Machine Learning in eCommerce to Elevate Customer Experiences

The eCommerce industry is booming. We’ve seen significant growth lately. Moreover, eCommerce sales will continue to rapidly increase, reaching $1.1 trillion by 2029.

While growth is good, too quick growth can bring many challenges — primarily, a highly competitive market. Customers will have limitless options, which can make it difficult for brands to stand out among the rest. Additionally, an overwhelming amount of choices can create buyer fatigue, leading customers to choose nothing.

To address these issues, eCommerce brands will need to turn to advanced solutions that involve hyper-personalization. Customer service should go above and beyond if they want to capture new users and drive customer loyalty. Luckily, machine learning (ML) technologies like artificial intelligence (AI) can make this process easier. 

The Power of Machine Learning

Machine learning is the new must-have technology that is taking just about every industry by storm. Everywhere you turn, different sectors are using machine learning applications to up their game and drive significant growth. This speaks to the versatility of ML technologies and how they can be leveraged for just about everything. For example, they can provide accurate data-driven insights, assisting with decision-making processes within a company.  

Just like it impacts other industries, machine learning is revolutionizing eCommerce and online shopping. When combined with existing human roles, ML makes eCommerce stores and the teams that run them even more effective. 

Big data, for example, is a major part of online experiences today. However, humans are only capable of processing so much data. ML learning tools can analyze huge amounts of data in a much shorter amount of time. Hence, they provide faster and more intelligent insights that can be used to improve the eCommerce customer journey. In other words, machine learning enables eCommerce brands to work smarter, better, and faster to deliver exceptional customer service experiences. 

Using Machine Learning to Improve eCommerce Customer Experiences

There are numerous uses and applications for machine learning when it comes to creating better customer experiences. Below are a few ideas for leveraging ML technologies to take eCommerce workflows and customer service to the next level. 

1. Hyper-Personalization

Personalized experiences are a new way to draw in customers and keep them coming back for more. ML makes hyper-personalization easier than ever. There are countless methods to use machine learning tools to personalize touchpoints:

• creating site navigation based on customer interests,
• implementing personalized product recommendations,
• sending emails based on products viewed or purchased.

You can even use ML to create personalized content for marketing campaigns to create personalized sales and offers. 

2. Issue Resolution

Machine learning is used in predictive analytics to assist in issue resolution. For example, intelligent tools powered by AI can spot complex patterns in data. Consequently, they can provide valuable insights that could then be used to anticipate and forecast potential customer issues. This enables brands to step in and take action before the issue becomes a more serious problem.

3. Customer Loyalty and Lifetime Value

ML tools can offer insights into ways to improve customer satisfaction. They’d leverage customer data, such as purchase history, feedback ratings, and behavior patterns to provide strategic recommendations. The same tools can be used to predict the potential future value of a customer. As a result, brands can focus on tailoring services and products to meet the needs of high-value customers. It can help cultivate long-term relationships and customer loyalty. 

4. Internal Communications

Internal communications aren’t just about making things easier for employees. When you improve internal communication, it can also impact the customer. When communication is streamlined, employees can collaborate and improve productivity. As a result, it will indirectly impact the quality of products and customer service. 

There are many ways to improve internal communication. For example, you can foster a more open and communicative culture or train for better communication. However, machine learning tools can also be used to boost internal communications. 

AI tools can be used to automate tasks, which can help streamline workflows and make communication easier. Managers can also use AI to create more targeted messaging to meet the needs of each employee. In data analytics, ML can provide real-time data enabling employers to make more informed decisions when communicating with employees. All of this means enhanced efficiency and productivity, which will have an impact on customer experiences. 

5. Chatbots 

One of the earliest trends in eCommerce applications of machine learning was chatbots. These tools have gotten even more advanced as ML technologies have evolved. Using natural language processing (NLP), chatbots can provide accurate responses and solutions without the need for human intervention. This enables CSRs to focus on more critical tasks.

6. Speech Recognition

Using speech recognition software powered by ML, eCommerce brands can analyze customer calls and direct them to the right person. These tools can extract information such as the customer’s sentiment and intent, as well as important keywords. Companies can use that information to route the call to the right support staff for an optimal solution. 

Wrapping Up

The applications and use cases mentioned above are just a few examples of how machine learning can enhance customer experiences. As ML algorithms become more sophisticated, eCommerce brands will be able to leverage these technologies to create hyper-personalized experiences. With this in mind, the future of eCommerce holds a lot of promise. It will likely see unimaginable growth and success. 

If you’re looking for additional support for your eCommerce processes, reach out to Trellis for a free consultation on how to scale your business online.

Author bio

Charlie Fletcher is a freelance writer passionate about workplace equity, and whose published works cover sociology, politics, business, education, health, and more. Check out the full portfolio on https://charliefletcher.contently.com/.