How New AI Solutions for E-Commerce Are Enabling Customized Shopping

How New AI Solutions for E-Commerce Are Enabling Customized Shopping

AI solutions for e-commerce are reshaping the power of customized shopping experiences. Optimize your sales efficiency with powerful data-led strategies here.

Over 60% of Americans think that companies using AI will make life easier for many people. This Pew Research statistic reinforces the idea that we will see mass acceptance of this technology soon, especially as it can provide unique and personalized responses. So, what are some ways it improves the shopping experience in e-commerce spaces for every person? 

Below, we dig into how AI solutions for e-commerce businesses can drive improved personalization and what that means from the shopper’s perspective. Read on to discover how e-commerce artificial intelligence tools will drive a new era of sustainable growth in online sales and embrace the future of AI e-commerce today.

Exploring the Role of Machine Learning with E-Commerce AI

Machine learning algorithms can already process vast amounts of data to identify patterns. We have been developing detailed algorithms for decades that attempt to apply data analytics processes to shopping habits. As such, it stands to reason that AI can be useful to refine existing shopping experiences further and create a personalized journey for each individual or family.

Businesses can more accurately forecast how customers act by using predictive analytics based on mass habits and individual preferences. A business can then leverage e-commerce best practices alongside this information to adapt how it presents its products to any specific account.

Software can now automatically perform tasks like:

• Generating and iterating on customer segmentation
• Processing world data in real-time to adapt to market changes
• Watch worldwide and local trends for news to leverage for promotions
• Automate mundane tasks such as customer service and inventory management

Together, this information can provide information to customers that both boosts buyer agency and keeps control firmly in the hands of the business. Research from GSC Advanced Research and Reviews also confirms that this increases customer purchase satisfaction.

Specific AI Solutions for E-Commerce

Machine learning in e-commerce allows for accurate predictions using the full scale of customer data on offer. For example:

With accurate and carefully curated inventory, for example, a system can detect when it is likely to run out of specific inventory. If those products are limited, it can then analyze customers’ profiles, determine who is most likely to buy a product if prompted and promote it to them. Doing this ensures that the company frees up inventory space and also does not oversell products.

When specific events or holidays are coming up, a system can also look at the habits of customers as a whole, as well as their online activity. It can work out who will most likely celebrate a specific holiday and promote related products to them. Should the company receive a complaint about a specific promotion, it will detect this if connected to a CMS system and refrain in the future.

These microtargeting efforts take minimal effort and offer an extremely high ROI by leveraging AI-driven customer insights to great success. 

Targeting Customers with Hyperspecific Customizability

As customers continue to use your site, AI-driven algorithms can also analyze larger swathes of data about them. This includes their:

• Purchasing history
• Preferences
• Pages visited
• Blog posts read
• Customer service interactions
• Product reviews

Using this information, an AI can craft individualized recommendations for each user. For example:

Personalized Browsing Recommendations

By analyzing what a customer prefers by analyzing their behavior, it can start recommending products it sees other users buy. It can also detect which users rate those products highly to ensure the targeted user will likely have the same opinions, avoiding making “bad” recommendations.

Timely Suggestions

A system can detect how often customers buy specific items. If customers buy a face cream once every eight weeks, the AI can wait for a similar time before sending emails recommending the product again. It can also offer deals to reduce the likelihood of customers shopping around for better deals.

Tailored Promotions

A system can start to identify specific customer segments based on their behaviors. For example:

• Loyal and returning customers
• Deal-seekers
• First-time buyers
• Luxury item buyers

The AI can start making personalized suggestions for items and offers based on the habits of these segments. For example, loyal customers can receive exclusive discounts that reward their actions, or be targeted with preorder bonuses. Alternatively, those looking for deals may be offered more but with a lower value to get them to make smaller purchases more often.

Dynamic Search Results

Many users may see more specific information in their search results that result from their buying habits. An algorithm can start to push items that are likely to be more relevant to each user earlier in search results, making a sale more likely. 

Personalized Bundles

If the AI detects that a user often buys specific items together or that specific segments follow this pattern, it can create “branded” bundles. These product combinations can save the user time and improve their UX by giving them exactly what they want when they want it.

Stock Predictions

Based on all this information, AI can also predict future buying patterns. This data ensures a company always has enough stock for customers based on their expected sales levels.

Other Benefits of AI Solutions for Customized Shopping

Beyond the suggestions above, other examples of what a digital system might do when utilizing AI include:

• Natural language processing to empower virtual assistants to help customers
• Allow a company to detect if its direction is going to be successful or if it should pivot
• Detection of fraudulent transactions based on clear patterns
• Guiding product development with analysis of customer feedback
• Leveraging specific marketing success to learn the values customers hold
• Learning how customers respond to both internal and competitors’ price changes

The limits are almost endless, and the more information you make available, the more clear judgments an AI can make on 

Leveraging E-Commerce Artificial Intelligence Tools for Better Engagement

The world of customized shopping is already transformed by AI solutions for e-commerce that empower both the customer and the store. It’s time you harness the power of AI to elevate your sales strategies and turn shopping experiences into something that helps your business thrive.

Working with NotifyVisitors, you can leverage AI to find new ways to optimize your customer conversion and boost loyalty to your e-commerce store. Schedule a demo today and find out how we can help you fuel your full potential.