How AI Shopping is Transforming the Way We Buy Online

In digital spaces, artificial intelligence (AI) can influence and optimize every action a shopper takes. At the center of this story is personalization, which connects shoppers with relevant content, offers, messaging, and products throughout the buying journey. AI shopping—a data-driven, customized, and highly relevant digital shopping experience—is now the default expectation for many consumers.

In a recent BCG survey of 5000 global consumers, 80% of respondents made this point crystal clear, saying they “want and expect” personalized experiences. Brands are seeing tangible results from AI applications, according to McKinsey, with many organizations reporting a measurable business impact from AI adoption.

To deliver an exceptional AI shopping experience, retailers must tie AI-powered capabilities like personalized product recommendations and smart shopping assistants to the digital buying journey. AI shopping enhances customer experience, boosts sales, and keeps customers engaged along their entire buying journey.

4 Steps to Building a Flawless AI Shopping Journey

Since AI potentially touches every part of the digital buying journey, it can be challenging for retailers to know where or how to implement it. At Monetate, we work with retailers to craft effective AI shopping experiences that deliver measurable results and we have a few tips to get the AI shopping ball rolling.

Here are four steps you can take to start building an exceptional AI shopping journey for your customers.

🗺️1. Map The Journey with AI and Analytics

Creating an AI shopping journey that resonates with customers requires deep knowledge of how people move through the online buying process. For your first step, focus on mapping the journey. After all, you can’t improve what you don’t understand.

Journey analytics tools use AI and machine learning to reveal how visitors navigate from first click to purchase, identifying what’s working and (perhaps more importantly) what isn’t.

By processing huge amounts of data, AI uncovers patterns humans might miss like which product categories typically lead to cart abandonment or which search terms correlate with higher conversion rates.

The most effective journey-mapping approach combines multiple data sources including:

•   Behavioral analytics: Track how customers interact with your site, incorporating metrics like click patterns, time spent on pages, and navigation paths.

•   Customer feedback: Use survey data and social listening to understand the “why” behind customer actions

•   Audience segmentation: Use AI to automatically group shoppers into segments based on behavior, revealing distinct customer types with different needs—this information can then be used to target and personalize experiences for these identified segments.

Data-backed journey mapping becomes the foundation of the AI shopping journey you create. It clarifies how to address actual customer needs rather than wasting time on ineffective strategies.

🚪2. AI Search is Your Digital Front Door

Search is where most customer shopping journeys begin, particularly when they reach a retailer’s website. Nearly 70% of shoppers will head straight for the search bar as their first step in product discovery.

AI-powered personalized search uses natural language processing (NLP), data, and machine learning to understand the intent of a user’s search. It makes finding the perfect product much more successful for shoppers than lexical (keyword)-based search alone. Here’s how:

• By interpreting natural language queries, AI makes search simpler for users and much more relevant. It can, for example, recognize synonyms, account for misspellings, and connect shoppers with relevant products, even if they aren’t an exact match to a specific query.

• Thanks to machine learning, AI search systems learn from each interaction, so results become increasingly relevant.

• AI search can prioritize the way results appear—displaying the most relevant results at the top of the page based on the context of the searcher and the query, but also based on what’s important for the merchandising team (e.g., unloading excess inventory, highlighting a hot new product, etc.)

The most effective AI search solutions also incorporate visual search capabilities. For example, allowing customers to upload images to find similar products. AI search bridges the gap between inspiration and purchase. It’s a more intuitive and natural shopping experience that mirrors how people naturally discover products.

🤖3. Use AI to Automate and Scale Personalization

AI makes it possible to dispense with the manual, time-consuming tasks once required to personalize digital experiences. Ecommerce personalization platforms like Monetate use machine learning algorithms to analyze and learn from customer behavior patterns. This is fundamentally how personalization technology can deliver individualized experiences that scale as your company—and product catalog—grow.

Office Depot, a leading US office supply retailer, saw tremendous success when they implemented Monetate’s AI-driven personalization to customize product detail pages (PDPs). Office Depot took an automated personalization approach to dynamically determine what type of content appeared first on a PDP, customizing these pages based on individualized visitor behavior data. They generated nearly $7 million in revenue in four months.

Focusing on PDPs as a key area for personalization is a great example of retailers can start with one aspect of the buying journey and still see immediate results. There’s tremendous opportunity to customize content as an individual shopper moves through a website—on the home page, the search bar, the PDPs, the shopping cart, and even after a purchase is complete.

🛍️4. Use AI Shopping Assistants & Chatbots for Enhanced Customer Support

AI shopping assistants and chatbots complement the AI shopping journey by acting as digital concierges, helping customers discover products and find information quickly. They supplement other AI shopping capabilities like intelligent search and tailored product recommendations.

AI chatbots improve customer experience by delivering unique content to visitors who interact with them in the flow of the shopping journey. They can answer product questions, suggest complementary items based on browsing history, and guide customers through complex purchasing decisions.

Chatbots work in harmony with other AI shopping capabilities, using customer data to create consistent experiences. Many large retailers are embracing AI shopping agents to help digital shoppers with support issues and connect them with the right products.

For example, Best Buy recently partnered with Google Cloud and Accenture to use a GenAI-powered chatbot for personalized customer support. This self-service support option is available on Best Buy’s website and app. Per Best Buy’s website, “This assistant will help customers quickly troubleshoot product issues, make changes to their order delivery and scheduling, and even manage their software and Geek Squad subscription.”

The Future of AI Shopping

AI shopping remains a relatively new technology. The tools that facilitate it are evolving regularly and there are some exciting trends poised to transform the way shoppers experience online buying. Innovative AI capabilities promise to make the online buying journey even more customized and tailored to individuals and include:

1. Augmented Reality (AR) shopping

Augmented reality (AR) capabilities like virtual try-ons and product visualization allow customers to see how a product on a screen might look in their physical spaces (or on their bodies) before purchasing. In the future, it’s possible that shoppers will interact with AR-powered ads that where they can virtually try products like clothing and makeup and VR storefronts promise to “gamify” shopping, making it immersive and incredibly interactive.

2. Dynamic pricing

Sophisticated dynamic pricing algorithms already exist but will become more ubiquitous over the next few years. Dynamic pricing uses AI to adjust prices in real-time based on various signals like manufacturing cost, demand, competition, and customer behavior. Big retailers and marketplaces are already doing this.

Amazon, which has been using AI to dynamically update prices  millions of times daily since 2018, recently announced their Automate Pricing Tool for sellers which lets sellers set pricing rules or used predefined rules to automate price adjustments based on their goals (e.g., staying competitive, improving sales, etc.)

3. Integrated AI shopping assistants

Beyond basic chatbots, AI assistants are evolving to provide personalized guidance throughout the customer journey. Best Buy’s implementation with Google Cloud demonstrates how these abilities can troubleshoot product issues and manage orders seamlessly.

4. Enhanced security and fraud prevention

As AI shopping becomes more connected to the shopping journey, retailers are incorporating it to improve security and fraud detection. AI tools analyze user behavior and transaction patterns to detect and prevent fraud before it happens. They can identify unusual purchase behavior, sudden changes in account details, and other suspicious activities. AI also enhances security through biometric authentication methods like face recognition and fingerprint scanning.