encouraging engagement over other channels that are operationally more expensive to run.

From an external perspective, customers no longer have to wait in phone lines because they have engaged with a channel that suits their query type. This reflects positively on CSAT scores as their enquiries are dealt with successfully, instantly and with 24/7 capabilities.

Image that shows how AI and NLP assist customer CX

AI Metrics Influence Customer Journeys and CSAT

When customers are depending on you for assistance more than ever, ensure customer journeys are seamless and successful. This includes getting customers from query to intended result smoothly and without roadblocks - this is particularly important to customers who feel they can count on you during times of hardship and is reflected positively in CSAT.

The data derived from conversational AI provides insights to improve customer journeys. Not only does it reveal whether a specific issue was resolved or not, but it identifies invisible pain points. Customer outcomes, treemaps, dwell time, bounce rates and cart abandonment data can suggest a successful or unsuccessful customer journey – its this data that is important.

Based on AI metrics, Knowledge Managers can configure customer service tools to address hidden pain points or roadblocks that have been uncovered to improve the customer journey. Custom triggers can be introduced to determine when a tool should appear, it which form or aesthetic and under which conditions. Further split testing can validate these actions for optimised journeys.

For vulnerable customers you cannot obtain the help they require due to poor customer journeys, that is enough for them to jump ship. During sensitive times, there is little room for error and having the capabilities to support customers is paramount.

NLP Is Learning Your Customers’ Needs for Optimal CX

Effective customer-facing self-service tools should utilise NLP to offer a positive CX and ensure the customer feels understood. This is important under normal conditions but even more so during times of crisis when CX is a deal-breaker for customers.

Tools that utilise NLP are not only able to ‘understand’ naturally phrased questions and therefore deliver relevant results, but by adopting machine learning principles, such tools ‘learn’ from customer interactions for constant CX improvements.

Built on machine learning principles, NLP captures data from each customer interaction to identify patterns and trends in customer habits, behaviours and language preferences. This data is then stored and used in future interactions, creating familiarity and enhanced CX.

Some vendors even utilise additional search layers to ensure the right resolution is always reached on every occasion. The aim is to provide a better quality of answers but most importantly, to ensure that “I’m sorry I don’t understand the question. Please try again” is not served to customers – ever!

Further, if a self-service tool detects that the query is non-routine and requires human understanding to be resolved, it will then be escalated to an agent-assisted channel. This approach assures a dead end never occurs.

Prevent customers from going around in circles trying to use the ‘right’ keywords to trigger their desired results or being served the frustrating “I’m sorry I don’t understand the question” time after time. Ensure customer service tools are in place that utilise NLP and machine learning principles for optimal CX, especially during adversity when it's particularly important.

To Summarise

Choosing customer service tools that are powered by AI and utilise NLP and machine learning principles can help your company not only survive, but thrive through times of crisis.

When customers need you the most, be there for them. Provide your customer service and contact centre teams with the tools they require to deal with large volumes of contact effectively. Select software that is built on AI and NLP to facilitate positive CSAT and ensure that CX is constantly improving.

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