AI for eCommerce: The Ultimate Guide
It’s estimated that by 2030 AI will contribute $15 trillion to the global economy through productivity and the resulting increased consumption. This is not surprising when you consider that adaptation of AI has been growing by around 6% per year since 2020.
AI for eCommerce plays a big part in this growing trend. And if you haven’t been substantially investing in AI for eCommerce, it’s almost too late — almost.
In this guide, we take you through absolutely everything you need to know about harnessing the power of artificial intelligence to dominate your niche. Here’s a quick look at what this guide will cover.
Let’s jump in.
How Artificial Intelligence Is Changing the eCommerce Industry
From personalized online shopping experiences to advanced eCommerce ad optimization, AI significantly impacts how online retail stores compete in a fast-growing industry.
The most substantial way AI is affecting the eCommerce industry is by helping more sellers to compete in this ever-expanding space. According to Statista, the top reason for integrating artificial intelligence is so that online brands can obtain or sustain a competitive advantage over their competitors.
And when you consider that there are an estimated 26.5 million eCommerce sites globally for online shoppers to choose from, the competition is immense. All of which is helping to drive AI technology for retail.
Ultimately, AI has become a powerful tool for brands to streamline their sales funnels while staying visible and relevant — reported to enhance overall business productivity by as much as 40%. The trick is matching the correct type of AI (such as generative AI models or data mining technologies) to your specific commerce business need and to reach customer engagement goals. Here are the AI innovations that are driving eCommerce technology.
Types of AI Driving eCommerce Technology
- Machine learning. Machine learning is a set of algorithms that continuously analyzes data and outcomes to dynamically “learn” and adapt.
- Deep learning. An offshoot or subset of machine learning, deep learning algorithms have been designed to imitate how humans gain certain types of knowledge, looking for patterns to drive automation.
- Data mining. Data mining is the process by which an AI algorithm searches for and collects historical data to make predictions.
- Natural language. Natural language AI is a collection functions that enable computers to understand and generate human language.
- Generative AI. Generative AI is designed to produce various types of content, including text, images, and video, based on user prompts. An excellent example of this would be ChatGPT, which is driving conversational commerce.
- Conversational AI. Conversational AI is eCommerce AI that can answer questions and mimic human conversations. A good example of conversational AI would be voice assistants such as Siri or on-store AI chatbots.
The bottom line is that AI enables stores to sell more products to more shoppers with automation and personalization. And the benefits to commerce businesses?
Benefits of Implementing AI for eCommerce
1. Smooth Dynamic Automation
AI-powered automation enables sellers to complete as many store tasks as possible with minimal human intervention. This can be as complicated as backend logistic robotics or as simple as product recommendations.
Either way, by leveraging advanced tools that harness the power of artificial intervention, you can run specific tasks on autopilot.
2. Better eCommerce Ad Targeting and Management
One area in AI — machine learning, in particular — is making big inroads in eCommerce ads. With the right technologies, online retailers can personalize their marketing across various channels while optimizing them automatically. (A leading tool using advanced AI technology designed specifically for eCommerce digital marketing is Traffic Booster.)
3. More-Seamless Buying Journey
Building a well-performing eCommerce sales funnel is vital if you want to compete. Why? Because of the way you move buyers through, the journey to checkout needs to be seamless to be successful — something that is virtually impossible to do without the power of AI.
From gathering data to automated abandon cart emails, automation helps you keep customers engaged in real-time.
4. Better Customer Retention
With the right AI technology in place, you can not only predict shopper behavior, but pivot strategies as these behaviors change in real-time. This ensures you are able to give your customers a more personalized shopping experience from start to finish, which helps you reduce churn rates and boost customer loyalty — ultimately improving retention.
5. Improved Profits
Yes, implementing AI to help manage your online store means quicker and more efficient optimization, resulting in more sales with higher AOVs (average order values) and improved CACs (customer acquisition costs). But that’s not the only way it boosts profits.
Integrating AI means less admin (and fewer work hours and team members) are needed to push those sales, ultimately improving results and driving down costs. By cutting back on backend admin work while optimizing for maximum performance on the frontend, AI helps you reduce costs and therefore increase profits.
AI Uses for eCommerce (and Top AI Tools)
Now we know just some of the benefits of investing in AI for eCommerce and artificial intelligence technology. So, let’s look at the best uses for AI — as well as some of the tools that will enable you to integrate these technologies into your store:
- Product description automation (+SEO optimization)
- Customer segmentation optimization
- Visual search improvements
- PPC management and optimization
- Customer service enhancement
- Voice search implementation
- Fraud prevention
- Demand forecasting efficiency
- Smart logistics implementation
- Product recommendations
Let’s take a closer look at each.
1. Product Description Automation (+SEO Optimization)
Auto-generated product descriptions are fast becoming a sought-after integration for online retailers. This is particularly important for stores with substantial category lists.
Not only does it save merchandising and marketing teams a lot of time, but improves SEO and marketing performance. And since launching in November 2022, OpenAI’s ChatGPT (the most talked about AI tool) is now driving product description AI to even greater levels.
StoreYa AI ChatGPT: AI Tool for eCommerce Product Descriptions
Product Description ChatGPT AI offers online retailers advanced AI algorithms and natural language processing capabilities — to generate amazing product descriptions with a click of a button.
Offering sellers the ability to generate high-quality product descriptions quickly and accurately frees up valuable time for other important tasks while also ensuring the descriptions are optimized for visitors. (Find out more here.)
2. Customer Segmentation Optimization
Whether it’s for email marketing or onsite promotions, the right customer segmentation strategy will ensure your messaging and buyer journey is tailored specifically to each shopper — and the platform they are on.
However, being able to automatically analyze data and segment strategically is critical. This is something that is almost impossible to do without AI. The right customer segmentation AI tools will be able to analyze and segment in real-time, improving accuracy and cutting back on admin time.
Peak.ai: AI Tool for eCommerce Audience Segmentation
Peak offers AI-powered customer segmentation as part of its platform.
Their Audiences feature enables online retailers to predict customer behavior, create lookalike audiences, and more. Some elements include segment maps, 35+ AI-driven attributes, centralized data, and easy integration. (Find out more here.)
Some other tools that use AI for customer segmentation include:
3. Visual Search Improvements
Visual search is another AI element that eCommerce stores should be looking at integrating. If you’re unfamiliar with visual search, it’s the ability for online shoppers to search a store by type of image instead of a keyword or text.
A good example of this type of technology in action is Pinterest’s Lens feature.
Since 2020, users have been able not only to search for items in a photo with this feature but to shop for them too.
Visidea: Visual Search AI for eCommerce
Visidea is a visual search and product recommendations tool. Powered by artificial intelligence, it’s designed to optimize your store shopping experience through visual search and personalized product recommendations.
4. PPC Management and Optimization
Another area of retail that is being shifted by new AI technologies — especially machine learning — is digital marketing. By incorporating AI tools into your PPC marketing, eCommerce stores can collect and analyze more store and customer data and adapt to that data, all in real-time.
This results in more-personalized campaigns that are automatically optimized to peak performance. When using the right tools, that is.
Traffic Booster: PPC Management AI for eCommerce
Powered by AI, Traffic Booster enables online retail stores to automate Google, Facebook, and Instagram ads. This includes optimizing your campaigns in real-time according to 300+ analyzed parameters to ensure you get the best results for the least amount of budget spend.
5. Customer Service Enhancement
Another way you can use the power of AI to drive personalization is through customer service. Whether it’s an advanced chatbot to keep shoppers engaged 24/7 or AI-generated video messages, incorporating AI in your customer support strategy and/or systems can be a game-changer. And thanks to the generative AI boom, it’s only just getting started.
Thankful and Tidio: Generative AI for eCommerce Customer Service Tools
Thankful is a generative AI SaaS that leverages GPT to ensure brands can automate their customer support while ensuring support responses are personalized and contextually relevant. (Find out more here.)
Alternatively, for Shopify users, you can use Tidio. Tidio is a customer experience platform with live chat, Lyro AI chatbot, ticketing, email marketing, and more.
Some other tools that use AI for customer service include:
6. Voice Search Implementation
Implementing voice search wasn’t easy — or cheap — in the past. However, thanks to AI technology advancements, it’s getting easier to optimize for natural language queries vital for voice search.
You can implement voice search technology by connecting a voice assistant (such as Google Assistant, which uses conversational and generative AI models) to your eCommerce platform (such as Shopify). Or you can use a stand-alone AI SaaS service that harnesses the power of conversational AI.
Optimove: AI-Powered Voice Search
Optimove is a platform that offers retailers hyper-personalized CRM marketing.
One of their newest features is AI-powered voice search. With speech-to-search, brands can empower their shoppers to search by speaking instead of typing.
Some other tools that use AI for voice search include:
7. Fraud Prevention
Another vital area worth investing in AI for eCommerce is fraud detection and prevention. Because AI technologies such as deep learning or machine learning can analyze vast amounts of store, marketing, and customer data, they can detect patterns and deviations which can signal fraud — all in real-time.
Riskified: AI for eCommerce Fraud Prevention
Specifically designed for online retailers, Riskified’s AI technology will quickly evaluate online orders and customer behavior to spot illegitimate transactions.
Some other tools that use AI for fraud detection/prevention include:
8. Demand Forecasting Efficiency
Demand forecasting is an integral part of any eCommerce business. Without correctly planning and managing inventory, the less likely your business is to survive long term, never mind turning a profit. Traditionally, demand forecasting was based on historical data, but this is no longer enough to compete. In order to survive, you need access to real-time data.
AI-powered sales and demand forecasting mean inventory predictions are not only more reliable, but more profitable too. Several AI tools are designed to help online retailers do just that; here’s one.
Foresient: AI for eCommerce Demand Forecasting
Using a generative AI model, Foresient’s (by Fractal) analytics-based, demand forecasting AI tool was created to help retailers better spot and predict demand patterns.
Some other tools that use AI for demand forecasting include:
9. Smart Logistics Implementation
From route optimization and warehouse automation to demand forecasting and inventory management, AI has already substantially transformed the logistics industry. And by implementing AI into your logistics strategies and mechanisms, you have better predictive capabilities and real-time data and insights.
This enables you to reduce costs while improving efficiency. And it doesn’t have to be involved and costly. With the right logistics Shopify app, you can use AI to select carriers in real-time — based on historical performance and data points.
Veeqo: AI for eCommerce Logistics
Veeqo is a multi-channel shipping and inventory platform for online retailers. It uses AI to help sellers optimize and automate different inventory and shipping tasks.
Some other tools that use AI for eCommerce logistics include:
10. Product Recommendations
Artificial intelligence has played a considerable role in driving the development of personalization through product recommendation technologies. The only thing more effective than a good product recommendation aimed at segmented customer groups is a personalized product recommendation based on real-time customer behavior.
Incorporating AI into on and offsite product recommendation strategies allows stores to optimize across multiple channels and use predictive analysis to up and cross-sell — to name a few integrations. All of which improves the overall online shopping experience, and therefore, customer satisfaction.
RichRelevance: Product Recommendation AI for eCommerce
RichRelevance is a cloud-based platform that offers personalized product recommendations and shopping experiences, combining individual shopper behavior and preferences with your business needs.
Some other tools that use AI for product recommendations include:
How to Implement Artificial Intelligence into Your Online Store in 4 Steps
Integrating artificial intelligence into your online store or marketing strategies doesn’t have to be overwhelming. Here are four quick steps on how to do just that:
- Get serious about data collection
- Define your goals
- Choose the best AI tool to match your business needs
- Test and optimize
Let’s take a very quick look at each!
1. Get Serious About Data Collection
First, you want to ensure you start collecting as much data as possible. For AI to work its magic, no matter what application, it needs data. So, you want to ensure you are set up to collect as much customer data as possible, from browsing behavior to purchase histories.
But remember to make sure you are data privacy compliant — complying with data privacy laws like GDPR.
2. Define Your Goals
Next, look at which area of your commerce business you want to incorporate AI in and what you want to achieve with automation and other AI algorithm capabilities. This could be optimizing your overall shopping experience or merely focusing on your on-store product recommendation strategies.
3. Choose the Best AI tool to Match Your Business Needs
Every top eCommerce service or tool should offer some degree of AI and automation — you will need to decide how much AI technology you need, if it suits your specific goals, and if it fits into your commerce business budget. You will want to look at each AI tool and consider:
- Integration and compatibility requirements
- Budget restrictions
- Features and functionality
- Tool training and customer support
- Testimonials, customer feedback, and user reviews
4. Test and Optimize
With any new AI tool, you will want to test and optimize settings to reach peak performance. This means keeping a close eye on your most important eCommerce KPIs to ensure the AI technology is working for your brands and meeting your unique business needs.
Final Thoughts: The Future of AI in eCommerce Is Here
Whether it’s as “old” as an AI chatbot or as sought after as an automation tool that harnesses the power of a unique AI algorithm, AI for eCommerce is here to stay. In fact, it is likely to change the face of online retail in the next few years.
AI technology is moving at a feverish pace, and with it, eCommerce technology and tools. Just look at the revolution of chat GPT-powered conversational AI and how it’s advancing everything from SEO optimization to customer support to the way businesses interact with their customers.
But remember, no matter which AI applications you decide to implement, remember there is no one-size-fits-all AI solution. Instead, you need to find solutions that offer an AI algorithm that aligns with your goals and needs to boost customer interaction, backend productivity, and brand profitability.
Artificial Intelligence in eCommerce FAQs
Artificial Intelligence in eCommerce FAQs
What are the components of artificial intelligence?
AI is a complex field that comprises data gathering/analysis, processing, and problem-solving AI algorithms. These AI solutions include:
- Machine learning
- Neural networks
- Deep learning
- Natural language processing (NLP)
- Cognitive computing
- Computer vision
- Knowledge representation
What is deep learning?
Deep learning is a type of machine learning AI that essentially teaches computers or systems to process data in a way the human brain would. It’s designed to recognize complex patterns in images or text to generate predictions and insights. It’s the AI technology that drives virtual assistants, fraud detection, and facial recognition AI solutions.
What does AI stand for in eCommerce?
eCommerce AI is artificial intelligence designed to improve the online shopping experience for commerce businesses. eCommerce AI uses various types of AI algorithms and technology, including machine learning and predictive analytics
How is AI used in eCommerce?
From virtual assistants, digital marketing, and online merchandising to dynamic pricing and personalized recommendations, AI can optimize almost every element of your online store.
How does AI generate personalized recommendations?
AI generates personalized recommendations using a wide range of techniques, such as content filtering and collaborative filtering.
An example of content-based filtering would be if a customer engages with a t-shirt in your store, and your system recommends other products (like a hoodie) with the same design.
An example of collaborative filtering is when your system recommends that same t-shirt to a different user altogether because they have similar tastes and behavior.
What kind of eCommerce automations can AI support?
Any repetitive task you need in order for your online store to function properly can be optimized and automated using artificial intelligence.
What is an example of AI in e-Commerce?
Some examples of eCommerce artificial intelligence applications include personalized recommendations, AI chatbots and virtual assistants, sales analysis tools, augmented reality, dynamic pricing, visual search, customer support automation, digital marketing, inventory management, customer loyalty programs, fraud detection/prevention, and more.
Nicole Blanckenberg
Nicole is a content writer at StoreYa with over sixteen years experience and flair for storytelling. She runs on a healthy dose of caffeine and enthusiasm. When she’s not researching the next content trend or creating informative small business content, she’s an avid beachgoer, coffee shop junkie and hangs out on LinkedIn.
Comments
comments
Powered by Facebook Comments