How Leaders Are Navigating AI in Ecommerce

What is the most common use case for generative AI in ecommerce? Writing product descriptions. This is especially beneficial for businesses with large catalogs or technical, complex products. Although AI-powered product recommendations have been part of the online shopping experience for a long time, generative AI adds even more nuance and makes the entire process feel more bespoke. Generative AI allows better targeting and more refined personalisation, helping you create relevant experiences faster and with more context. AI even allows you to create dynamic product descriptions tailored to each customer’s unique preferences and pain points.

The best AI platforms offer highly relevant personalisation at the individual level without having to create a separate model for each customer. Even better? By incorporating user feedback, AI-based recommendations and personalisation become smarter over time, leading to increased conversions and higher customer satisfaction.

In brick-and-mortar stores, sales and service agents are your biggest asset. They’re able to pick up on cues from customers as they shop and suggest appropriate products. Thanks to generative AI, this can happen online, too. Chatbots have been a part of online shopping for years, but they never had the kind of conversational power that could really enhance the customer experience in an effective way. Those days are over. Now, digital concierges can process natural language and image-based prompts, generate tailored answers, and engage in data-driven interactions. This enhances multiple aspects of the customer journey.

Product discovery: AI-powered concierges are particularly helpful when it comes to product search discovery. Most businesses (82%) using AI for commerce report at least moderate levels of improvement to product discovery. Consider a shopper looking to recreate one of their favourite celebrity’s recent outfits. Instead of aimlessly browsing through product listing pages, they can simply upload a photo of the famed fashionista and ask AI to recommend similar products. Bespoke experiences like this can also open new doors to customer loyalty and retention.

Customer service: Chatbots have always been able to handle the most basic customer inquiries, like “Where’s my order?” or “What’s your return policy?” But as AI advances, digital copilots can handle increasingly complex interactions. For example, a copilot trained on your product details can answer specific questions about an item’s specifications and unique attributes. They can also suggest related and secondary items during conversations with shoppers, like batteries, chargers, and other products that will enhance the post-purchase user experience.

Shopping just got a lot easier — and much more entertaining.

Whether you’re a merchandiser, marketer, designer, or developer, generative AI can help you save time. In fact, commerce professionals using AI estimate it saves them an average of 6.4 hours per week. Businesses can automate routine tasks and increase sales with GPT-powered product descriptions, smart promotions, and more. Time-intensive tasks that once required manual configuration, like creating new promotions, can be automated at scale. And generative coding can help teams innovate faster.

Now, tools like generative page designers allow users of all skill levels to design webpages in seconds with simple, conversational building capabilities. AI can also uncover insights and make recommendations to help teams reach strategic goals. Want to clear out dead stock and make way for new merchandise? Improve your abandoned cart strategy? Generative AI can suggest promotions, price points, and marketing messages to help you achieve your goal. Need to boost average order value? AI insights can recommend proven strategies that can increase add-to-carts and improve revenue.

Expedited shipping, self-service order tracking, and easy returns have become table stakes in ecommerce technology. Now, generative AI will bring a new wave of optimisation to inventory and order management.

For example, inventory managers can train AI on returns reports and customer reviews to fine-tune product descriptions and decrease return rates. Route managers can use AI to map out more sustainable delivery routes. And operations teams can have AI analyse shipping and fulfillment data to determine more efficient and cost-effective ways to source and ship items. This is especially useful considering that shipping costs, sustainability concerns, and inefficient order routing are top business concerns.

For all the benefits of AI, there are certain roadblocks that keep businesses from realising its full potential.

Your AI is only as good as the quality of your data. A majority (70%) of commerce leaders say that poor data integration and harmonisation is at least a moderate pain point on the road to AI implementation. To reap the benefits of AI in commerce, make sure all your company’s data is in one consistent format. This is known as “data harmonisation”. Once your data is harmonised, it can be used to fine-tune an existing large language model (LLM) — an AI algorithm that uses deep-learning techniques and large datasets to understand, generate, and predict new content — to enable generative intelligence.

The best AI platforms will let you deploy your business’s transactional, product, order, fulfillment, and other commerce data — along with your customer relationship management software (CRM) and any third-party data — to get a 360-degree view of your customer. And they’ll do it while ensuring strict data security and privacy controls. That data will then provide opportunities for automation and growth, personalisation, and actionable insights.

Maintaining customer trust is critical. Only 17% of customers fully trust companies to use their data responsibly, and a mere 13% fully trust companies to use AI ethically. This means organisations must be transparent about data collection and how they use it in business operations. To do that successfully, companies will need to develop ethical standards around their use of AI.

You’ll need to answer tough questions like: How do you ensure sensitive data is anonymised? How will you monitor accuracy and audit for bias, toxicity, or hallucinations? These should all be considerations as you choose AI partners and develop your code of conduct and governance principles.

Generative AI in ecommerce is still an emerging field, but early adopters are already seeing benefits in time savings, customer satisfaction, and revenue gains.

For customers, a tailored experience increases shopper loyalty and enhances your brand’s reputation. By replacing search with a conversation — something customers still want — AI’s predictive intelligence guides customers to products they’re likely to enjoy, and relieves them from sorting through a jumble of search results. In fact, 69% of customers are open to using AI to improve their experiences.

For businesses, generative AI technology can make teams more productive in product and content development, allowing them to focus on more strategic work and roll out innovations faster. And the added business insights from vast amounts of data can help you more deeply understand your customers.