AI is becoming the basis for customer experience in 2024

What are the core problems in traditional CX methods?

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Furthermore, the problems that CX, support, and customer success teams face can directly be tied to what AI can solve for them -

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Managing bulk repetitive queries

One of the most significant challenges in customer support is managing bulk repetitive queries. Approximately 60% of customer queries are repetitive, often falling into the category of "How to" questions. These types of inquiries do not require complex problem-solving or intervention from a live agent, yet they consume a substantial amount of time and resources. The impact on the customer experience is considerable; customers are often left waiting for answers to simple questions, which can lead to frustration and dissatisfaction.

When support teams are inundated with these repetitive queries, their ability to address more complex and unique customer concerns is hindered. This situation creates a bottleneck in the support process, resulting in delayed responses and reduced overall efficiency. As customers encounter delays, their perception of the company's customer experience diminishes. The repetitive nature of these queries also leads to monotony and burnout among support agents, further impacting the quality of service provided.

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Inability of customers to solve problems themselves

A major cause of repeat queries is the customers' inability to solve problems on their own. This is not due to a lack of willingness; many customers prefer to resolve issues themselves if they have the right tools and information. However, the difficulty lies in navigating a knowledge base that is often unfamiliar and not user-friendly. This challenge significantly impacts the customer experience.

Customers typically find it frustrating to sift through extensive documentation, especially when the information is scattered or poorly organized. This frustration is exacerbated when customers cannot find clear, straightforward answers to their questions. As a result, they end up reaching out to support teams for help, leading to an increase in repeat queries. This cycle not only strains customer support resources but also leaves customers feeling powerless and dissatisfied with their experience.

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Information access challenges for customer-facing teams

The inability to find information is also a problem that plagues customer-facing teams. Company information is scattered across knowledge bases, docs, sheets, reports, etc., causing them to lose hair having to search for information when a query comes in. Not to mention the time it takes after that to curate a personalized response. This disorganization leads to inefficiencies and delays in providing accurate and timely responses to customer queries. The impact on customer experience is significant, as delays and inaccuracies can frustrate customers and erode their trust in the company.

Support teams often spend an excessive amount of time searching for the right information to address customer queries. This not only slows down response times but also affects the quality of the answers provided. When information is difficult to access, it can lead to inconsistent responses, further diminishing the customer experience. The frustration felt by support teams as they navigate disorganized information systems can also contribute to lower job satisfaction and higher turnover rates.

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Complexity of products

Most products are complex, and not everyone on the support team may understand them well enough to answer every query immediately. Considering 100s of help articles, product videos, and 1000s of resolved tickets and customer conversations - it’s almost impossible to have all this knowledge as an employee. This makes onboarding laden with friction, slowing down how the teams function along with their ability to answer queries, and even puts too much pressure on new members to understand the product faster.

The onboarding process for new team members becomes a significant pain point, as they are expected to quickly become familiar with a large volume of information. This expectation can lead to high levels of stress and anxiety, negatively impacting their performance and morale. Furthermore, the inability to quickly and accurately answer customer queries can result in longer wait times and decreased customer satisfaction. The overall customer experience suffers when support teams are not adequately equipped to handle the complexity of the products they are supporting.

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Unnecessary friction between teams

The inability to resolve queries efficiently often leads to tickets being escalated between teams .This becomes a vicious battle of “that team knows it” where everyone just ends up reassigning tickets for days and ruining any chance at getting good feedback from the customer. This inefficiency not only hampers internal collaboration but also deteriorates the customer experience.

When tickets are repeatedly escalated, customers are left waiting for extended periods, leading to frustration and dissatisfaction. The lack of clear ownership and accountability within support teams contributes to this problem, as no one takes responsibility for resolving the issue promptly. This friction between teams can also result in miscommunication and errors, further exacerbating the delays and negatively impacting the customer experience. Customers perceive this internal inefficiency as a reflection of the company's overall service quality, diminishing their trust and loyalty.

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Longer customer wait times

In the midst of these internal challenges, the customer often has to wait for replies that can take hours, if not days, to resolve. Longer resolution times are a leading cause of poor customer experience, ultimately leading to customer churn. Customers today expect quick and efficient service, and prolonged wait times can severely damage their perception of a company's support quality.

When customers experience long wait times, their frustration and dissatisfaction grow, leading to negative reviews and a decline in customer loyalty. The competitive nature of the market means that customers have plenty of alternatives to choose from, and they are likely to switch to a competitor if their needs are not met promptly. The impact of long wait times on customer experience cannot be overstated, as it directly influences customer retention and the company's reputation.

How does AI in customer experience solve this?

Automate 80% of your customer queries with AI

Almost every industry faces repeat queries that comprise more than 50% of their customer concerns. A lot of your support agent’s time is spent on addressing these repeat queries which isn’t productive at all. If anything, it’s the opposite of what your team should be doing so they can - save the time spent on basically closing the same ticket over and over again, spend that time on working on things that are actually important for the business, and give better customer experience with instant resolutions that can be seamlessly done with an AI chatbot.

Leverage AI tools for customer experience and customer support to train them on your entire product knowledge base, help centers, documentation, FAQs, customer conversations, and more. With this, AI has complete understanding and comprehensive of your product and customer knowledge, enabling it to answer queries more promptly with personalized touches, keeping in mind company brand and voice.

Now, set this up as a chatbot on your website and within the product where it’s convenient for your customers. Here, they can directly ask everyday queries to the bot, without needing any agent assistance whatsoever.

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Self-serve for your customers

This point is an extension of the first point -  when you enable self-serve for your customers with something like an AI customer support chatbot, it enables customers to resolve their concerns on their own. In today’s world, this is what customers want. Everything is so instant these days plus people don’t like the idea of relying on someone else for a solution if they can do it themselves/is a bigger problem that needs technical assistance. Therefore, being able to troubleshoot and resolve queries themselves is not only preferable for customers but also more rewarding. Best part is, you get a better customer experience without even engaging with the customer. AI agents serve as a part of your customer support team.

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The dilemma of where to find what

As we mentioned, one of the biggest problems with customer-facing teams is that product and company information is scattered across knowledge bases, docs, sheets, reports, etc. Most companies use ticketing tools for structuring customer tickets like Zendesk, Freshdesk, etc., CRM tools for customer contacts and deals like HubSpot, Salesforce, etc., communication tools for internal use and customer connect like Slack, Discord, etc., and documentation tools like Confluence, Notion, etc.

Across these many tools and throughout these many data sources, it becomes difficult to find information and almost impossible to find information on time. Support agents fail to resolve customer queries within a respectable time, CSMs find it difficult to get company or customer information on time when on call, and CX teams might ruin customer experience and expectations from the beginning with below-average onboarding.

All this can be connected with an AI customer experience tool. Connect all your data sources into one tool and set it up across convenient channels where your teams can access information easily and not have to navigate between tools and tabs. Ask the AI agent where it’s convenient for you and get the answer right there. You can also customize the AI agent to fit the brand voice and tone to personalize the responses and send them across with minimum changes.

Support teams can resolve queries faster, customer success teams can get company information instantly, and CX teams can improve the entire customer experience by ensuring everything from a great onboarding to important touchpoints and quick turnaround throughout the relationship.

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Better team efficiency with better onboarding

The bigger a company, the larger its information database. It becomes impossible for one person to know all this information about products, customers, internal comms, etc., from hundreds of articles and internal docs, CRMs, team & customer conversations, support tickets, data sheets, and god knows which other corners data gets stuck in. A constant battle of “where’s this” and “I swear I’ve seen this somewhere” only leads to time lost in inefficient team dynamics and individual dilemmas. By the time you find information, either the customer is agitated or you are.

When a new employee joins, burdening them with the crippling weight of all this company information will only lead to quicker burnouts and even worse CX KPIs. But with an AI tool that understands everything, they don’t have to go through the ordeal of learning or even looking for all this information. Simply ask AI for tutorials and help articles, past customer data, POCs, and company information, and get it where you want it. No need to search, no need to ask anyone, just do it all yourself. Onboarding becoming enormously more convenient and doable.

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Streamline how teams function

Customer-facing teams can often end up not knowing who is responsible for what or who might know where something is. Tickets are escalated from one person to another and working in these silos becomes toxic for teams and draining for customers.

With an AI customer experience tool, teams can ditch the “they might know it” headache and independently get all information without reassigning work to someone else. Ask for the information where you need it, resolve what needs to be resolved, and streamline processes by eliminating friction entirely. This is how teams can win amongst themselves and win more customer loyalty through better service.

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No more bad customer service

All these changes from AI lead to improving customer service altogether. The leading causes of bad customer service are longer wait times, too much back-and-forth, lack of personalized conversations or the feeling of not being important to a company, lack of empathy, and of course, unresolved or partially resolved issues that never truly get solved. Bad customer service is the biggest enemy of churn, in fact, 60% of customers leave because of it.

AI improves support with automation and self-service, better discoverability of information with AI agents where it’s convenient for the team, and streamlines team communication for better efficiency and less friction. When all these things get taken care of, everything becomes less likely to contribute to bad customer service.

Threado AI: Getting started with an AI solution

Automating chat support

Threado AI enables businesses to build AI agents that can understand the intent behind customer queries and break them down into action items - search through hundreds of documentation and give instant answers or perform actions like calling an API to cancel a plan or extend a trial. Threado AI contextualizes customer queries and provides answers that are precise, without fuss or fluff.

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Immediate assistance 24/7

Be it customers or your customer-facing teams, Threado AI offers immediate assistance 24/7 across platforms and channels for convenient access and faster support. Teams can resolve 5X more queries in the same amount of time across - Slack, Microsoft Teams, or on the Web with a Chrome app. Get reliable and instant answers anywhere and anytime you want.

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Unified data platform

Threado AI makes it super easy to connect all of the company sources - knowledge bases, CRMs, ticketing platforms, and more. A single source of truth for your teams and customers, available wherever you need it.

We support integration with Zendesk, Intercom, HubSpot, Freshdesk, Salesforce, Google Drive, Confluence, Notion, and Slack. Threado AI understands not just help docs but also the conversations through tickets, conversations, and internal docs to answer contextual queries such as customer information related to accounts, help support agents resolve complex concerns, and onboard new customers faster without the hassle of tutorials and videos.

Seed for a better tomorrow

personalization, cost efficiencies, and data-driven decision-making. These advantages not only enhance the customer journey but also provide businesses with a competitive edge in an increasingly digital marketplace. Real-world examples, such as Threado AI 3.0, demonstrate the tangible impacts of AI, showcasing success stories across various industries.

However, the journey is not without its challenges. Ethical considerations, the need to balance automation with human touch, and the initial hurdles of implementation require careful navigation. Despite these obstacles, the potential for AI to continue transforming customer experience is immense. Emerging technologies promise even greater levels of personalization and engagement, hinting at a future where AI-driven customer experience is even more intuitive and seamless.