In this article…
Technology is pushing the boundaries of commerce like never before. Artificial intelligence (AI) is one of the primary driving technologies at the forefront of the commerce evolution, using advanced algorithms to revolutionize marketing and personalize customer experiences. As of 2024, AI adoption in e-commerce is skyrocketing, with 84% of brands already using it or gearing up to do so.
This article explores the AI revolution coming to commerce, focusing on what makes AI a driving force for e-commerce in particular, and the ways it’s reshaping how businesses engage with consumers.
Understanding the AI revolution in commerce
AI is quickly reshaping commerce as we know it by democratizing access to sophisticated tools once reserved for large corporations, breaking down functional silos within organizations, and integrating data from multiple sources to achieve deeper customer understanding. It’s paving the way for a future where every brand interaction is uniquely crafted for the individual, powered by AI systems that anticipate preferences proactively.
AI is a broad term that encompasses:
- Data mining: The gathering of current and historical data on which to base predictions
- Natural language processing (NLP): The interpretation of human language by computers
- Machine learning: The use of algorithms to learn from past experiences or examples to enhance data understanding
The capabilities of AI have significantly matured into powerful tools that can improve operational efficiency and boost sales, even for smaller businesses. They have also fundamentally changed how businesses interact with customers and handle operations. As AI continues to develop, it has the potential to provide even more seamless, personalized, and ethically informed commerce experiences and establish new benchmarks for engagement and efficiency in the marketplace.
Four benefits of the AI revolution coming to commerce
Major commerce players like Amazon have benefited from AI and related technologies for a while. Through machine learning, they’ve optimized logistics, curated their product selection, and improved the user experience. As this technology quickly expands, businesses have unlimited opportunities to see the same efficiency, growth, and customer satisfaction as Amazon. Here are four primary benefits of AI adoption in commerce.
1. Data-driven decision making
AI gives businesses powerful tools to analyze large amounts of data more quickly and accurately than a person. Through advanced algorithms and machine learning, AI can sift through historical sales data, customer behavior patterns, and market trends to uncover insights and suggest actions that might not be immediately obvious to human analysts. By transforming raw data into actionable insights, AI empowers businesses to make more informed decisions, reduce risks, and capitalize on opportunities.
As a real-world example, Foxconn, the largest electronics contract manufacturer worldwide, worked with Amazon Machine Learning Solutions Lab to implement AI-enhanced business analytics for more accurate forecasting. This move improved forecasting accuracy by 8%, saved $533,000 annually, reduced labor waste, and improved customer satisfaction through data-driven decisions.
2. A better customer experience
AI is set to make customer interactions smoother, faster, and more personalized by recommending products based on preferences and behaviors, making it easier for customers to find what they need.
When consumers visit an online store, AI also provides instantaneous help via a chatbot that knows their order history and preferences. These AI-powered assistants offer real-time help like a knowledgeable store clerk. They give the appearance of higher-touch support and can answer basic questions at any hour, provide personalized product recommendations, and even troubleshoot issues. Chatbots free up human customer service agents for more complicated matters, and these agents can then use AI to obtain relevant information and suggestions for the customer during an interaction.
3. Personalized marketing
Data-driven personalization of the customer journey has been shown to generate up to eight times the ROI, as data shows 71% of consumers now expect personalized brand interactions. Until AI came around, personalization at scale was complex to achieve. Now, gathering and processing data about a customer’s shopping experience is easier than ever based on lookalike customers and past behavior.
Many businesses have adopted AI to glean deeper insights into purchase history, web browsing, and social media interactions to drive better segmentation and targeting. With AI, advertisers can analyze behavioral and demographic data to suggest products someone is likely to love. Consumers can now browse many of their favorite online stores and see product recommendations that perfectly match their tastes and needs.
AI can also offer special discounts based on purchasing habits, and send personalized emails with products and content that interest customers to make their shopping experience more engaging and relevant. This personalization helps businesses forge stronger customer relationships.
Personalization across digital storefronts
Retail media involves placing advertisements within a retailer’s website, app, or other digital platform to help brands target consumers based on their behavior and preferences within that environment. Retail media networks (RMNs) expand this capability across multiple retail platforms to create seamless advertising opportunities throughout the customer journey. Integrating AI into RMNs can improve personalization across digital storefronts with personalized, relevant ads and custom offers in real time that improve the customer experience.
4. Operational efficiency
AI can also be beneficial on the back end, enabling more efficient resource allocation, pricing optimization, efficiency, and productivity.
Customers can be frustrated when they visit a store for a specific product only to find it out of stock or unavailable in a particular size. With AI, these situations can be prevented through algorithms that forecast demand for certain items. Retailers like Amazon and Walmart both use AI to predict demand, with Walmart even tracking inventory in real time so managers can restock items as soon as they run out.
AI can automate and streamline operational tasks to help businesses run smoother, faster, and more cost-effective operations. It can:
- Offload tedious data entry, scheduling, and order processing tasks for greater fulfillment accuracy.
- Analyze historical data and market trends, predicting demand to help businesses optimize inventory, reduce waste, track online and in-store sales, and prevent shortages.
- Forecast demand levels, transit times, and shipment delays to make better predictions about logistics and supply chains.
- Improve data quality using machine learning algorithms that find and correct product information errors, duplicates, and inconsistencies.
- Adjust prices based on competitor pricing, seasonal fluctuations, and market conditions to maximize profits.
- Pinpoint bottlenecks, identify issues before they escalate, and provide improvements for suggestions.
Future trends and predictions
If you want to stay ahead in e-commerce, it’s just as important to know what’s coming as it is to understand where things are today. Here are some of the trends expected to shape the rest of 2024 and beyond.
Conversational commerce
Conversational commerce allows real-time, two-way communication through AI-based text and voice assistants, social messaging apps, and chatbots. Generative AI advancements may soon enable more seamless, personalized interactions between customers and online retailers. This technology can improve customer engagement and satisfaction while providing helpful insights into preferences and behaviors for better personalization and targeting.
Delivery optimization
AI-driven delivery optimization uses AI to predict ideal routes for each individual delivery, boosting efficiency, reducing costs, promoting sustainability, and improving customer satisfaction throughout the delivery process.
Visual search
AI-driven visual search is quickly improving in accuracy, speed, and contextual understanding. Future developments may integrate seamlessly with augmented reality (AR) so shoppers can search for products by pointing their devices at physical objects. Social media and e-commerce platforms may soon incorporate visual search more prominently, allowing users to find products directly from images.
AI content creation
AI is already automating and optimizing aspects of content production:
- Algorithms can generate product descriptions, blog posts, and social media captions personalized to specific customer segments.
- AI tools also enable the creation of high-quality visuals and videos.
- NLP advancements ensure content is compelling and grammatically correct.
- AI-driven content strategies analyze consumer behavior and refine messaging to meet changing preferences and trends.
This automation speeds up content creation while freeing resources for strategic planning and customer interaction.
IoT integration
Integrating AI with Internet of Things (IoT) devices could help make the ecosystem more interconnected in the future. AI algorithms can use data from IoT devices like smart appliances, wearables, and sensors to gather real-time insights into consumer behavior, preferences, and product usage patterns. This data enables personalized marketing strategies, predictive maintenance for products, and optimized inventory management. AI-driven IoT data analytics can also streamline supply chain operations to reduce costs and inefficiencies.
Fraud detection and security
There will likely be an increased focus on the ethical use of AI and data privacy regulations to strengthen consumer trust and transparency. AI-powered systems will get better at detecting and preventing fraud in e-commerce transactions, which will heighten security measures for both businesses and consumers.
Chart the future of commerce with Experian
AI has changed how marketers approach e-commerce in 2024. With AI-driven analytics and predictive capabilities, marketers can extract deeper insights from extensive data sets to gain a clearer understanding of consumer behavior. This enables refined segmentation, precise targeting, and real-time customization of messages and content to fit individual preferences.
Beyond insights, AI automates routine tasks like ad placement, content creation, and customer service responses, freeing marketers to concentrate on strategic planning and creativity. Through machine learning, marketers can predict trends, optimize budgets, and fine-tune strategies faster and more accurately than ever. The time to embrace AI is now.
At Experian, we’re here to help you make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Using AI in your commerce marketing strategy with our Consumer View and Consumer Sync solutions can help you stay competitive with effective, engaging campaigns.
Contact us to learn how we can empower your commerce advertising strategy today.
Latest posts
Spring is here! For some of us, spring means the return of warm weather, for others it signals a time to clean out the clutter or, a time for more outdoor activities. Successful marketers know that just as spring habits vary, so do seasonal buying patterns. Marketers should take advantage of advanced marketing tools to capitalize on consumer spending around the changing seasons. There are three areas that will help you deliver the most value to your customers throughout the year: preference data, message relevancy, and a mobile-first approach. Preference data Spring is a great time to gather preference data as “spring cleaning” inspires consumers to research and purchase new items as they begin purge their closets of last season’s look. Collecting information from your customers about the types of products they are interested in will enable you to accurately tailor the content you send them through the remainder of the warm weather seasons. Message relevancy Differences in climate and culture affect style preferences from city to city. To give your customers a tailored experience, use their preference data to delivery personalized content and product suggestions. By using dynamic content tools and filters in your marketing automation platform, you can be sure the right content is presented at the right time, to different audiences within the same campaign. Personalizing your communication shows your customers that you understand their needs and preferences, builds brand trust, and long-term loyalty. Mobile first With the thaw of winter, spring inspires activity and productivity – with so much to do, your customers have more reasons to be on the go. This is the perfect time of year to scale up your mobile PUSH and SMS campaigns to reach consumers wherever they are. Consider adding triggers based on location data from visits to your mobile app or visits to your site from a mobile browser. Triggering a message to your customers while they’re near your store is a powerful way to drive relevant messaging and purchase intent. Focusing on these three core areas will help you deliver the most value to your customers through the season and throughout the year. Learn more about how our team of experts can help with comprehensive marketing strategies that will take your marketing to the next level.
Partnership leverages industry-leading Tapad Device Graph™ for more effective video marketing across all connected devices NEW YORK, April 11, 2017 /PRNewswire/ – Tapad, a part of Experian, the leading provider of privacy-safe, cross-device marketing technology solutions, has announced its partnership with Innovid, the world's leading video marketing platform. This integration enables Innovid to bring cross-device personalization and a more unified viewer experience to its video marketing clients including Bank of America, L'Oréal, Microsoft and Procter & Gamble. Innovid's proprietary technology is the only platform optimized for video, enabling marketers to thrive in an ever-changing digital television landscape. Since its launch last year, Innovid's Marketing Cloud Suite has helped marketers increase message relevance and the opportunity to drive conversions, retention and acquisition through video personalization. By leveraging the Tapad Device GraphTM, Innovid's marketers can now benefit from the ability to drive consistent, personalized user experiences across all devices, creating more impactful connections with consumers and increasing ROI. "Personalization is a must for every data-driven marketer and really needs to happen across all devices to ensure a unified customer journey," says Ronnie Lavi, SVP of product at Innovid. "At Innovid, we recognize one size does not fit all when it comes to video. As an open platform, we are always looking to add best-of-breed capabilities through integrations and partnerships, and we've chosen Tapad because of its superior cross-device expertise." "Innovid has long paved the way for effective personalization in the video marketing space," says Pierre Martensson, GM of Tapad's data division. "As video continues to gain popularity across digital formats, we're excited to see how our technology empowers Innovid to bring that renowned personalization to more customers across all of their devices." Contact us today!
Tracey Scheppach's new marketing and media practice leverages Tapad's device-level data to help clients achieve "marketing nirvana" NEW YORK and CHICAGO, April 5, 2017 /PRNewswire/ — Today, Tapad, now part of Experian, is the leading provider of unified, cross-screen marketing technology solutions, and Matter More, a next generation marketing and media practice with deep experience in the advanced TV space, announced a strategic partnership to bring together world class digital data and audience development expertise to help marketers improve how they connect with consumers. As consumer behavior continues to expand across multiple devices, today's marketers need robust, comprehensive data solutions to accurately engage the people who matter most to their brands. At the same time, the TV industry has reached an advertising tipping point, capitalizing on the power of device-level data. "Achieving unduplicated reach and frequency across all channels with true addressability, and the ability to measure outcomes, is marketing nirvana," says Tracey Scheppach, CEO and co-founder of Matter More, a new agency built for the modern age. "The best opportunity to deliver 'marketing nirvana,' at scale, is by partnering with Tapad and using their world-class Device Graph to help our clients simply matter more to the people they care about most." "By leveraging our access to rich TV data, we can now measure the actual performance of media across channels," says Marshall Wong, SVP, TV for Tapad. Tapad's proprietary Device Graph™ unifies consumer behavior data across all devices, uncovering the interests, passions and behaviors of the audiences who matter most. As with any data solution, privacy, transparency and trust are crucial to bringing marketers a solid offering that delivers results. "Tapad is excited to partner with Matter More to tap into their knowledge base and experience working with some of the largest brands on TV today," says Kate O'Loughlin, SVP and GM of Tapad's media division. "The time has come to truly unleash the power of device-level data at scale." Contact us today