January 4, 2023
Customer experience

An executive's guide to understanding where conversational AI can best impact CX

by Halvard Totland, Chief Product Officer, boost.ai

Artificial intelligence has been popularized in movies and entertainment as sentient bots that are purpose-built to replace humans. In reality, their applications are much more practical in nature and should be considered another handy tactic in the toolbox of software applications that can be the critical integration that drives your business to the next level of operations.

As solutions driven by machine learning and AI start to be verticalized into fields such as agriculture, healthcare and financial services, the ethereal idea of interaction with AI being a part of everyday life is starting to become accepted and even recommended for enterprises of all sizes that are looking to problem-solve stopgaps in their ability to scale. As consumers head more digital than ever, here are a few things to consider when looking to add AI into your CX flow.

CX can't be approached with a "one-size-fits-all" mindset.

In the days before SMBs and global enterprises alike needed a digital presence to be legitimized by everyday consumers, the customer experience was simply to monitor and improve. For brick-and-mortar businesses, CX was based on their ability to be personalized by remembering the names and faces of local customers. While enterprises now have the capacity to scale up their service range to the entire globe, the base metric of quality CX hasn't changed. Consumers may be driving digital-first more than ever, but that doesn't mean they don't want to feel like an individual rather than a number when engaging with their favorite companies.

As market sizes have grown from small towns to potentially billions of customers, CX flow has complexified to the point where entire consultant agencies are dedicated to helping improve the CX of companies of all sizes. At the root of it all sits the need for a personalizable experience. Anyone claiming this can be accomplished with a "one-size-fits-all" tool doesn't have the customer in mind.

AI-driven chatbots are helping to shape the next generation of customer support, but these chatbots are only as good as the context in which they are implemented. AI isn't innately going to give your business a personalized customer experience. However, when properly vetted and placed within an existing CX flow, it can help your business open the path for scalability previously not thought possible.

AI sounds exciting, but what type do you need?

There are an ever-expanding number of use cases for AI in customer experience and support flows, so it's understandable that there are just as many articles hyping up the potential for AI as there are ones looking to clarify just what exactly AI can do for everyday businesses. From my perspective, there are two basic categories to help define which type of AI you should focus on when looking to improve CX. While there are definitely more technical labels you could provide, these should help shape the basic path forward when searching for what AI might help you best.

• Customer-facing. Bots focused on customers are often built to be proactive, personalized and connected with the customer's past engagements with the brand such as e-commerce history or CRM data. They should be deployed when an enterprise has realized there is a need for enhanced support around externally facing teams that aren't able to currently handle peaks in traffic or would like to upgrade to round-the-clock support. The modern consumer has the ability to interact with brands through any number of channels such as a phone call, email, website form or direct message on social media. Properly integrated chatbots can now even respond to customers in an omnichannel format, ensuring continuity of content and communication across these multiple channels.

• Targeted at your support team. Vendors who offer chatbots that are customer-facing may also be able to integrate a similar system targeted at your support team. Virtual agents assisting support teams can boost live agents' ability to support customers by processing the conversation in parallel and continuously suggesting relevant information to the agent that can help answer the customer's inquiry faster. There is a misnomer that bots should replace support agents when, in actuality, their best place is at the right hand of the trained support expert.

Where do I go from here?

Determining the best course of action when implementing AI comes down to a few key considerations. What kind of offering will best serve not only your customers but also your employees? While positive experiences are central to maintaining customer loyalty, improving operations internally represents another pillar of the CX strategy. There is no one approach that best serves every organization, but AI can help deliver positive results when properly placed. An internal virtual agent can lift simple work from those who help customers with complex requests, just as an external-facing chatbot empowers customers with more self-service options.

Looking ahead, Gartner, Inc. predicts that one in 10 agent interactions will be automated by 2026. Whether or not your organization contributes to that growth is up to you. However, it's important to ask.

• What types of AI are most beneficial in your industry?

• How can those processes support customer experience across the service chain?

• What kinds of services are optimized? Which services aren't?

As an executive, your next move is to sit down with your key stakeholders to see what they can determine are some of the biggest stopgaps in your path to CX improvement. An integral thing to remember when gathering these stakeholders is that most IT projects are not ultimately going to land in just the technology department but are instead for use by other teams. Whether it be sales, marketing, customer service or support, you should ensure that individuals from both the technology team and the team in which this bot is going to be used are represented from the start. This can ultimately lead to a better product in the end and a lower risk of miscommunication about where AI can best impact your CX.

Originally published on Forbes.com

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