6 ways generative AI transforms eCommerce personalization

Personalization was a game-changer for eCommerce businesses that chose early adoption. It helped them distinguish their online businesses from their competitors, capitalizing on the ability of the eCommerce sites to gather and analyze vast amounts of customer data and tailor experiences to customers.

eCommerce personalization kickstarted innovation in the form of product recommendations and user segmentation that enabled limited customization of content and discounts to match the collective preferences of each customer segment. While this level of personalization made customers feel valued, the novelty factor waned away, and eCommerce personalization became the norm, leading to market saturation, convergence of strategies, and erosion of the competitive edge.

However, the advent of artificial intelligence (AI) has rekindled innovation, unlocking new possibilities for hyper-personalization that were not possible before. By leveraging AI and hyper-personalization, online stores can once again distinguish themselves in a crowded market, offering a shopping experience that is not only personalized but also predictive, proactive, and deeply engaging.

So, how did traditional eCommerce personalization differ from AI personalization?

AI personalization differs from conventional eCommerce personalization in the following ways.

Traditional eCommerce Personalization	AI Personalization
Achieves personalization through rigid categorisation of customer groups based on search and purchase history and customer behavior	Analyzes vast and complex datasets in real time to create highly individualized shopping experiences
Reads customer preferences and behavior and reacts by offering personalization	Predicts customer preferences with remarkable accuracy using advanced algorithms and machine learning models
Slow, rigid product recommendations, reacting to changes in customer activity and behavior	Works in real time, creating new possibilities such as constantly varying product recommendations according to the most recent customer behavior
Limited content customization to customer segments	Hyperpersonalized AI content generation at scale to cater to individual customers
Slow and error-prone manual content creation	Automated, AI-powered, personalized content generation at scale
Limited data depth and visibility and analytical capabilities	Real-time data visibility, continuous learning from data and enhancing predictability and strategy optimization
Limited personalization capabilities in a saturated eCommerce market	New possibilities and innovations, such as dynamic pricing, personalized product descriptions, visual elements, email marketing, etc., tailored to constantly evolving individual preferences

6 Ways AI Enhances eCommerce Personalization Capabilities

1. Hyper-personalized Product Recommendations

AI-powered personalization leverages advanced machine learning algorithms to continuously analyze customer data and the constantly evolving customer preferences to anticipate what the customers need at any given time and proactively provide highly personalized product recommendations on the eCommerce site.

The AI tools for personalization on eCommerce platforms achieve this level of personalization by continuously reading and learning from browsing patterns, search history, past purchases, and real-time customer behavior on the site, including interactions with various elements of the eCommerce site, customer support interactions, writing or reading product reviews, adding products to wishlist, etc. It ensures the relevance and timeliness of tailored product recommendations, significantly improving customer engagement and sales conversion.

2. Dynamic Pricing for Personalized Offers

Fixed pricing of products leaves so many opportunities unseized, impacting both the eCommerce businesses and the customers.

For instance, if the demand for a product is too high at a specific time, like air conditioners during summer months, businesses need to adjust the price of that product based on demand and availability to keep in line with the market trend; otherwise, it would result in reduced profitability.

On the other hand, sometimes businesses may need to chase a lower price to attract customers, especially when the availability of products in the market against the demand is high. For instance, light strips for decoration may sell in great numbers during the holiday season, and the market would be flooded with similar offerings. At that time, lower prices can make a difference in sales.

At the same time, businesses must reward long-term customers for their loyalty by offering exclusive discounts and special prices. So, eCommerce businesses need to adjust the pricing according to the demand and supply and personalize the pricing according to various parameters like Customer Lifetime Value.

AI tools enable eCommerce personalization in pricing through dynamic pricing strategies. AI algorithms continuously read customer behavior, observe fluctuating market trends, and monitor competitor pricing in real time. They adjust the prices of the products dynamically based on the changes in these parameters.

Dynamic pricing enables personalized pricing, exclusive deals and offers, and special discounts for every customer according to their average customer value and average bill value, incentivizing them to complete the purchase and rewarding them for their loyalty. 

3. AI-powered chatbots for Personalized Customer Support

Automated chat interfaces of the past consisted of just a set of pre-programmed tasks and replies to frequently asked queries. They lacked the human element required to solve more complex problems, and the scope of customer support was limited.

With AI-powered chatbots, eCommerce businesses can drastically improve the scope of automated customer support and enable highly personalized responses. They use natural language processing (NLP) and sentiment analysis to understand and personalize the responses to customer inquiries.

For instance, they can infer the customer names from the data and address them by name, provide shopping assistance by anticipating their needs based on the data, thus simulating a salesperson, and personalize product recommendations based on their latest preferences and real-time interaction. They can even assist customers in completing purchases.

4. Personalized Content Creation with Generative AI

Content on your eCommerce site, including but not limited to product descriptions, images, videos, interactive AR/VR content, and knowledge resources, helps customers make purchase decisions. Traditional eCommerce personalization was limited to customized email marketing to broad customer segments. So, there is enormous room for tweaking all other types of content, narrowing them further down to the individual level.

Generative AI has opened new avenues in eCommerce personalization by automating the generation of personalized content at scale, catering to the interests of every customer. AI-powered personalization tools can:

• Automatically generate hyper-personalized marketing messages, product descriptions, and even visuals at scale that resonate with individual customers. 
• Create text content and knowledge resources that speak directly to the preferences and needs of each shopper. 
• Personalize the looks and design elements of the website itself to make the eCommerce site appealing to every user at any given time and context.
• Create customized email campaigns with personalized subject lines and body text that resonate with the constantly changing preferences and product interests of individual users, increasing open and click-through rates.
• Create personalized landing pages that adapt to the customer’s behavior, showcasing the most relevant products and offers.
• Automate personalized content generation for social media, targeting specific, narrow subsets of various customer segments.
• Generate real-time, personalized deals, offers, and discounts based on a customer’s behavior.

5. Mobile Personalization through AI-Powered Push Notifications

While accessing an eCommerce site on mobile through a browser or a dedicated app can enhance the customer experience and convenience massively, it is nothing more than a simplified mobile version of the desktop site. These mobile platforms have a lot more potential than that, and AI personalization unlocks it.

For example, AI tools use machine learning to track and analyze customer interactions with notifications, learn the pattern of mobile usage, and identify the exact time when the customer interacts with the mobile and the notifications the most. With these insights, eCommerce businesses can identify the right time to communicate with the user and send exclusive, personalized communication such as time-bound deals, special offers, product recommendations, or reminders.

It ensures push notifications are relevant and timely, thus improving engagement, incentivizing customers to interact with the notifications and the app, and increasing the chances of a purchase.

6. Personalized Omnichannel Experiences

The customer journey is not limited to eCommerce websites. These days, it also extends to various channels, as users increasingly browse in one channel and resume where they left off on another channel. It creates room for inconsistency in customer experience, and difficulty in tracking customer behavior across channels and providing a uniformly personalized experience in various channels.

AI-driven personalization addresses this issue by integrating with various touchpoints across multiple channels, including websites, mobile apps, social media, and messaging platforms, and creating a seamless omnichannel shopping experience. It enables uniform personalization and customer experience across channels.

For instance, you may see the same ad from a company on Google ads, Facebook, Instagram, Twitter, and other platforms during the same period. It points to AI-driven personalization across channels.

Unlocking New Personalization Possibilities with Artificial Intelligence and Machine Learning

AI has been transforming the eCommerce shopping experience in many ways. However, what we have achieved with these cutting-edge technologies so far in eCommerce personalization is nothing compared to the future possibilities. 

FAQs

1. How is generative AI used in eCommerce?

Generative AI in eCommerce automates personalized content creation, such as product descriptions, email campaigns, social media content, product images, videos, and visuals.

2. How is AI used for personalization? 

AI personalizes the eCommerce experience by analyzing customer data to deliver tailored product recommendations, dynamic pricing, and personalized content. 

3. What are the advantages of AI in personalized shopping? 

AI enhances personalized shopping by delivering tailored experiences. AI-driven strategies improve customer engagement, increase sales, and foster loyalty by making the shopping experience more relevant and enjoyable for every customer.

4. What is an example of personalization in eCommerce? 

An example of personalization in eCommerce is AI-powered product recommendations.