AI in customer experience: How AI elevates your CX strategy

According to HubSpot, 90% of customers who contact a company with a question expect an immediate response. While human agents do their best to provide a valuable customer experience (CX), technology like AI has become essential to keeping up with shoppers’ rising expectations. In fact, 61% of shoppers would rather receive a faster reply from AI than have to wait to speak to a customer service agent about their issues.

AI has accelerated the capabilities of customer service teams, allowing them to offer everything from 24/7 service availability to personalized recommendations. If you want to build a customer experience that can meet rising customer expectations, then it may be time to consider bringing AI tools into your CX strategy. But first, it’s important to understand the benefits, challenges, and capabilities of these powerful solutions.

Key benefits of AI in customer experience

While the benefits of using AI may vary based on the tools you choose, here are some common ways this technology can be used to improve your customer experience:

• Personalization: AI tools are adept at collecting, analyzing, and using customer data to create personalized experiences. For example, AI customer experience tools can analyze buyer data to make customized product recommendations. AI can also analyze past issue history to help human agents create quick, positive resolutions to current problems.
• Automation: One of the biggest detriments to your team’s success is spending too much time on simple, repetitive tasks. With AI customer experience tools, you can take tasks like responding to frequently asked questions off your team’s plate, increasing productivity, and reducing burnout.
• Scalability: As your business grows, your customer experience will need to adapt to match your new volume of shoppers. AI solutions can take on an influx of requests without passing the burden onto your staff, freeing up your team for more valuable work during a critical time of growth.

Top challenges of implementing AI in CX

While the benefits of enhancing CX with AI are clear, these solutions also come with challenges. Here are a few common drawbacks to consider when shopping for an AI tool:

Data privacy 

Data privacy is one of the top concerns of consumers. They want to know what data of theirs is collected, how it’s used, and who it’s shared with. In fact, 81% of Americans believe the information companies collect about them will be used in ways they’re not comfortable with.

To get consumers on board, practice transparency. Being upfront with your users about the information you’re collecting and how your AI tools use this data can help build their confidence in your business.

Integration issues

The practicality of your AI solutions will ultimately depend on how effectively they integrate with your existing tech stack. Non-integrated solutions can end up creating more manual work than necessary, which can lead to errors and unexpected customer issues. Find out which integrations are offered by the AI solution you’re considering before making a final decision, as interconnectivity will be essential to maximizing the value of your new tool.

Training needs

Your new AI solution is unlikely to know exactly how you want it to act out of the box. It can take time and effort from your team to train AI tools to align with your brand voice and understand your internal data. However, some solutions are easier to train than others, like the AI tools that allow you to train them using internal data.

How AI enhances predictive analytics in CX

Customers expect brands to know their needs before they even do. That’s why many companies use predictive analytics to proactively identify and respond to buyers’ needs. Traditionally, this practice required businesses to spend a great deal of time and resources on capturing and analyzing data — that is, until today.

Now, companies can use AI to drive predictive analytics in CX. AI solutions can intake and process large data sets to pinpoint customer preferences, issues, and more. These insights can then be used to offer suggested products, proactively address customer issues, and find upsell opportunities.

Amazon, for example, is testing out the usage of customer data to offer anticipatory shipping. Using AI to analyze customer buying behavior, anticipatory shipping will send customers items they need before they even think about reordering.

While this may be a more advanced use case for AI, predictive analytics could alter the landscape of CX. On a smaller scale, AI tools could enable your business with the ability to:

1. Predict customer needs and behaviors

AI customer experience tools use dedicated algorithms to sort, analyze, and produce insights from customer data sets. Many of these AI solutions can find patterns in this data to help your team anticipate which products customers are interested in, when they may reorder an item, and what common pain points they encounter.

2. Personalize experiences

A quality customer service experience makes shoppers feel like more than just a number. With predictive analytics in CX, your team can find ways to ensure your customers feel seen. This could look like sending them customized offers, loyalty rewards, product recommendations, or birthday cards to show how valuable they are to your business. 

3. Proactively solve issues

There are often early indications in customer service that a customer’s issue is prone to escalation. You can teach AI to identify these common phrases, behaviors, or patterns and alert your team so that they can provide proactive intervention — preventing a potentially valued customer from churning.

4. Improve customer segmentation

Offering customers promotions and content that’s relevant to their interests is part of providing a quality customer experience. This is why many marketing teams predict distinct personas to help better target certain demographics with specific content. AI can use predictive analysis to help collect data and segment customers into ideal profiles on behalf of your team to simplify your marketing strategy and enhance the effectiveness of your customer service tactics.

5. Revamp sales forecasting

By analyzing sales data, AI tools can better predict customer buying behavior. These predictions can be used by your customer experience team to better plan promotional campaigns, design an enjoyable loyalty program, and ensure your customers have the products they want when they are most likely to buy.

6. Enhance customer engagement

Predictive analytics in CX can also be used to improve your customer service practices as a whole. These AI models can identify potential bottlenecks or issues in your customer experience, such as long resolution or response times. Using this data, your AI solution can make recommendations to increase customer satisfaction and agent performance.

7. Optimize resource allocation

Part of effective customer experience management is making sure you have the right people in place at the right time to handle customer issues. That’s why staffing is such a challenge in the world of customer service. Predictive analytics allow you to optimize the way you approach staffing. AI solutions can analyze historical data to identify times when high staffing levels are most necessary and help you better allocate your human and financial resources.

8. Refine decision making

AI’s ability to sift through large data sets and produce actionable insights can be essential when making core business decisions about your customer experience. Using AI for customer support lets you gather precious information about your buyers’ preferences, which can be leveraged to build an informed customer experience strategy.

9. Identify upselling opportunities

Predictive analytics can provide insight into the buying behaviors of your customers. Through AI, this data can be collected and analyzed faster than ever before. AI can pinpoint buying patterns, identify potentially compatible products, and suggest them directly to your customers — or provide this information to your human agents. These suggestions can make the customer experience more personalized and open the door to potential revenue.

10. Foster customer loyalty

Customer loyalty hinges on your ability to offer proactive service. Through AI-powered predictive analytics, you can anticipate the potential purchases your customers could make in the future and provide them with customized offers to increase their satisfaction. You can also use these tools to offer personalized suggestions or repurchasing reminders that suit your customers’ needs.

The future of AI in customer experience

Although AI has already begun to change how we understand customer experience, this revolutionary solution is far from finalized. Plenty of innovations will continue shaping the near future of AI-driven customer experiences, including:

• Conversational AI: As customer experience AI continues to evolve, it will increasingly resemble human interactions. Conversational AI uses a combination of natural language processing and machine learning to develop the ability to hold conversations similar to human beings. As this technology makes its way into CX, these tools will help enable a smoother, more enjoyable online experience for customers.
• Hyper-personalization: Beyond making general recommendations based on past shopping behavior, AI could evolve to make real-time, hyper-specific recommendations to customer needs. Using advanced predictive analytics, AI tools could recommend relevant products or offers to shoppers as they browse your site.
• Ethical AI in CX: This development battles one of the main complaints against AI: the ethical use of data. AI could develop an understanding of what data is ethical to use, how to be transparent about data usage, and how to ensure customers have a fair and beneficial experience.

To stay ahead of the curve, you need to pick an AI customer experience solution that’s already on the cutting edge, like Jotform AI Agents.

Start enhancing CX with Jotform

While AI as a technology can be essential to enhancing your customer experience, finding the right tools can be difficult. There are so many options available on the market today that it can be hard to make the best choice. But consider a solution like Jotform AI Agents, which offers a user-friendly, comprehensive, and customizable experience that is sure to improve your CX.

Jotform AI Agents help your business create a one-of-a-kind online experience — without writing any code. You can train your AI agents using internal data to handle simple, common issues your customers may encounter. Jotform’s AI-powered tools elevate your customer interactions to provide a more efficient, personalized, and robust shopping experience — all while efficiently collecting data for your team’s later use.

Getting started with Jotform AI Agents is easy:

1. Start from scratch, start with a form, or use a template to save time.
2. Train the AI with documents or URLs.
3. Customize it using the Agent Builder. Create and personalize your AI agent to fit your needs, branding, and expectations.

Jotform AI Agents also come in premade templates specifically designed for customer service. Customer service and support AI agents use machine learning and advanced natural language processing to accurately understand customer needs and provide appropriate assistance.

Agents can also be customized to accurately reflect your brand’s personality. From voice, visuals, and colors to support protocol and other specific industry requirements, you can program these tools to seamlessly integrate into your team’s existing customer service strategy.

Transform your customer experience with AI

Thanks to today’s technology, providing a great customer experience doesn’t have to be difficult. As AI for customer support continues to advance, how it benefits businesses and shoppers alike becomes harder and harder to deny.

Consider adding a solution like Jotform AI Agents to your workflow today to harness the transformative power of AI. A program like this can simplify your team’s life while elevating your overall customer experience.