The Transformative Role of AI in E-Commerce Strategies

The Impact of AI Tools on E-Commerce

The rise of AI tools is changing the way e-commerce works. More and more people are using generative AI, like ChatGPT, to search for, choose, and even buy products. This shift is affecting every part of the e-commerce marketing funnel. Retailers are also using AI to gather real-time data from the web. They use this data for things like dynamic pricing, forecasting demand, and managing inventory.

Retailers Need to Keep Up with Rapid Changes

These changes are happening fast, and e-commerce retailers must keep pace. Research shows that 67% of customers feel companies are not responding to their needs quickly enough. The busy shopping season in 2025, from Black Friday to the New Year, will be a big test for retailers. They will see how well they can use AI and meet customer needs.

Surge in Traffic from AI Tools

According to Adobe Analytics, traffic to retailers from AI tools like ChatGPT, Perplexity, and Claude increased by 1,200% from July 2024 to February 2025. A survey revealed that 23% of shoppers plan to use AI tools during the upcoming holiday season. Among younger shoppers, like Gen Z and millennials, that number rises to over 42%.

Rethinking Marketing and Content Strategies

With these developments, retailers must rethink their content, marketing, and sales strategies. A study by Bain found that a significant number of consumers now rely on zero-click results—meaning they get answers directly from AI without visiting a website—for 40% of their searches. This shift could lead to less traffic on retailers’ websites, but the conversion rates for those who do visit are higher.

Generative Engine Optimization (GEO)

While traditional search engine optimization (SEO) techniques are still important, generative AI is changing the game, leading to the rise of Generative Engine Optimization (GEO). GEO presents new challenges for e-commerce merchants. The large language models (LLMs) that power these AI tools assess the credibility and trustworthiness of brands. Retailers must work hard to build their reputation, particularly by getting reviews from respected sources.

Understanding Customer Queries with AI

Another challenge is that customers use different types of queries with generative AI tools. OpenAI reports that nearly half of all queries are in “asking” formats. For example, instead of searching for a “slim-fit pink shirt,” a customer might ask for “slim-fit pink shirts for business casual events.” Retailers need to adapt product descriptions accordingly. This can involve adding detailed FAQs to product pages to help AI crawlers match products to inquiries.

Digital Twins for Better Marketing

Interestingly, AI is also being used for content analysis. Researchers at Columbia Business School are using LLMs to create “digital twins” that represent shopper behavior. When a product is input, these twins mimic potential buyers, including their names, ages, and preferences. They then search on tools like ChatGPT to see how visible a product is. This information can help companies adjust their marketing strategies.

AI-Powered Data Collection in E-Commerce

The marketing funnel is just one aspect of e-commerce affected by AI. Business intelligence (BI), which involves collecting and analyzing data to improve operations, is also being transformed. For effective BI, e-commerce companies need reliable and up-to-date data, including external sources. AI has become crucial in collecting competitive data.

Streamlining Data Extraction

Collecting public web data, such as prices and product descriptions, has been essential in e-commerce for years. Now, AI is making this process easier. AI tools can be used with natural language, so no coding is needed. This saves engineers a lot of time. AI can also find suitable URLs for scraping, helping retailers gather data from competitors more efficiently.

Real-Time Demand Forecasting and Dynamic Pricing

With real-time data on competitor prices and inventory, retailers can adjust their offerings quickly. Dynamic pricing is a popular BI function; a recent survey showed that 61% of European retailers use it. However, fewer than 15% currently employ algorithms or AI for this purpose, indicating a significant opportunity. By using the latest data on pricing, LLMs can help retailers automatically adjust prices, especially during busy times like the holidays.

Forecasting Demand with AI

AI can analyze customer demand and stock levels to predict future needs. This capability can provide various benefits. For example, Deloitte Digital has noted that retailers can use AI to keep track of their inventory and place orders as needed. Additionally, AI can help analyze web data to gauge how a brand is perceived in the market.

Embracing Opportunities in E-Commerce

While AI is changing the e-commerce marketing funnel, it’s also creating new opportunities. Retailers can use AI to create GEO-optimized content, gather valuable real-time data, and make informed decisions about pricing and inventory. AI can also enhance customer support.

Thriving Amid Disruption

AI’s impact can be intimidating, especially for retailers during peak sales periods. However, those who embrace the changes and opportunities AI brings will not just survive; they can thrive in the new landscape of e-commerce.