AI in E-commerce: Reshaping Every Stage of Customer Journey

As technologies evolve, the dynamic relationship between customers and businesses is also facilitated with the aid of technologies, one of which is AI. With a projected market value of 2.1 billion USD by 2032, AI is set to reshape the way businesses engage with consumers. Establishing its presence throughout 6 stages of the customer journey from awareness to customer retention, AI offers various opportunities to unlock future growth for the e-commerce industry. 

1. Awareness

The awareness stage in the customer journey is a pivotal point where potential customers first become familiar with a product or service. As businesses aim to engage with a broad customer base, content is the primary point of interaction. However, creating diverse and compelling content can prove to be time-intensive. 

Here, generative AI steps in to streamline the efforts of content creators. When prompted to create a blog post, AI can generate general ideas and outlines and make suggestions for improvement to provide content creators with a comprehensive outcome. 

In addition, AI also plays a crucial role in helping businesses stay updated with evolving SEO techniques. Enterprises can finetune their content by harnessing its capabilities to seamlessly align with search engine algorithms. This strategic approach enhances online visibility and elevates search engine results page rankings (SERPs). 

As a result, when customers look up products online, the business will emerge prominently among the first search results. The integration of AI ensures that the content resonates with search engine criteria, enabling brands to capture the audience’s attention and solidify their online presence.

2. Interest

At the second stage of the customer journey, customers would want to discover more about the product and service offerings. AI plays a crucial role in this phase by analyzing customers’ browsing history, past purchases, and interactions. This deep understanding enables AI to generate dynamic and up-to-the-minute product recommendations tailored to individual customer needs. Implementing AI can significantly enhance the customer experience, increasing the likelihood of a successful first purchase. 

AI can prompt customer purchase with personalization

AI can prompt customer purchase with personalization.

AI can help companies incorporate collaborative filtering techniques. This strategy means AI identifies customers with similar buying patterns, preferences, or demographics and recommends products that have appealed to others in the same cohort. Therefore, customers are exposed to items they might not have discovered on their own but are likely to find appealing based on the behavior of similar shoppers. 

For instance, Amazon utilizes generative AI algorithms to analyze vast customer data and deliver personalization. As 35% of consumer purchases on Amazon result from product recommendations, this capability enables AI to dynamically adapt to each customer’s preferences and ensure a seamless shopping experience.  

3. Consideration

In the third stage of the customer journey, customers usually read reviews and evaluate different buying options before reaching a decision. To remain competitive, brands can utilize AI to adjust the prices with dynamic pricing. By analyzing influencing factors such as seasonality, economic conditions, and other variables, AI dynamically adjusts prices to optimize them during fluctuations in demand. 

This agile pricing strategy ensures businesses stay responsive to market dynamics, maximize revenue during high-demand periods, and adjust prices during slowdowns. Amazon, for example, changes its product prices 2.5 million times a day with a vast store of data to optimize prices and increase its profits. 

4. Purchase

AI can significantly contribute to effective cross-selling and up-selling strategies. By analyzing customers’ purchase behaviors, AI algorithms can suggest complementary products that complement their initial purchase. AI-driven upselling uses machine learning algorithms to predict what products or services a customer is most likely to be interested in and recommends at the right time, resulting in increased revenue and customer satisfaction. Specifically, upselling techniques can increase revenue by 10% to 30%and upsells are 68% more affordable than acquiring a new customer.

For instance, L'Oréal successfully harnessed a specialized AI tool to customize their upselling and marketing efforts. By analyzing customer behaviors and product visuals, the AI solution provides personalized product recommendations that cater to shoppers’ unique preferences. The brand not only automated product tagging with AI but also delivered personalized pop-ups. With this AI tool, L'Oréal witnessed substantial improvement in key performance metrics, with an impressive 140% increase in conversion rates and a notable 109% increase in average order value.

5. Post-purchase

AI-powered chatbots play a crucial role in the post-purchase stage by providing dynamic and context-aware responses. Traditionally, chatbots were limited to a rule-based system that restricted communication to default answers. As traditional chatbots cannot go beyond simple interactions, AI-powered chatbots such as ChatGPT or Bing AI are a new generation of conversational AI that can understand and respond to various user inputs. 

Conversational AI chatbots can provide personalized assistance

Conversational AI chatbots such as ChatGPT can provide personalized assistance. 

After making the purchase, customers may have inquiries about the products. Conversational AI chatbots can offer personalized assistance and recommendations, ensuring that each interaction addresses specific concerns. Furthermore, AI-powered chatbots can provide detailed and accurate product specifications and usage guidelines. With 54% of companies using some form of chatbot or other conversational AI platform for customer-facing applications, customers can have comprehensive product information at their fingertips to foster confidence in their purchase decisions. 

6. Customer retention

In the last stage of the customer journey, businesses need to devise strategies to retain customers. Indeed, customer feedback analysis is a useful strategy since they can identify areas for improvement in their products and services. However, extracting insights from customer interactions using traditional analytics methods and tools is time-consuming and resource-intensive. By leveraging AI, customer journey analytics allows brands to sift through a much larger and complex data space.

Using AI to analyze customer reviews can be a useful strategy

Using AI to analyze customer reviews can be a useful strategy. 

Notably, Amazon effectively utilizes AI-powered feedback analysis to comprehend customer preferences in the e-commerce landscape. With 93% of online shoppers considering verified purchase reviews influential in their decision-making, Amazon's vast data is navigated using AI to address common customers’ pain points. By identifying specific emotions such as joy or frustration, Amazon can gain a nuanced understanding of customer opinions to help merchants refine their products.

Reshaping customer journey with AI in e-commerce

Understanding the customer journey stages can unlock significant value for e-commerce businesses seeking to refine their marketing efforts and customer service. Thus, AI provides a practical means for achieving these optimizations. With a substantial 270% growth in adoption over the past four years, AI offers a pathway for e-commerce companies to stay adaptable in the e-commerce landscape, enhance customer loyalty, and foster revenue growth.

Author Tuan Minh Tran