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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.
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Ditch the cookie, not the data with the next evolution of contextual targeting Today, we're excited to announce Contextually-Indexed Audiences, a game-changer in contextual targeting. Experian’s new solution offers advertisers a powerful, privacy-safe solution that combines the precision of deterministic audience targeting with the flexibility of contextual targeting. Powered by real-time analysis from two million websites, access to 1,400 trusted audience segments, and easy activation through the top demand-side platform’s contextual marketplace or Audigent private marketplaces (PMPs), this solution offers advertisers a scalable way to reach their target consumers. With this solution, advertisers can reach consumers on websites that over-index for visitors with the demographics, behaviors, or interests, they are looking to target. For example, an automotive brand can select Experian’s “Contextually-indexed in-market for a luxury electric car” audience segment and reach consumers when they are browsing websites that often attract that exact segment. Best of all, this is done in a privacy-safe way since it’s not reliant on cookies, mobile ad IDs (MAIDs) or other user identifiers. How Contextually-Indexed Audiences work Contextually-Indexed Audiences harness advanced machine learning technology to move beyond traditional keyword-based strategies. The solution works in three steps: First, it analyzes traffic from over two million websites and mobile apps to identify the types of frequent visitors to those platforms. Next, using Experian’s Digital Graph, it resolves the identities of those visitors and maps them to more than 1,400 of Experian’s Syndicated Audiences, determining which audiences are most overrepresented on each site. Finally, the relevant audiences are assigned to those sites, allowing advertisers to deliver ads to people in those audiences while they are actively browsing the websites — without relying on user identifiers. Customer success story A leading auto manufacturer was among the first clients to activate this new solution while we were in beta. The goal was to identify new contextual targeting solutions that focus on privacy while maintaining scale and performance. The client identified two key target audiences: first-time vehicle buyers and experienced buyers. The initial campaigns using this new solution were highly successful. Even as the campaign scaled to twice the original volume, it continued to deliver three times the targeted click-through rate (CTR) goal. “Partnering with industry leaders like Experian, we're pushing the boundaries of contextual targeting with innovative data strategies that offer buyers greater flexibility and improved performance. These advanced contextual solutions are exciting as they not only drive results but also have the same privacy safeguards as traditional contextual targeting.”Matt Griffith, CTO & Co-Founder, Audigent Benefits of Contextually-Indexed Audiences Accurate consumer reach: Real-time integrations with over two million websites and apps coupled with machine-learning indexing technology ensure audience segments are constantly refreshed, which means advertisers reach consumers based on their latest habits. Privacy-safe audience targeting: These audiences are not reliant on cookies or any other user identifiers for targeting. Audience customization: Create the right audience segment for your campaign by using a combination of over 1,400 audiences across 12 data categories like demographics, politics, health, travel, finance, and TV. Flexible activation: Activate these audiences instantly in the top demand-side platform’s contextual marketplace or utilize our partnership with Audigent to create a custom private marketplace (PMP), where they can be activated across any media buying platform. When using a PMP, advertisers benefit from additional performance optimization capabilities. Experian’s Contextually-Indexed Audiences offer advertisers a powerful solution that combines the precision of audience targeting with the flexibility of contextual targeting. With real-time analysis of over two million sites and access to 1,400 trusted audience segments, advertisers can reach consumers based on their exact behaviors and interests. This is done in a privacy-safe, yet scalable way since it’s not reliant on cookies or other user identifiers. Whether activating instantly through the top demand-side platform or customizing through Audigent PMPs, this is the future of audience targeting. Ditch the cookie, not the data, and elevate your strategy today. See how these audiences can work for you Latest posts
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By partnering with us, you work with a single data provider that offers access to a diverse range of audiences across multiple categories, including political and holiday shopping. Our audiences are available for activation on the leading demand, supply, social, and TV platforms. Reach out to your account representative or our audience team for information about our comprehensive audience mapping and finding the right audiences for your campaigns. Connect with our audience team Download our audience lookbook to discover more about Experian’s audiences. Latest posts