One of the most challenging yet essential tasks for any company is finding customers to provide a product or service that fulfills a need. However, it’s equally important to keep the customers you already have. 

Profits soar when a single customer you’ve found through marketing or advertising becomes a repeat customer.

Not only are loyal customers good for your bottom line, but they also help to spread the word to their network of family and friends. Good word-of-mouth marketing is the best advertising because it comes from someone independent and objective about a product or service. There are many ways to go about keeping your customers happy. Indeed, people have been working very hard on a problem for a long time—way before people were using AI for anything. The traditional way of maintaining a positive image in the eyes of one’s customers, like excellent customer service, paying attention to each stage of the customer journey,’ and rewarding loyal customers, still works. But these tried and true strategies can become even more effective when paired with the latest technology.

The key to understanding artificial intelligence is thinking about how a human responds to situations. So it’s always in a way that is flexible to the problem and what’s going on in it. 

An artificial intelligence system is just a machine meant to do the same thing: respond to an ‘input’ by producing an ‘output’ that’s the same or similar to what a human would do. 

For example:

• A human might look at a spreadsheet of a customer’s recent purchases and make a good guess about what their next purchase will be. 
• An AI system would be able to do the same thing if it’s correct, at least as often as the person can. 

However, we’ve seen many AI systems better than humans at specific tasks. 

One way that AI can outperform humans in specific tasks is through inculcating machine learning-based algorithms.

Machine learning produces systems that intelligently respond to inputs by analyzing thousands, hundreds of thousands, or millions of examples. 

By picking up on different features of these examples, the machine learning algorithm can learn to make predictions with tremendous accuracy. 

To go back to our example above, you could train a machine-learning algorithm to guess whether or not a customer will make a new purchase in the next six weeks. 

After comparing the actions of hundreds of thousands of customers, AI might well outperform humans. This use of AI, called predictive analytics, is becoming increasingly popular in the business world. 

AI and machine learning have already been applied to:

• Customer relations
• Customer loyalty
• Customer retention

In particular, the data collection that’s now easier than ever can be used to train machine learning systems to provide personalized experiences to your customers, showing them only the products they find interesting.

These days, it’s become trendy to refer to customer experience as CX—but this is just a new name for the old process of ensuring all the interactions your customers have with your business create positive experiences rather than negative ones. When you leave your customers with positive impressions, they’ll form positive memories and make purchase decisions in the future on that basis. Here are a few ways executives have been using AI to improve CX. 

Personalization

In general, the personalization of websites using AI revolves around delivering unique, AI-powered content to each consumer based on their preferences and previous activity. AI can be helpful for this purpose because it can track what someone has been doing on your website and automatically create a unique experience for them. Another way to use AI for personalization is by crafting custom email content shaped by which links the person tended to click on in the past. 

Engagement and communication (Chatbots)

Chatbots started poorly, getting a reputation in the early days of the internet for wooden, repetitive answers that didn’t respond to questions. However, that was years ago, and people are starting to realize that technological advancement in AI has brought us chatbots that can chat. The Acquire chatbot has been getting a lot of hype lately for its human-like output. Often, text-based chatbots are a more effortless way of getting information from your company, especially in comparison to picking up the phone and calling your customer service division. The instantaneous answers leave your customers feeling like they haven’t wasted any time resolving their problems. 

Effortless user experience

Web designers have a term for a user experience they try to avoid at all costs: friction. The harder it is for customers to do what they want to do on your website, the less likely they’ll continue using it. It is a situation where bad design can lead to lost customers. Including AI in the loop for design is becoming more and more common. Although humans aren’t replaced in this process, AI can try thousands of times to solve experience problems and generate innovative designs. But this doesn’t know if an idea is innovative or simply odd. That’s for humans to decide still. AI isn’t inherently creative. It only amplifies humans’ creativity. If humans are kept in the loop, it can be a tool to help navigate a variety of issues to improve the user experience. A crucial part of user experience is how responsive a company is to problems. Not only can you use an AI chatbot to respond to questions, but you can also use it to direct customers to a human employee that specializes in their problem. A company called five9 has developed several applications that help improve the efficiency of your customer service while keeping everyone happy. 

Self service

The idea behind self-service in the CX space is to avoid human intervention in customer support altogether. It can lead to a much quicker resolution of problems than getting a human agent involved in problem-solving. The name of the game here is creating a customer journey through the support system where every step is straightforward and quick and gets them closer to solving their problem. In addition to chatbots, you can add techniques like sentiment analysis and predictive analytics. If you can train a machine-learning algorithm to guess what issue a customer has based on their behavior, you can deliver solutions exceptionally quickly. 

Handling large volumes of people

One of the best aspects of AI customer experience systems is how they scale. Once you have a high-quality and responsive AI system, it will work whether twelve people are looking for assistance or twelve thousand. This AI implementation dramatically differs from traditional, human-led customer service, which only has so much capacity. Once that’s exceeded, you’ll have customers spending extended periods on hold. That’s never a good thing for customer loyalty.

In a certain sense, customer loyalty programs are about rewarding your best customers for their continuing engagement with their business. However, the other reason is that they give your customers incentives to stay through discounts and other perks. 

Like anything else in business, a customer loyalty program is an investment that should yield more in revenue than you spent on it. 

Identify customers likely to leave 

Your business can use AI to improve the outcomes of your customer loyalty program through data processing and predictive analytics. 

Identifying which customers are likely to leave soon and targeting them with incentives to keep them in the fold is possible.

Since an AI system can keep running and updating its predictions, you can split customers into different categories that update dynamically depending on how their behavior has changed. 

Monitoring fraudulent behavior

Some loyalty programs open themselves to exploitation by malicious actors looking to take advantage of the deals or perks. A fraud-management system can monitor customers’ behavior to ensure they aren’t getting more benefits than they deserve.

As we’ve already gone over, one of AI's greatest strengths is its ability to make predictions quickly and accurately. As a result, AI has many benefits to following how customers interact with your business and using it to predict what they will need and do next. 

Predicting buying trends

One of the most popular ways to use AI is to predict future demand for products and services. This knowledge can help your business, from managing inventory to marketing specific products to certain demographics. 

Sentiment analysis

The way that people interact with businesses isn’t just driven by reason and logic. Emotions play a significant role as well. Many AI systems track how your customers feel, like Lexalytics Salience and Meaning Cloud. 

Customer churn prediction

Customer churn refers to the number of recently stopped customers using a company’s products or services. Knowing how many customers are likely to leave in the future can help with planning and preparing initiatives to find new ones.

AI and machine learning can speed up and improve new product development and discovery, leading to reduced costs, better products, and greater customer loyalty. AI systems that allow companies to test out their products virtually give business leaders a chance to see how their products will perform in the real world before it gets there. 

Testing many different versions

AI can let you try out far more options than the usual human-led A/B testing paradigm. Instead, you can try hundreds of slightly different products and have an AI system track how well they’re being received. 

Predicting recalls and problems at launch

One tool that researchers are developing is AI systems that can find and fix problems before they occur. For example, researchers have been able to predict which foods and brands are most likely to face recalls in the future using only Amazon reviews. 

Understand your competitors

One way to fine-tune your products to ensure they succeed in the market is by looking carefully at your competitors’ products and analyzing how they appeal to customers and how they fail. Outperforming competitors in terms of the quality of your products or services is undoubtedly a way to keep customers in your camp.

In customer loyalty, insights are the value that can be extracted from data using analytic tools. For example, creating and using a machine learning model can help you identify new segments of the market to which products can be tailored and identify the parts of your customer loyalty program working well. 

Understand consumer perceptions

Through programs that collect data about customer actions and sentiments, the development of customer loyalty programs provides the correct level of incentives to get the most out of your investment. 

Evaluating and tailoring your marketing

Machine learning can evaluate the individual responses of thousands of competitors to your marketing materials, giving you a deeper and more exhaustive understanding of what messaging is the most successful. 

Evaluating the health of your customer service

AI isn't only good for improving your customer service. It can also generate insights into customers' frustration and suggest ways to avoid that outcome.

If you were skeptical that AI can make a difference in the up-close and personal world of customer relations, we hope this article will convince you otherwise. 

Customer loyalty, maintaining an ongoing and positive relationship between a business and its customers, is a vital part of running any business. There are many ways that AI can improve both results and efficiency. 

If you want to learn more about the various uses for AI in customer relations, take a look at longer posts on how it interacts with:

• Customer loyalty
• Product development
• Customer service

Unbxd is an AI-powered product discovery platform that helps brands exponentially scale online with relevant and personalized customer experiences.

We provide contextually relevant and customized Search, Personalization, and Product Recommendation solutions and an intelligent merchandising console to help you meet your eCommerce objectives all year long.

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