Artificial Intelligence in eCommerce: Benefits, Use Cases, and Ways to Implement

Artificial Intelligence in eCommerce: Benefits, Use Cases, and Ways to Implement
Article by DesignRush DesignRush
Last Updated: September 25, 2022

In popular media, artificial intelligence often conjures up visions of killer robots and space aliens.

But in eCommerce, AI is less about humanoids than about the complex algorithms and learning technologies laying the foundation.

Artificial intelligence can help present-day online retailers optimize customer experience on and off their eCommerce websites. This is done by collecting business and customer data to make informed decisions and predict the future accordingly.

This article will discuss using artificial intelligence in eCommerce and how this technology enables the eCommerce industry to move forward by improving customer interactions and streamlining the overall business processes.

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How is Artificial Intelligence in eCommerce Bringing a Change?

Artificial intelligence does have a cool factor to it, but it is not simply for this that the technology is widely implemented. AI has the potential to impact several business functions across an organization.

Understanding the components of artificial intelligence is crucial to evaluating how AI impacts your eCommerce business.

The concept of AI comprises:

  • Data Mining - the gathering of current and historical data to make predictions
  • Natural Language Processing or NLP - focuses on how computers interpret natural human language.
  • Machine Learning - a collection of algorithms to apply experience and draw examples to solve problems. Deep Learning refers to the process of algorithm layering to understand the data better.

Over the last few years, AI technology has become a powerful tool to increase sales and optimize operations. Today, even small eCommerce businesses prefer using technologies with a degree of AI capability.

What Are the Benefits of Using AI in eCommerce?

There are numerous benefits of using AI in eCommerce, and these are the top ones:

Targeted Marketing and Advertising

Personalization is one of the top eCommerce marketing strategies, but only a few businesses can fully implement it across channels. Standing out from the crowd and interacting one-to-one with your customers is imperative.

AI and machine learning enable deep personalization techniques to customize content.

By analyzing the purchase history and customer interactions induced by big data, you can clearly understand what your customers want and deliver what will resonate the most with them.

Increased Customer Retention

Customer retention is enhanced when you deliver targeted marketing and advertising messages personalized for the customers.

Research reveals a 10-15% uplift potential in retention and revenue from omnichannel personalization strategies.

Building better data and insights on customers is a critical element of personalization. It is an asset generating additional value, and the ROI for personalization will soon outpace traditional mass marketing.

Easy Automation

The purpose of automation is to execute a task with as little human intervention as possible. This can be anything from automating tasks to scheduling emails in a CRM to leveraging advanced technology to assist the hiring process.

AI and machine learning are the most popular eCommerce trends leading the future of the industry.

AI plays a pivotal role in automating the repetitive tasks that keep your online store running. You can also automate product recommendations, low-level support, loyalty discounts, and more with AI.

Effective Sales Processes

AI can help create a more efficient sales process by collecting data about your customers, following up on abandoned cart inquiries, and more. You can enable the customers to move through the funnel by engaging them with chatbots for simple questions.

AI in eCommerce: 5 Use Cases

There are numerous use cases for AI in eCommerce, and here are five that you might not be aware are built on AI technology. Let’s take a look:

Personalized Product Recommendations

With AI, gathering and processing customer data about their online shopping experience is easier. AI is used to provide personalized product recommendations based on earlier customer behavior.

Websites that analyze your purchase history use AI to recommend items you might like. Retailers also depend on this technology to collect and research data to deliver a personalized experience and generate customer insights.

Implementing marketing campaigns and optimizing pricing becomes easier with AI too.

Over time, AI will require even lesser data scientists’ involvement for everyday applications in eCommerce companies.

Pricing Optimization

The practice of altering the product price based on demand and supply is an AI-enabled dynamic pricing strategy. The AI tools can predict what and when to discount by accessing the correct data and calculating the minimum discount for sale.

Enhanced Customer Service

With chatbot technology and virtual assistant, businesses can deliver higher-touch customer support assistance. These bots are not entirely independent, but they facilitate simple transactions, allowing the live support agents to focus on the more complex issues.

Virtual agents are also available 24/7, so one can address low-level issues and questions at any time of the day without compelling the customers to wait for long.

Customer Segmentation

Equipped with more informed customer data and processing power, eCommerce operators can understand their customers and identify new trends better than ever.

AI systems can potentially explore the highly complex and varied options for customer engagement fast. They can continuously optimize the performance as more data becomes available. This also implies that marketers can set parameters and enable AI to optimize and learn to achieve precision.

Intelligent Logistics

Logistics is an area where AI shines. The technology helps in forecasting transit times, demanding levels, and delaying shipments.

Intelligent logistics is all about using real-time information through RFID tags, sensors, etc., for forecasting demand and managing inventories. Over time, Machine Learning systems get more intelligent to predict their supply chain and logistics functions better.

How To Implement Artificial Intelligence in eCommerce?

Implementing new technologies is always exciting, but a roadmap or strategy is necessary to make the most of it.

Here are a few steps to implementing AI in eCommerce:

Create a Strategy

Creating a strategy lays out the path to your AI goal before anything else. It would help if you analyzed what you want to accomplish with AI. Start small and take a practical approach as you build on your success down the road.

Find Use Cases Relevant to Your Corporate Strategy

The most successful and relevant AI use cases are usually at the intersection of data differentiation, business objectives, and AI training data and models.

Seek Third-Party Expertise

Even with considerable AI knowledge, it is always good to leverage expert assistance in implementing AI in eCommerce. A team of experts will be the best for building a robust and strategic AI roadmap. They can also help bring your minimum viable product (MVP) to prominence.

Develop a Full-Scale Solution

Once you are happy and confident in what has been produced, it is time to develop the full-scale solution. It might still take some iterations before working as expected. As you get more comfortable working in AI, you will identify more significant benefits from implementing projects.

Takeaways on Artificial Intelligence in eCommerce

The present-day AI for eCommerce might look less glamorous, but it increases conversion rates, improves customer experience, and helps streamline the way businesses run and operate.

If you aim to deliver the best possible customer experience on your eCommerce store, you must consider the multiple benefits of AI technology. Better use of business and customer data will set a plan that works.

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