March 9, 2023

Should You Consider Artificial Intelligence for Customer Experience Improvement?

You have undoubtedly heard about artificial intelligence (AI) and how it will impact many business areas. Perhaps you’ve even researched artificial intelligence for customer experience. But before you go down that path, consider how AI could positively or negatively impact your B2B customer strategy.

In a world striving for optimal efficiency, we see more and more removal of the human element from business processes at all levels in favor of automated digital solutions. However, a solution must be personalized and tailored to the issue at hand to address a customer’s problem effectively.

And while AI can “substitute” for a human in some cases, many of these solutions are generic and gloss over the nuances inherent to any given challenge—nuances that should influence the resolution. When it comes to B2B customer support, AI’s disadvantages include a lack of: 

AI is simply not a replacement for human customer service. Companies that rely too heavily on automated solutions will end up with unsatisfied clients who may not return. 

Read on to learn how ineffectively using artificial intelligence for customer experience costs not only money but also your relationships with current and future customers.

Is There a Place for AI in Customer Service?

Don’t get us wrong—AI can be a helpful complementary tool to improve the customer experience at your company, particularly in data collection and organization. It enables representatives to provide better customer service by making these time-consuming processes more efficient. 

AI can benefit your customer experience team by:

Artificial intelligence sorting computer files for lead generation services

Currently, AI works best for highly transactional, low-value scenarios. For example, a customer wants to check on their $10 order status, and your company handles thousands of orders daily. An AI tool can quickly answer the customer’s query without wasting your team’s time.

However, this becomes problematic for businesses with lower transaction rates and high customer value. Say you have a client buying $50,000 worth of products annually. This type of client likely requires (and is certainly worth) a more personalized customer experience.

So yes, artificial intelligence for customer experience purposes can work—but it should never fully replace the human in the equation.

What Are the Drawbacks of Artificial Intelligence?

Highly Impersonal & Non-empathetic

Recall positive customer feedback that you’ve received. What do those reviews usually center around? 

Most likely, your team and the way they made the customer feel! Customers are loyal to companies that get to know them personally, understand their situation, and remember them when they return. 

If you’re debating between using AI and hiring an outsourced call center, remember that AI is incapable of the above the way a human representative is. Even in believable and convincing AI cases, once people realize they’ve been dealing with a chatbot, their perspective shifts. This could sour an otherwise positive interaction if customers feel deceived.

Empathy becomes even more crucial for handling complaints or high-anxiety situations, which require emotional navigation that AI can’t provide. A 2019 report by Verint found that most consumers want to speak to someone by phone or in person when they have a question or complaint. 

Now, consider a time when you have had an issue with a service or product. Have you had to fight through AI to reach a live person? Did it leave you feeling even more frustrated and anxious? 

Don’t do the same to your customers!

Sure, a chatbot can be programmed to apologize to an unhappy customer. It could even include a discount, replacement, or freebie. But it can’t provide that ever-important empathy. These automated apologies won’t feel genuine and could make your customer feel like just another number.

Bottom line: People still desire emotional intelligence from brands. Companies must use artificial intelligence to gather crucial analytics and support customer relationships rather than replace humans.

Unable to Develop New Solutions or Connections

You understand why customer experience matters for B2B clients. The B2B buyer’s journey often takes longer, takes more research on the prospect’s end, and requires more personalized solutions on your end. Trained representatives can tailor products or services to your clients’ needs to maximize satisfaction and retention. 

This is where AI fails. It uses compartmentalized thought and can’t make abstract connections between pieces of information that appear separate like a human mind otherwise could. AI cannot understand creativity or identify beauty, meaning it can’t see all the possibilities we can!

A customer chatting with artificial intelligence for customer experience

“The main problem with AI is that it’s focused on achieving the results you tell it to complete. This means it’s not very good at deviating from its instructions or coming up with unexpected solutions to problems,” Devan Leos wrote in an Entrepreneur article.

Because of this disconnect inherent in AI thinking, customers won’t receive solutions they couldn’t find and gather themselves. The answers to old problems that AI is likely familiar with may not meet clients’ future needs as new scenarios arise.

Instead, the purpose of artificial intelligence for customer experience should be to gather, collect and organize. The action plan must come from people who are invested in the outcome the way a computer cannot be, whether you opt for an outsourced contact center or keep customer service in-house.

More Costly in the Long Run

You can’t ignore cost when evaluating your lead generation services and options. And wouldn’t using an AI tool be so much cheaper than hiring reps or finding a call center solution?

Not necessarily! Consider: 

When you consider all of the above, AI software is by no means inexpensive. It’s not a set-and-forget or one-time-cost solution. First, you have to purchase it. Then you must install it on your website and support lines, maintain/fix it, and update it.

Lead generation services wasting money on AI

But the ultimate cost of AI use ends up being the loss of customers who are not satisfied with their experience. This goes for both current customers, who will be disappointed if the service quality drops, and new ones, who experience a poor, impersonalized first impression of the business. Losing that personal touch and annoying customers simply aren’t worth it. It will cost you more money due to lost business and low client retention.

Plus, since AI must collect data to respond to customers, there’s an added cost and risk. You must keep up with mandates for site infrastructure to ensure security and privacy and prevent data breaches. Of course, AI is young, and its security is far from perfect—if your system is ever compromised, your company will be financially responsible.

So if the primary reason you’re considering artificial intelligence for customer experience is cost, think again. Investing in an outsourced call center company could save you money, deliver a better return on investment, and avoid other financial risks in the long run.

Final Thoughts on Artificial Intelligence for Customer Experience Improvement

As you weigh the advantages and disadvantages of implementing artificial intelligence for customer experience tasks, remember its inability to empathize or think outside the box and its upfront and hidden costs. These qualities give AI a minimal place in customer service.

Relying on AI alone will not cut it for your customer support. You could end up with: 

However, you could use AI to assist your customer service reps to:

Do you want to explore what customer experience solutions best suit your business? Reach out to Chameleon to discuss all of the possibilities today! Our people-centric team will guide you and take the stress of lead generation and customer support off your team’s plate.

Contact Us Today

"*" indicates required fields

This field is for validation purposes and should be left unchanged.