Leverage the power of AI to boost customer experience

Published August 12, 2022

What exactly is artificial intelligence (AI) — the robots, algorithms, the singularity, and machines taking over the world? Despite what Hollywood would have us believe with movies like “Transcendence” and “Ex Machina,” AI is data-oriented computer programming in its simplest state. Whether software or hardware, AI takes data and then uses that information to create actionable solutions for the task it has been assigned.

How AI improves the customer experience

Machine learning and AI capabilities include absorbing personal data to analyze customer behavior and trends and providing businesses with customer insights. One use case is AI marketing technology. It helps companies identify different segments within their target market and use more appropriate marketing material tailored to each customer. 

Additionally, AI functionalities can be integrated into business operations to enhance the personalization of the customer experience. No matter what the industry is — retail, restaurants, finance — all sectors have use cases for an AI strategy. For example, Starbucks improved personalization by predicting and preparing daily orders based on its Deep Brew AI system. Another company harnessing personalization with the power of AI is Home Depot. Its algorithm can make a personalized recommendation based on voice and image-based search, which helps increase sales and forecast demand. This use of predictive analytics lets companies make real-time decisions on the go to provide a personalized customer service experience while having a keen idea of how to manage inventory in the months ahead.

If a further push is needed, a recent analysis shows that 99% of Fortune 1000 companies are investing in AI — and 92% are accelerating their investments.

Benefits of AI to manage customer expectations

It’s estimated to be five times more expensive to acquire a new customer than maintain an existing one. There can be huge cost savings from AI tools improving customer retention.

An estimated $136.80 billion is lost yearly due to churn, which can make a meaningful difference in revenue, margins, and profitability. So, how does AI effectively reduce churn rates?

There will always be times when churn is unavoidable — think of layoffs and relocations. However, AI can pre-predict when a customer might leave. If identified, employees can intervene to persuade customers to stick with them or retarget customers to keep their business. 

On the other hand, companies can use AI, machine learning, and analytics to spot their most valuable customers. This lets them isolate the ideal customers to upsell products and services to. 

Improving the overall personalization experience will strengthen customer loyalty and brand recognition. This has numerous positive knock-on effects for companies too. For some perspective, here are some of the heavy-hitting stats to back the data up, courtesy of HubSpot:

  • 94% of U.S. consumers will recommend companies they deem “very good.”
  • 93% of customers will likely make a repeat purchase in exchange for excellent customer support.
  • 80% of people said they would change to a competitor after more than one bad experience.

Creating this loop of positive experiences is achieved by isolating core problems. Once found, solutions need to be rolled out to have a meaningful impact

Let’s say a customer is trying to reach customer support — because that’s the only option. They don’t want to be on hold for 30 minutes, simultaneously scanning a website’s FAQ section for an answer. Doing something as simple as incorporating a virtual assistant — or conversational AI — to address menial queries can make a world of difference.

How to begin using data to personalize the customer experience

There’s been an expression used in the media in recent years: “ Data is the new oil.” This refers to the fact that companies seeking to innovate run on user data. How would they improve the product or service and compete with others without it? That’s the entire purpose. Operating without data is like going into a sword fight blindfolded. 

That being said, data needs to be of a certain quality to be of any use.

Good quality data has five characteristics:

1. Relevance

2. Accuracy

3. Completeness

4. Timeliness

5. Reliability

Relevance is the degree of importance the information has.

Accuracy ensures all data received and analyzed is correct. 

Completeness refers to having all of the necessary information available.

Timeliness refers to how recently a data point was collected. The older the data, the stronger likelihood that it’s not as relevant.

Reliability is the sum of all other points. If it’s not reasonably trustworthy, the data has no real use. In fact, it could potentially damage the reputation of a firm.

Before businesses even start collecting data, they should come to a reasonable conclusion of what their customers’ most valuable data points are. Only then should predictive analytics, chatbots, and other capabilities be tested.

But, once done correctly, businesses can start compiling large quantities of data, leading to customer success. Inferring probabilities about loyalty and spending and improving existing products and services is just the start. The real purpose is not only to prevent firms from failing but to improve the quality of the business. More efficient end-to-end channels and personalized customer experience are just an added plus.

Businesses shouldn’t be taking shots in the dark with social media ad campaigns and hoping for the best. They need to utilize data and AI to advertise products using omnichannel personalization to find customers who may genuinely be interested.

AI tools that can be used to enhance customer experience

AI can handle the simple, recurring issues that happen with all businesses. One way this can be done is by utilizing a chatbot rather than a human agent. While it may be a surprise, chatbot statistics have shown that more than 87% of users are satisfied with customer interaction. Another point that may influence this is that 63% of people don’t even realize they are talking to a chatbot. 

This speaks volumes about how far the industry has come and how sophisticated artificial intelligence is. Incorporating bots makes the life of a customer support agent more manageable. It lets employees dedicate more time to more important issues by limiting human interaction. All the while, the customer journey is refined.

If a customer needs to escalate an issue, AI integrations mean they’re in safe hands. Service professionals are equipped with all the tools and information they need to deal with customers — including those that may be thinking of ending the business relationship. Identifying these issues early will exert huge returns for the lifetime value of customers by creating trust between parties. 

Finally, it’s important to note that the earlier AI is used, the smarter it gets. Getting top-level decision-makers on board is the driving force behind AI adoption. Producing great analytics requires investment in talent and technology, but the alternative is business deterioration.

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