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10 Bold Ways to Use AI in Ecommerce

10 Bold Ways to Use AI in Ecommerce

The robots are coming for eCommerce!

Unless you’ve been living on a remote deserted island for the last couple of years, you have surely heard about artificial intelligence (AI).

AI has exploded in popularity and is transforming almost every aspect of our lives- online shopping included. In fact,eCommerce robots are so powerful that they forecast that AI will power 95% of customer interactions by 2025.

So here it is. If you are an eCommerce business owner, the use of AI is non-negotiable. You need to harness the power of AI if you want to succeed online and you need to take bold steps toward this transformation.

In this blogpost, we share some ways for you to harness the power of AI in eCommerce. From hyper-personalizing an email to stopping payment frauds, here are some turbo charged tactics you can put into play as early as tomorrow.

Keep on reading to learn more!

Hyper Personalized Recommendations

You already use some kind of personalization, right, for example adding a person’s name to a standard email such as “Dear (first name)” and a standard message. This is a common brand interaction and example for traditional perzonalization.

Hyper personalization goes to another depth entirely. It uses the power of AI and machine learning (ML), in addition to other devices powered by the Internet of Things (IoT). AI allows you to generate product recommendations tailored specifically to each individual customer based on their unique browsing history, purchases, interactions and more. A good example of this would be Amazon recommendations.
Examples of such engines are YouChoose, Recolize, Kibo, and Unbx.

Hyper-Targeted Marketing Campaigns

Powered by machine learning algorithms that analyze consumer behavior and preferences, hyper targeted marketing campaigns can precisely tailor content, product recommendations, incentives and communication channels.

This extreme segmentation allows you to deliver the right message to the right customer at the right time, driving up your engagement and conversions.

Examples of hyper-targeted marketing tools:

  • Albert: AI-powered personalization and predictive segmentation.
  • AgilOne: Customer data platform for building AI models to predict behaviors.
  • Triblio: Leverages AI for account-based marketing and campaign personalization.
  • Persado: AI-generated messaging that emotionally resonates with each customer.
  • Crayon: Uses machine learning to rapidly create and optimize hyper-targeted campaigns.

Readers Also Enjoy: What Is Hyper Personalization? How to Use It for More Sales? – DevriX

Predictive Analytics

AI can churn through mountains of data from across your business to uncover insights that human analysts would likely miss.

Predictive tools can forecast future trends and demands, optimize pricing, flag potential issues, and simulate different scenarios so that you can make better decisions.

Here are 5 examples of predictive analytics tools for eCommerce:

  • Google Analytics: Provides predictive insights on website traffic, customer segmentation, and sales forecasting.
  • Mixpanel: Predicts user engagement and churn to optimize product experiences.
  • Adobe Analytics: Uses machine learning to predict customer lifetime value and forecast revenue.
  • SAS: Statistical analysis software with predictive modeling capabilities for merchandising, marketing.
  • IBM Watson: Leverages AI and ML to uncover trends and patterns to forecast.

Virtual Shopping Assistants and Shoppers

Virtual Shopping Assistants and Shoppers

Chatbots and virtual assistants like Ada Support are revolutionizing eCommerce customer service. These chat agents that can answer common questions, process returns, provide support and deliver a top-notch self-service experience 24/7.

Virtual shopping assistants refer to any AI/bot that can help shoppers. Although, virtual personal shoppers are more specific than assistants – they use AI/data to mimic a personal stylist and provide highly customized fashion/beauty recommendations.

These virtual stylists suggest products, outfits, and bundles that reflect the shopper’s taste and complement their wardrobe. The goal is to deliver a personalized boutique-like shopping experience that builds loyalty and trust.

Here are 3 examples:

  • Fabriq AI: An AI stylist that learns your style preferences and makes daily outfit suggestions based on your wardrobe.
  • Eyewear Virtual Try-On by Ditto: Uses AR and AI to create a customized virtual dressing room to try on eyeglasses.
  • Clara by Clarifai: A visual AI assistant that can search for clothing items identified in photos to make shoppable recommendations.

Dynamic Pricing

AI pricing tools can run thousands of simulations to identify the optimal price point for maximizing revenue. Leverage real-time data to adjust pricing on the fly based on fluctuations in supply, demand, competitors’ prices, conversions and more.

Tools like Competera, Price2Spy, and Versium dynamically crunch numbers and derive actionable pricing strategies. Retailers like Amazon use dynamic pricing to respond fluidly to fluctuations in supply and demand.

Smart Payment Processing

Smart payment processing uses AI and machine learning to provide automated and optimized payment solutions to eCommerce businesses.

With smart payment tools you can streamline processes, prevent fraud, offer targeted promotions, and customize checkout experiences. Examples include Riskified, Sift, Bolt, and Ekata which use advanced algorithms to take the guesswork out of payment processing.

Readers Also Enjoy: 10 of the Most Popular Payment Gateways for Your Mobile Checkout Process – DevriX

Automated Inventory Management

Machine learning algorithms like InventoryBox can optimize your inventory operations buy forecasting demand, identifying trends in product consumption, pinpointing dead stock, and recommending ideal inventory levels for each product. This last feature prevents overstocking and stockouts by using robots like 6 river systems to do the reordering. Other tools like Lokad and Brightpearl leverage data science to perfect inventory planning and cut waste.

With AI handling the number crunching, you can keep your inventory lean and moving. You can also avoid tying up excess capital, and ensure that customers find the products they are looking for. It takes the guesswork out of inventory management.

Lifetime Customer Value Prediction

Because not all customers are equal, AI-powered tools like can be a lifesaver. These tools can analyze past spending patterns, among other metrics, to score each customer based on their projected lifetime value.

These insights can then help to not only optimize your acquisition strategy, but personalize engagement, and allocate resources toward your highest value customers. It focuses your marketing on revenue growth.

By understanding the value of each customer, you can micro-target higher revenue segments and maximize Customer Lifetime Value (CLV).

Enhanced Site Search

AI-powered search tools like Algolia offer an enhanced site search experience. It learns from user behavior to understand intent and match queries with relevant products. They provide autocomplete suggestions, spell-check, synonyms and continually refine results for higher conversions. Voice search optimization is a must too.

Other AI search options include Lucidworks Fusion, Attivio Cognitive Search, and Cove.

Automated Lead Scoring

Powerful AI lead scoring models can analyze thousands of data points to focus on the leads most likely to convert.

Algorithms assess factors like demographics, interaction history, activity on your site and so much more to identify the prospects worth chasing. Hot leads get fast tracked for follow-up while bad leads are filtered out.

You can make your sales team more efficient by using AI like Leadfeeder to automatically score and prioritize leads.

Other options like Ironscales use predictive analytics to determine lead readiness and recommend actions for sales reps. Salesloft leverages AI and machine learning to optimize sequences and outbound engagement.

Readers Also Enjoy: What Is Lead Scoring and How to Do It for B2B – DevriX

Wrap Up

The future is here! AI in eCommerce will continue to evolve in exciting new ways as the technology expands.

Adopting AI early allows you to get ahead while competitors play catch up.

With the right strategy and tools, these robots can become powerful allies to your business growth. Be bold and explore how artificial intelligence can give your online store an edge.