Introduction

In today’s competitive ecommerce landscape, delivering personalized experiences to customers has become crucial for success. Customers expect brands to understand their unique needs and preferences and provide tailored experiences across touchpoints and channels in real-time. However, many companies struggle to deliver one-to-one personalization at scale.

This is where artificial intelligence (AI) comes into play. By leveraging AI and machine learning (ML) models, ecommerce merchants can not only meet customer expectations but also drive significant results for their business. In this blog post, we will explore five techniques that utilize the power of AI to implement personalized shopping experiences at scale. With this knowledge, merchants can develop their own AI strategy and seek out solutions that are most relevant to their business.

Section 1: Using AI to Segment Customers

At the core of personalization is the ability to use customer data to create tailored experiences. Traditionally, ecommerce merchants have relied on basic demographic data and limited behavioral data to manually segment their customers. However, this process is slow, lacks granularity for hyper-personalized experiences, and may not consider other valuable data types such as real-time behavioral or transactional data.

AI can revolutionize the way merchants segment their customers by easily identifying valuable segments without involving data analytics teams. By feeding customer behavioral data, ecommerce data, and data from other sources into AI models, merchants can generate propensity scores that indicate a customer’s likelihood of taking certain actions in the future. These scores can then be used to create powerful segments such as “high propensity to churn” or “high propensity for complementary products.”

Automating segment qualification in real time is another benefit of using AI in segmentation. Instead of relying on static segments, personalization leaders often shift customers from one segment to another based on real-time behaviors. For example, if a customer suddenly starts browsing women’s categories after only shopping in men’s categories, they can be automatically added to a “women’s gifts” segment and receive a different site experience during that browsing session.

Section 2: AI for Facilitating Product Discovery

When customers visit an ecommerce site, merchants have only seconds to present the most relevant products to them. AI can play a crucial role in optimizing product discovery through three key opportunities: site search, category browsing, and product recommendations.

AI-powered search solutions enhance the search experience by providing suggestions as customers type, handling typos, and offering synonyms. Furthermore, these solutions can use shoppers’ behavioral actions on the site to deliver the most relevant products. For example, if a shopper spends time in the running gear section and then searches for “pants,” AI algorithms can re-rank search results to prioritize running pants over denim pants for that particular shopper.

Browsing experiences can also be personalized using AI. Instead of relying on manual merchandising, which often lacks dynamic capabilities, AI can dynamically re-rank products based on customer-specific behaviors. Additionally, ecommerce site navigation can be personalized based on a shopper’s category affinities. For example, if a shopper predominantly looks at women’s categories, those categories can be positioned first in navigation menus.

Product recommendations are another valuable tool for facilitating product discovery. Leveraging segmentation and propensity scores allows merchants to deliver highly relevant product recommendations based on each shopper’s behavior. This not only improves conversion rates but also enhances the overall customer experience.

Section 3: Creating Personalized Content with AI

Content plays a pivotal role in creating a unique brand experience on ecommerce sites. However, creating personalized content manually can be time-consuming and complex, especially as businesses grow and need content variations for different screens, channels, regions, and brands.

AI-powered solutions automate manual content workflows by supporting asset management tasks such as creating new assets, tagging existing assets, producing variations by size or context, and assembling modular content for personalization. These solutions can remove backgrounds, replace objects, cut out pieces of existing images, and even create 3D models of products without the need for lengthy photoshoots. AI also helps in tagging assets efficiently, making them easier to find and deploy on ecommerce sites.

Section 4: Delivering and Optimizing Personalized Content and Promotions with AI

To drive engagement and conversion, it’s essential to allocate the right content, promotions, and messaging to the right customers. This is where AI can be a powerful tool in personalization.

AI allows merchants to dynamically adjust what content is shown based on real-time behavioral and profile data. By adapting content to a shopper’s current context, brands can ensure relevance and prevent shoppers from clicking away due to irrelevant content.

Personalizing promotions is another area where AI excels. Instead of offering discounts to all customers or large subsets of shoppers, AI can suggest promotional offers tailored to each visitor based on their profile and behavioral data. This not only maximizes conversion rates but also avoids training customers to wait for discounts before making a purchase.

Furthermore, AI-powered tools enable continuous optimization of personalized content and promotions over time. By testing different variations and automatically deploying the most effective ones, brands can continuously improve their customer experience and drive better results.

Section 5: Delivering the Next Best Interaction with AI

Beyond the ecommerce site experience, customers expect every interaction with brands to be personalized across various touchpoints. However, manual orchestration of these touchpoints without AI support often leads to fragmented and inconsistent customer experiences.

AI-powered tools can determine the next best experience for each customer by utilizing real-time data across channels and devices. By ranking messages based on individual preferences and adjusting rankings as customers engage with the brand, brands can deliver consistent personalized experiences throughout the customer lifecycle.

Additionally, AI can optimize interactions based on specific key performance indicators (KPIs) prioritized by the merchant, such as maximizing conversion rates or revenue. This ensures that every interaction with the customer is tailored to drive the desired business outcomes.

Conclusion

Delivering personalized experiences at scale may seem complex, but AI can simplify and enhance the process. By utilizing AI techniques such as segmentation, product discovery, content creation and optimization, personalized content, and promotions, and next-best interaction strategies, ecommerce merchants can provide unique and tailored experiences to their customers.

Kobe Digital offers powerful personalization tools that leverage AI capabilities across various aspects of ecommerce. By integrating these tools with existing technologies and data, merchants can transform their businesses and deliver exceptional customer experiences. With a clear AI strategy in place, merchants can meet customer expectations while driving significant results for their businesses.