If you’re not already using AI in customer support, now’s the time to change gears.
AI (Artificial Intelligence) has come a long way from being a niche concept for tech enthusiasts. Today, it’s a mainstream part of everyday life, driving efficiency, productivity, and creativity in every industry.
Airlines use AI to predict flight delays and streamline check-ins. Real estate agents use intelligent tools to schedule open houses and appointments. Even fast-food chains use AI to keep drive-throughs running smoothly. AI is everywhere.
AI has a lot of potential in customer support. More than 86% of leaders say they think AI will help them boost their customer service strategy.
But, effectively using AI for customer support is trickier than it seems.
When a single negative interaction with your brand (even if it happens with a bot), can harm your company’s reputation and drive customers away, it’s essential to approach AI with caution.
In this guide, we’ll explore the basics of using AI for customer service and outline everything you’ll need to consider before diving in.
Artificial intelligence, or “AI,” is the term for technologies that enable machines to perform tasks like humans. AI systems aim to mimic human cognitive functions like problem-solving, decision-making, and learning.
Understanding AI is challenging because it is not just one thing. AI involves many interconnected technologies, such as machine learning, deep learning, and automation. However, the overall goal of AI is, in most cases, to enhance how people and machines work together.
According to one of AI’s founding figures, John McCarthy, the goal is for machines to be able to “act” like humans, so we can collaborate with them more effectively. For instance, with AI tools like Aivanti companies can automate repetitive tasks, collect and use data more effectively, and deliver more personalized experiences to customers.
Using AI for customer support usually involves taking advantage of various interconnected “sub-sections” of AI technology. One of the most important components of AI in customer support is machine learning (ML). This is a branch of AI that allows systems to learn and improve on their own, without having to be explicitly programmed to perform tasks.
Instead of following strict rules – like matching a customer’s service request to a pre-defined response based on keywords – ML analyzes patterns in past data to make predictions and suggest solutions. Machine learning helps things like Amazon’s product recommendation engine make better suggestions to customers over time.
Machine learning in customer support is a game-changer. With machine learning, AI agents can more effectively understand and predict what customers need, based on previous interactions. They can even personalize interactions in real-time.
The rise of machine learning is just one way that AI for customer support is becoming smarter. Increasingly, innovators are exploring the world of deep learning too. This advanced form of machine learning relies on neural networks, which mimic the function of the human brain.
Deep learning allows systems to process unstructured data (like documents, text or speech), and learn from them. AI customer support tools powered by deep learning can understand and analyze more complex queries. Some can even detect user sentiment, by examining tone and language for signs of whether people are happy, frustrated, or confused.
With insights into emotions and intent, AI agents can adjust their responses in real-time, delivering more empathetic and personalized replies to customer questions. These days, around two thirds of organizations think the deep learning abilities of AI tools will help them give customers a more warm and familiar experience at scale.
Automation and AI are usually very closely linked, particularly in customer service. AI can certainly automate support tasks, like answering routine questions customers have about your ecommerce business, return policies, or stock levels.
However, there is a difference between automation and AI. Automation involves setting machines up to follow pre-set instructions. For example, an automated tool built into your e-commerce platform might be “triggered” to send a confirmation email when a customer places an order.
AI is more dynamic. Using algorithms, AI-based customer support tools analyze data and make decisions based on historical insights and current circumstances. AI goes beyond following rules to complete intuitive tasks for companies.
For instance, an AI assistant like Aivanti can analyze customer history, and suggest new products they might want to purchase or introduce new ways of troubleshooting issues. Understanding the difference between AI and automation is how you make sure you’re taking the right approach to adopting new tech. It’s how you can ensure you’re differentiating between simple repetitive tasks that can be automated without “intelligence” and processes that require AI innovation.
AI has become pretty commonplace among customer service teams. More than 63% of retailers say they’re already using AI to “improve” customer interactions. Adoption is growing in just about every industry – particularly since new models like the world-famous ChatGPT exploded into the spotlight.
With more advanced models and algorithms, companies can achieve more with AI in customer support than ever before. Today’s teams aren’t just using AI for things like extracting insights from real-time and historical data.
Companies are turning to AI to reduce contact handling times, make teams more efficient, improve employee engagement, and personalize interactions. AI tools with machine learning are helping companies predict future customer needs and adapt to market dynamics. Generative AI is leading to more consistent, personalized interactions between customers and bots.
Using artificial intelligence support tools can even help companies save money on hiring extra staff for a 24/7 approach to service. But there are still challenges to overcome.
AI is frequently painted as the ultimate fix for all customer support issues, from improving scalability to reducing workloads. However, it’s not a magic bullet. Even the best AI tools can’t handle every customer support task or request. That’s why 75% of CX leaders say that AI should be a force for “amplifying” human intelligence, not replacing it.
There’s no doubt that AI has great potential, but its benefits need to be weighed against its limitations. Customers still get frustrated with poor chatbot interactions, and still want to reach out to a human representative at times. The key to success is finding the right balance between human input, and AI technology in your customer experience strategy.
Artificial intelligence customer support strategies are nothing new for most companies. But as new innovations continue to emerge, like generative AI, demand for AI will grow. Businesses that want to take advantage of all the benefits AI can offer, without running the risk of harming their reputation, or frustrating customers, need the right approach.
The first step in effectively using AI for customer service is getting to know your customers. That doesn’t just mean brushing up on demographic data. You need to know more than just where your customers are located or what age category they fall into.
Great AI solutions for customer support work because they’re fine-tuned to customer preferences. They’re designed by companies that understand their customer’s needs, pain points, and preferences.
Before you invest in AI tools for your business, ask yourself:
The best way to get the data you need to start building your AI strategy is with research. Evaluate contact center analytics and data from your e-commerce platform, but speak to customers directly too. Send out surveys, conduct focus groups, and invest in social listening tools. Find out what customers really want, or don’t want from an AI-driven experience.
There are plenty of ways to use AI for customer support. Most companies start with two focus areas: self-service, and agent support.
Around 61% of buyers say they always choose instant responses from an AI bot over contacting a human support team. So it makes sense to use AI to help customers solve problems quickly, on their own. Generative AI is particularly good at improving chatbot conversations. Unlike old rule-based bots, generative AI bots can create novel responses to queries, learn from data, and adapt to unexpected customer requests.
Self-service options featuring Gen AI can dramatically improve your 24/7 service strategy, and reduce the number of inquiries human agents have to deal with.
From an agent support perspective, AI is the key to helping sales and customer service teams accomplish more with less effort. In sales, AI analytics tools can identify qualified leads based on pre-set guidelines, ensuring teams can focus their attention on the right prospects. In customer service, AI tools can summarize previous self-service conversations and send them to agents, giving them the context they need to keep discussions flowing smoothly.
Unlocking the full benefits of AI in customer support means looking beyond just one or two touchpoints where AI can improve experiences for your customers. You need to think about the full customer journey, and identify every opportunity for improvement.
Step into the shoes of your target customer, and ask yourself what they experience when working with your company. How do they learn about your products to begin with? Where do they go to research their options? How do they make purchasing decisions?
Even implementing chatbots into more stages of the customer journey can improve experiences for 84% of customers. For instance, instead of just using an AI tool to answer support requests, you could use your chatbot to send personalized product recommendations to customers, help them track their orders, or keep them up to date about new store products.
Be aspirational during this stage. Don’t get bogged down thinking about budget limitations. Instead, visualize what the ideal AI-powered customer journey will look like from end-to-end. Once you’ve got a clear view of everything you can change and improve, you can begin to prioritize strategies based on your budget.
One of the trickiest parts of using AI tools for customer support is figuring out how much you can afford to invest in a new solution, model, or platform. Unless you have endless financial resources, building an AI system from scratch probably won’t be an option.
Fortunately, pre-built AI-powered chatbots and tools for customer service, like Aivanti, make it easier to implement next-level technology without spending a fortune. These tools generally don’t require a huge upfront investment. Plus, because they’re updated and maintained by another vendor, you can cut costs on maintenance and fine-tuning.
When you’re setting your overall budget, think about “Total Cost of Ownership” (TCO). In other words, don’t just consider upfront costs but the overall costs for training, updates, maintenance, integration and beyond. Then, think about the return on investment you can expect from your technology. Calculate ROI by considering the financial benefits of:
Now you’ve set a budget, and finished analyzing your customer’s needs and their journey, it’s time to design your AI implementation strategy. Start by identifying the tools you’re going to need to achieve your AI goals.
Do you need chatbots to enable self-service and support customers throughout the consumer journey? Are you investing in agent assistants that will make your employees more effective and productive? Maybe you want to use AI for IT support to improve workplace efficiency or access AI for analytics.
Based on your vision of how you can improve the customer journey and support your team members, decide what tools you will implement first and how you’ll monitor their results. Keep in mind the key to success is selecting tools that are effective, but still match your budget requirements.
Consider choosing more comprehensive AI tools for customer support that address various goals at once. For instance, Aivanti can deliver personalized service to customers, enhance sales funnels, and inform and educate your teams, all at the same time. This means you don’t have to invest in different tools for customer service, agent assistance, and analytics.
You’re almost ready to start implementing the benefits of AI and machine learning customer support tools into your business at this stage. But, before you go all-in, you’ll need to dedicate some time to training. First, make sure your AI IT support team is familiar with the tools your team will be using. This will ensure they can troubleshoot any issues your employees have.
Next, turn to your artificial intelligence customer service provider – the vendor giving you your tools. Ask them for documentation and details about how their systems work. This will help you to familiarize your team members with using AI for customer support purposes.
Invest in building comprehensive training programs and workshops for every team member who will be interacting with your tools. Cover topics like:
Give your team all the skills and insights they need to integrate AI customer support and assistance solutions into their day-to-day workflows. This will improve adoption and should lead to a better return on investment for your e-business.
Finally, to really get the most value out of AI in customer support, you’ll need to commit to continuous improvement. The more data you gather about how your tools and processes are influencing customer satisfaction and employee experiences, the better.
Fortunately, AI tools for customer support like Aivanti can help here too. They can make it easier to gather insights from interactions with transcription services, summaries, and reports. You can even use artificial intelligence customer support tools to collect direct feedback from customers. For instance, you can configure bots to ask customers in-depth questions about their experiences with your company and what they’d like to improve.
Regularly reviewing this data will ensure you can uncover quick ways to improve your strategy, and minimize risks. Use the information you collect to adapt your strategy based on customer interaction trends, feedback, and evolving technologies.
The benefits of AI for customer support are astronomical. But you’ll only get the right results with a careful approach. Every step you take, from deciding which AI and machine learning customer support tools you will use, to training your team members, makes a difference.
Even your approach to choosing the right artificial intelligence customer service provider is crucial. The right partner will help you to keep costs low, increase ROI, and get the most value out of your technology. Aivanti’s all-in-one solution for AI in customer support is an incredible option.
With this all-in-one platform, companies can access all the top benefits of AI for customer service. You can deliver 24/7 availability to customers, personalize every interaction, and access data-driven insights with endless scalability.
More than just a tool, Aivanti is a flexible platform and partner designed to grow with your business. It can adapt to changing team, customer, and ecom market needs, keeping you one step ahead of the competition. If you’re ready to experience the advantages of AI in customer support for yourself, contact Aivanti today. Discover how our AI tools for customer support can help you take a proactive approach to building a winning customer experience strategy.
