Artificial intelligence is revolutionising how businesses operate, and the eCommerce industry is no different. Customers might not be able to ask ChatGPT to find the perfect product, choose the ideal size and make a purchase just yet. But retailers can leverage machine learning algorithms in multiple ways, from personalising the customer experience to eliminating tedious manual tasks.
In this article, we’ll explore what AI can (and can’t) do for the eCommerce industry, specific use cases your brand can implement today, and how AI may change online retail in the future. Let’s dive in.
What Are the Benefits of AI in eCommerce?
Artificial Intelligence (AI) offers a wealth of benefits to savvy retailers that implement the technology. By using AI, eCommerce businesses can automate processes, optimise customer experience, and increase revenue. Here are some of the key benefits of AI in eCommerce:
Next-Level Personalisation
Unrivalled personalisation is one of the biggest benefits of using Artificial Intelligence in eCommerce. AI algorithms can analyse customer data (things like past purchases, browsing history, and demographic) to provide personalised product recommendations.
Sure, your current eCommerce store may be able to provide product recommendations, but that’s usually limited to products the customer has previously looked at or products other customers have looked at. AI promises to deliver hyper-personalised recommendations that increase customer satisfaction and encourage bigger purchases. Even today, product recommendations have been found to account for up to 31% of eCommerce revenue.
Improved Search Results
Don’t you hate when you search for a query on an eCommerce store and the site returns a long list of irrelevant products? With AI, that is becoming a thing of the past.
AI-powered search engines can provide more accurate and relevant search results to customers. By analysing customer search queries and purchase history, AI algorithms can understand customer intent and provide results that match their preferences.
An Online Personal Shopping Experience
The concept of a personal shopper doesn’t have to be limited to high-end department stores. AI can enhance the customer experience by providing personalised customer service to every visitor.
Chatbots powered by AI can handle customer queries and provide instant solutions, leading to faster response times and increased customer satisfaction. AI can also analyse customer feedback and provide insights to businesses to improve their products and services. This leads to increased customer loyalty and retention.
Optimised Inventory Management
AI can enhance back-end operations, too. It can help businesses optimise their inventory management by predicting demand and automating restocking processes. By analysing customer data, AI algorithms can predict which products are likely to sell and when, allowing businesses to stock up accordingly. This leads to reduced inventory costs and increased revenue.
What Are the Challenges of AI in eCommerce?
AI isn’t perfect. Before the industry gets carried away with AI for eCommerce, several hurdles need to be overcome.
Data Privacy and Security
One of the main challenges of AI in eCommerce is data privacy and security. As AI algorithms rely on vast amounts of data to learn and make predictions, protecting customer data becomes critical. Brands must ensure that customer data is collected, stored, and processed securely to prevent data breaches and cyberattacks — this is particularly important for any businesses operating in a country governed by GDPR.
Moreover, with the increasing use of AI-powered chatbots and voice assistants, there is a risk of sensitive customer information being shared with unauthorised third parties. Brands must implement robust data privacy policies and security measures to safeguard customer data and build trust with their customers.
Cost
The cost of implementing eCommerce AI solutions can be prohibitive. Developing and deploying AI algorithms requires significant investment in technology, infrastructure, and talent. Small and medium-sized eCommerce businesses may find it challenging to justify the cost.
Moreover, AI algorithms require continuous monitoring and maintenance, which can add to the overall cost of implementation. Retailers must carefully evaluate the cost-benefit of AI solutions and choose the ones that provide the most significant value for their business.
Integration
Integrating AI solutions with existing eCommerce platforms and systems can also be a challenge. Retailers may need to modify their existing systems and processes to accommodate AI algorithms, which can be time-consuming and costly. Moreover, integrating AI solutions with legacy systems and platforms can be challenging due to compatibility issues.
Examples of AI in eCommerce
There are plenty of examples of eCommerce AI solutions that already exist. Here are some of the most popular:
Chatbots
Chatbots are one of the most common examples of AI in eCommerce. They provide customers with quick and efficient responses to their queries any time of the day or night, which improves customer satisfaction and reduces the workload of customer service reps. They can also be used to provide personalised recommendations to customers based on their preferences and past interactions with the website.
This is exactly the kind of AI we use in the Pro Carrier Portal. While our account managers are always on-hand to offer advice, we recognise that it’s often faster and easier to speak to a chatbot. The Pro Carrier Portal chatbot can help you with Where Is My Order (WISMO) queries, check HS codes and look up invoices.
Recommendation Engines
Recommendation engines are another popular application of AI in eCommerce. They use machine learning algorithms to analyse customer data and provide personalised product recommendations. This helps online retailers increase their sales by suggesting relevant products that customers are more likely to buy. Recommendation engines also help customers discover new products.
Visual Search
Visual search is an emerging application of AI in eCommerce. It allows customers to search for products by uploading an image or taking a photo with their smartphone. The AI algorithm analyses the image and provides results that match the visual characteristics of the product. This makes it easier for customers to find the products that they are looking for, even if they don't know the name or description of the product.
Predictive Analytics
Predictive analytics is a powerful tool that uses AI algorithms to analyse customer data and predict future customer behaviour. This can help brands make data-driven decisions about inventory management, pricing, and marketing strategies.
By analysing customer data, predictive analytics can identify trends and patterns that may not be visible to the human eye. This allows eCommerce brands to stay ahead of the competition and improve their bottom line.
Build the Future Yourself or Buy a Solution?
The impact of AI on eCommerce is undeniable. It won’t be long before every retailer realises that incorporating AI solutions in their eCommerce strategy can help them personalise their offerings, optimise their operations, and enhance their customer experience.
As the demand for AI solutions continues to grow, retailers are faced with a critical decision of whether to build the future themselves or buy a ready-made solution from a SaaS provider. While building a tailor-made solution may provide a competitive advantage, it requires significant investments in expertise, infrastructure, and resources.
Alternatively, buying a solution from a provider may offer immediate benefits, flexibility, and reduced risk, but with less control over the solution. Ultimately, the choice between building or buying an AI solution depends on a retailer's goals, resources, and priorities. Regardless of the option chosen, embracing AI technology in eCommerce is a necessary step for retailers to stay competitive and thrive in the digital era.
To find out more about how Pro Carrier can help you get started on the path to eCommerce AI, speak to an expert.
