From chatbots and virtual assistants that offer instant, personalized assistance to predictive analytics that anticipate customer needs, AI is redefining the very essence of customer interactions.

Automated systems are so intuitive that they can sort out simple queries without anyone having to wait in a tedious call queue. Human agents can now concentrate on customer issues that could only be solved with their skills, with AI-powered tools allowing them to do so more efficiently than ever.

TechHQ spoke to Colin Crowley, the Senior Director of Customer Engagement at contact center systems specialist Freshworks, about some of the challenges facing businesses and their CX improvement challenges.

“On a general basis, a lot of these AI-powered technologies help to resolve one of the age-old battles in the customer support world between efficiency and quality,” he said.

The typical AI chatbot can help to increase a company’s efficiency but automated, smart systems can’t handle every inquiry. However, forgoing them entirely results in human agents dealing with a high volume of menial issues, leading to unnecessarily long wait times.

“Typically, in the past, efficiency and quality were at loggerheads, where you would have to sacrifice one for the other. And, typically, you were sacrificing the former for the latter because it’s easier to quantify and monetize efficiency.”

In a contact center, efficiency is measured, traditionally, with metrics like the number of contacts an agent makes each hour or the average issue-handling time. However, an assessment of quality would involve evaluating a myriad of factors, including the agent’s communication skills, problem-solving abilities, and customer satisfaction.

Mr Crowley said: “I think what AI has done is really change that up entirely, so we now live in a world where you’re capable of increasing quality and efficiency at the same time; it’s no longer a choice between one or the other.”

Quality can now be metricized through AI-powered sentiment analysis, which gives a reading of how a customer is feeling about a conversation, and scoring based on specific criteria or keywords, allowing agents’ performance to be easily monitored at scale.

The best way to strike a balance is to allow chatbots to solely deal with high-volume, straightforward queries, said Mr Crowley.

He added: “That enables customer support teams increasingly to be, I guess you could say, ‘human’ at scale. It empowers them to be more personalized and empathetic and, at the same time, they can handle more contacts simultaneously.”

Companies can also implement A/B testing to achieve that balance, identifying whether a bot or a human agent would work better for ‘grey area’ customer inquiries. For example, early in the sales process, questions from prospective customers are likely to be simple ones that a chatbot could manage, but also the human touch could help boost brand image and be effective towards conversions.

“AI-powered technology can help you look at the qualitative difference in those conversations […] It makes the chatbots able to handle a lot more in a way that doesn’t make you feel like you’re in an endless loop.”

Similarly, an agent-facing bot could flag issues that a customer may have with the service when they reach out with an unrelated query. The agent can then offer to solve this issue too.

AI tools can further benefit human support agents with real-time sentiment analysis. This is particularly beneficial when they must quickly move between multiple conversations requiring different sensitivity and empathy levels.

Mr Crowley said: “Agent-facing bots can be there to help correct your tonality when you’re communicating back and forth with customers to make sure that, based on the mood and the sentiment of the customer, you’re communicating in such a way that is most acclimated to what the customer needs to hear at that particular time.”

For managers, more advanced, AI-powered data analytics can give them a unified view of agent performance, helping to identify areas of improvement. It is common for customer support organizations to sit on top of swathes of unused data, largely because they do not know how to gather it or turn it into actionable insights.

“That’s a huge area where AI can help because it can analyze all of this […] data coming in from customer contacts on the fly and help to funnel that back into the operations, product, or web team to improve your service or product,” said Mr Crowley.

The technology can also help agents offer benefits to customers while remaining mindful of company finances.

Mr Crowley said: “It’s hard to know what’s the best discount or amount of credits to give someone, and when you’re giving too much or too little.

“Based on certain criteria of the customer, which could be their loyalty tier, prior contact history, or how many orders they’ve had previously, that agent-facing bot could recommend the perfect accommodation that satisfies the customer and, at the same time, is conscientious about the company’s pocketbook.”

While there are many benefits to applying AI solutions, doing so effectively is challenging. Often the data necessary for them to work comes from disparate company systems, and it is time-consuming to collate it, especially in real-time and at scale.

The solutions can also involve a significant upfront financial investment without an easily measurable ROI, which has traditionally held companies back. However, Mr Crowley says that this is likely to decrease in the near future.

“Like with ChatGPT, we are seeing widely accessible technology that’s democratizing access to AI,” he said. “At Freshworks, we’re trying to build AI into the product from the get-go. This means you don’t have to balance three separate vendors for this and that AI technology and deal with the data siloing that takes place and extra price tags.”

Advancements in AI solutions are coming thick and fast, and customers now have hyper-personalized experiences in their dealings with all businesses. Their expectations for support are constantly being raised, therefore.

One way Mr Crowley said meeting increased demands could be achieved is by moving some agents, who have a reduced workload thanks to lower-level issues being taken over by chatbots, into an “innovation team.”“Agents can move into more specialized roles where they help to be pioneers in company technology by just keeping up with that technology curve and helping to pilot programs,” he said.

Other roles could be created for agents which involve performing quality assurance on the chatbots and managing their conversational flow. “That’s a great way to utilize agents who are really skilled,” said Mr Crowley.

“The technology can actually create more career opportunities for agents within a customer support organization.”

The role of the support agent itself will also evolve with the integration of AI. Mr Crowley said: “The average customer support agent is going to be handling specialty tasks more and more because most of the lower-level issues are going to be taken care of.

“That entirely changes the customer support role from being […] this lower-level role, where you’re just a reactive receptacle of people’s complaints, to a role for people who are more skilled, more specialized, and paid better.“You could say that it actually improves the agent experience too, because typically agents don’t like handling very mundane issues because it’s not very satisfying.”

However, it is necessary to pair the launch of AI tools with a clear plan about how the support agent role will change and remain a part of the company structure.

Any investment in customer-facing AI technologies should also be matched by investment into projects which support agents. After all, by having a bot at their fingertips which helps them manage four customer interactions simultaneously, they will reap benefits from their faster response time in the form of higher satisfaction scores.

“That’s a great way to condition customer support agents to see AI technology as something that enhances their experience and empowers them to do better without being burnt out, rather than seeing AI as something that takes their jobs away,” said Mr Crowley.

He added that integrating AI technologies into customer support organizations will influence their strategies more broadly. The success of chatbots could see more of a focus on conversational engagement through channels like Facebook Messenger and Direct Messages on Twitter.

Mr Crowley said: “These are all channels that are relatively real-time but with an asynchronous back and forth and are more immediately attached to everyone’s social life. AI is making conversational engagement disproportionately more efficient and higher quality than other contact channels, and that will push more companies to go towards those channels in higher degrees.”

They will also level the playing field between smaller and larger companies, as readily available AI solutions mean they can compete on efficiency in a way that was not previously possible.

He said: “That’s going to force, I think, a lot of these bigger companies to have better customer service. The smaller companies would traditionally tend to have better customer service because they are spending more on that as a differentiator. So AI will help increase competition on the customer service side with the bigger companies.”

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It is hard to ignore the AI revolution currently impacting all facets of society, not just the tech world. The release of ChatGPT last November opened the eyes of consumers and business leaders in all industries as to how powerful the technology has become in recent years. But, while many are only now using the bot to help them decide what to cook for dinner or structure a difficult email, some companies have been weaving the technology into their products for much longer.

Customers will likely be familiar with their friendly neighborhood chatbot that pops up in the corner of most product websites, asking them if they can provide any assistance today. They may also be familiar with the frustration of receiving a generic – and often unhelpful – computer-generated response to their query rather than being connected to a human agent.

To the more seasoned desktop user, this might call back memories of the infamous digital assistant ‘Clippy’, who first appeared on Microsoft Office applications in 1996. The chatty paperclip was widely criticized for its intrusive and often unnecessary interruptions, which many found annoying and distracting. TIME magazine named it as one of the worst inventions of all time.

But virtual assistants have come a long way since then, largely thanks to the infusion of generative AI, so businesses are more comfortable offering their own to customers. Leaders in CX can humanize the bot interactions with hyper-personalized responses, allowing them to provide the correct support, faster. On top of increasing general customer satisfaction, an advanced AI can be used for a plethora of use-cases, like picking up on any purchasing intent and transform that into a revenue-generating opportunity, for example.

At the same time, with the advent of ChatGPT and its advanced large language model (LLM), customers are coming to expect more from their experiences with chatbots.#

Saying that, leaving it up to an AI to make a recommendation is not a strategy that is without risk. Customers can be left dissatisfied if they feel like their chatbot is taking them around in circles or overcomplicating the interaction. Similarly, it is essential that full customer context can be easily transferred from the chatbot to the agent, to save the customer from having to repeat all the details of their issue.

In an environment where answers need to be at agents’ fingertips so they can quickly get them into customers’ hands, reconsidering the contact center’s software stack to integrate AI has never been more critical.

But you needn’t tear down and build again from scratch. To ensure maximum efficiency in business processes and get full return from existing investments, look at what extra functionality you might need, plus resolve and reduce replication in what you have.

Using ‘point products’ as an alternative to monolithic or multi-purpose software leads to the improvement of specific, targeted areas. It also reduces the risk of feature bloat, where programs start to recreate the capabilities of other software instances.

The replication of software’s abilities leads to the development of non-standardized working processes. If multiple disparate systems are used, it can especially take its toll on the productivity of customer service agents, who tend to work on different back-end tasks simultaneously.

One company offering such directed, ‘point’ solutions for the contact center is Freshworks. The California-based firm has been weaving AI into its suite of CX products like Freshdesk and Freshchat since 2018, optimizing them for the customer, agent, and the business leader alike.

Freshdesk is the company’s ticketing system that brings together customer queries from multiple inbound channels. This system uses AI to learn from previous tickets and suggest new resolutions to save agents’ time.

Indeed, its ‘Freshchat’ bot is currently being utilized by over 60,000 businesses worldwide. It provides personalized responses over channels customers are already familiar with, like WhatsApp and Facebook Messenger, as well as a widget on product sites. Embracing preferred communication channels in this manner is one of the top five priorities for customer service leaders in 2023.

With Freshchat, team leaders can access performance reports and real-time dashboards so they can quickly assess productivity and the success of any CX initiatives. The generative AI can also use this data and make recommendations on how to optimize operations to meet business goals, saving precious time.

For the agent, Freshchat provides pre-formed responses for frequently asked questions, live translation, and bulk actions, all of which can help speed up the customer interaction and ease workload.

A priority for customer service leaders is driving business growth through their support teams, whose performance directly impacts both brand perception and sales. A Freshworks study found that returning customers are 82 percent more likely to repurchase a product after a value-driven service interaction.

If you’d like to learn more about how AI-powered technologies are improving the quality of the support experience, as well as 4 other critical priorities CX leaders must embrace in 2023, check out Freshworks’ essential strategies for driving customer value in today’s economy here.

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