Artificial Intelligence in Ecommerce: How This Rapidly Evolving Tech Will Change the Online Storefront

When someone says “artificial intelligence,” the first thing that comes to mind might be a vision from movies like Steven Spielberg’s 2001 film A.I. Artificial Intelligence, sci-fi thriller Ex Machina, or 1982 cult classic Blade Runner.

But when it comes to the ecommerce sector, it’s less about human-like robotics and more about the learning technologies and algorithms that provide the foundation.

AI can help today’s online retailers deliver an optimized customer experience on and off their ecommerce websites by using collected business and customer data to make better business decisions and more accurately predict the future.

Let’s look at some of the ways AI and associated technologies are moving the ecommerce industry forward, from improving customer interactions to streamlining business processes.

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From digital transformation and software-as-a-service to virtual reality and artificial intelligence, technology keeps pushing the limits of what ecommerce can do. 

With compounding advancements in technology, there’s something new competing for online retailers’ attention every day. You’ll never find yourself at a loss for something new and different to try — the real task is identifying the best opportunities for your ecommerce business.

Artificial intelligence isn’t just a novel technology implemented for its “cool factor.” Implementing AI has the potential to impact any number of business functions across your organization. 

To understand how it could impact your business, it helps to have an understanding of the components of artificial intelligence. 

The definition of AI is broad, and encompasses data mining, natural language processing, and machine learning.

• Data mining refers to the gathering of both current and historical data to inform predictions. 
• Natural language processing focuses on human-computer interaction and how computers interpret natural human language. 
• Machine learning concerns using a collection of algorithms to apply past experience or provide examples to solve a problem. Deep learning “involves layering algorithms in an effort to gain greater understanding of the data.”

Over the past couple of years, AI technology has matured and become a powerful tool to boost sales and optimize operations. Even many small ecommerce businesses are using technology with some kind of AI capability.

Amazon has long recognized the benefits of artificial intelligence and related technologies. The behemoth ecommerce company uses machine learning to improve product selection and user experience and to optimize logistics.

A recent publication from McKinsey & Company and the Retail Industry Leaders Association named seven imperatives for rethinking retail in 2021, and every single one could in some way be supported by some type of AI-informed technology.

Personalization is a top priority, according to surveyed retailers, but only 15% say they’ve fully implemented personalization across channels. Stand out from the crowd with a more personalized message and have one-to-one conversations with your customers. 

Advances in AI and machine learning have enabled deep personalization techniques to customize content by user. By analyzing big data from purchase histories and other customer interactions, you can zero in on what your customers really want and deliver the message that will most resonate.

Delivering targeted marketing and advertising messages personalized for their customers can increase retention. McKinsey omnichannel personalization research indicated there’s a 10-15% uplift potential in revenue and retention from omnichannel personalization strategies. 

The report reads: “A critical element of personalization is building better data and insights on customers, an asset that also generates additional value across the value chain. … Our research suggests the ROI for personalization will quickly outpace that of traditional mass marketing.”

The goal of automation is to accomplish a task with as little human intervention as possible. That can mean anything from scheduling emails in a CRM or marketing tool, using Zapier to automate tasks or leveraging advanced technology to help with hiring. 

In the context of future ecommerce trends, however, some of the most commonly talked about today are robotics and machine learning.

AI can play a big role in helping you automate the repetitive tasks that keep your online store functioning. With AI, you can automate things like product recommendations, loyalty discounts, low-level support, and more.

Using AI can help you create a more efficient sales process by gathering data about your customers, automate follow-up abandoned cart inquiries, and more. You can help move customers through the funnel by having them engage with chatbots for simple questions.

There are plenty of use cases in ecommerce for AI, and you’re probably familiar with a lot of them — you just might not know that the technology they’re built on is actually related to AI. Here are six of the most common: 

1. Personalized product recommendations.
2. Pricing optimization.
3. Enhanced customer service.
4. Customer segmentation.
5. Smart logistics. 
6. Sales and demand forecasting.

It’s easier than ever to collect and process customer data about their online shopping experience. Artificial intelligence is being used to offer personalized product recommendations based on past customer behavior and lookalike customers.

Websites that recommend items you might like based on previous purchases use machine learning to analyze your purchase history. Retailers rely on machine learning to capture data, analyze it, and use it to deliver a personalized experience, implement a marketing campaign, optimize pricing, and generate customer insights.

Over time, machine learning will require less and less involvement from data scientists for everyday types of applications in ecommerce companies.

AI-enabled dynamic pricing is a strategy of changing your product price based on supply and demand. With access to the right data, today’s tools can predict when and what to discount, dynamically calculating the minimum discount necessary for the sale.

With virtual assistants and chatbot technology, you can deliver the appearance of higher touch customer support. While these bots aren’t completely self-reliant, they can facilitate simple transactions, leaving live support agents able to focus on more complex issues. 

Virtual agents also have the advantage of being available 24/7, so low-level questions and issues can be addressed at any time of day, without making your customer wait.

Access to more business and customer data and processing power is enabling ecommerce operators to understand their customers and identify new trends better than ever.

In an insight from Accenture, they write, “AI systems can explore highly complex and varied options for customer engagement very quickly, and continuously optimize their performance as more data becomes available. This means marketers can set parameters and allow the AI to optimize and learn to achieve precision.”

According to a report from Emerging Tech Brew, “Machine learning’s predictive powers shine in logistics, helping to forecast transit times, demand levels, and shipment delays.” 

Smart logistics or intelligent logistics, is all about using real-time information through sensors, RFID tags, and the like, for inventory management and to better forecast demand. Machine learning systems become smarter over time to build better predictions for their supply chain and logistics functions.

Particularly in a world during and after COVID-19, you’ll want to plan your inventory on both real-time and historical data. Artificial intelligence can help you do just that. A recent McKinsey report suggests that investment in real-time customer analytics will continue to be important to monitor and react to shifts in consumer demand that can be harnessed for price optimization or targeted marketing.

It’s always tempting to jump into new, exciting technologies. But you’ll want to have a roadmap before jumping into implementing a new program, to make sure you don’t lose a lot of time and money on false starts.

You have to start somewhere — and your strategy will lay out the path you need to take from there to your AI goal. Don’t just punt this to a newly hired AI expert or your CIO or CTO. 

Really put some thought into what you want to accomplish with AI. Take a practical approach, and don’t forget to start small. You can always build on your successes down the road.

The most successful AI use cases live at the intersection of business objectives, data differentiation, and readily available artificial intelligence models. All that to say — you should focus on revenue-generating opportunities where you have a data advantage and in a context appropriate for proven AI technology.

Even if you’re an armchair AI aficionado, you’ll want to accept expert assistance on this one. Bring in a tiger team on a project or part-time basis to dig in and help you build a strategic AI roadmap. Those third parties can be helpful in bringing your MVP (minimum viable product) to life as well.

Once you’re confident in what your team has produced, it’s time to build the full scale solution. Don’t be surprised if it still takes some iterations before it works like you expect. As you and your team become more comfortable working in the realm of AI, you’ll start to see greater benefit from the projects you implement.

Tomorrow’s AI sounds like it’s straight from the movies, but there’s plenty of AI technology today that may look less glamorous improving customer experience, increasing conversion rates, and helping to streamline the way the business is run.

If you want to deliver the best possible shopping experience on your ecommerce website, look into the various benefits of artificial intelligence and machine learning. It can help you make better use of your customer and business data to set a plan for your future that will work.