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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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Contextual targeting is having a comeback, and it’s smarter, sharper, and more strategic than ever before. By 2030, annual contextual advertising spend is anticipated to reach $562 billion! As marketers move away from cookie-based targeting and adjust to a privacy-first digital world, contextual advertising is becoming one of the most effective ways to reach engaged audiences. Unlike the basic contextual keyword targeting of the past, today’s contextual strategies are built on data, machine learning, and deep audience insights. Experian, with Audigent, plays a key role in powering this evolution, enabling marketers to execute contextual campaigns with the precision, performance, and compliance needed for today’s environment. Let’s talk about how advertisers are reaching audiences in a changing advertising era with smarter contextual targeting. What is contextual targeting? Contextual targeting, by definition, is a cost-effective, privacy-safe way to engage audiences based on what they’re reading or watching in the moment without relying on personal identifiers. It places ads on webpages that contain content relevant to your product or service. Contextual targeting vs. behavioral targeting The concepts of contextual and behavioral targeting are commonly confused. Both aim to deliver relevant ads, but their methods differ significantly. Let’s break it down. Behavioral: Based on online behaviors Behavioral targeting builds user profiles based on factors like browsing history, clicks, and purchases, tracking users across platforms using cookies and device IDs. For example, if someone researches new SUVs on multiple sites, they might see car-related ads long after they’ve stopped actively looking. While 68% of consumers say they’re concerned about how their data is used in advertising, marketers have the opportunity to build trust through better targeting with Experian. We help brands meet rising consumer expectations with responsible, privacy-forward behavioral data and targeting options that enable you to reach audiences effectively while aligning with your privacy and control needs. Contextual: Based on content and environment Behavioral targeting will continue to play a valuable role in personalized marketing strategies, but contextual targeting is a compelling alternative or complement for strong performance in a privacy-safe, scalable, cost-conscious way. Contextual targeting focuses on the ad environment. It analyzes the page\’s content, such as keywords, tone, and structure, and serves ads that align with that context without personal identifiers or user tracking. With Experian Marketing Data, you can enhance contextual targeting further by layering in data about who’s likely to be on the page. That combination of content signals and audience intent creates smarter, more privacy-compliant campaigns that perform better. Innovations in contextual targeting In its early form, contextual targeting depended on simple keyword matches. While functional, it lacked nuance and often resulted in broad or irrelevant placements. Today, the approach is far more intelligent. Thanks to AI, machine learning, and natural language processing (NLP), platforms can now assess the full context of a webpage, analyzing tone, sentiment, structure, and content depth to determine the best ad match. Contextually-Indexed Audiences Experian’s Contextually-Indexed Audiences take contextual targeting one step further by analyzing traffic from websites and mobile applications to identify the types of frequent visitors to those pages with the power of rich consumer insights. Instead of simply showing up on relevant pages, brands can reach pre-qualified audiences mapped to those environments, combining intent, content, and data-driven strategy in a single solution. This is where contextual targeting is headed and why it\’s no longer just an alternative to behavioral but a strategic advantage in its own right. A privacy-first future Even as third-party cookies remain in use, their long-term reliability is uncertain, and the industry continues moving toward solutions that don’t depend on personal identifiers. Laws like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have led advertisers to rethink how they engage audiences, shifting focus from individual tracking to content and context. With modern tools, advertisers can use contextual targeting programmatic strategies to reach audiences in privacy-compliant ways that still deliver high performance. Programmatic platforms like demand-side platforms (DSPs) now offer pre-built contextual segments by industry, interest, seasonality, and more. In a few clicks, marketers can launch campaigns that align with content environments where consumers are already engaged without behavioral tracking. For brands looking to future-proof their media strategies, contextual is one of the few options that checks every box. Why more marketers are using contextual targeting Contextual targeting can help you grow your audience, drive web traffic, boost visibility, and increase conversions as data privacy regulations grow stricter worldwide. Here’s a deeper dive into the benefits of this targeting strategy. Connect with ready-to-engage audiences One of contextual targeting\’s greatest advantages is the ability to meet consumers exactly where and when they’re most receptive. It places your ads on pages where they naturally add value to the user experience. When someone is actively reading or watching content about a specific topic, they’re already in the right mindset, which makes your ad feel more like a helpful recommendation than an interruption. For example, if someone is reading a blog post comparing hiking backpacks, they’re far more likely to engage with an ad for outdoor apparel or trail shoes than one for an unrelated product like kitchenware. Drive sales and revenue while lowering costs Another draw of contextual targeting is its affordability for brands with limited budgets. It doesn’t require third-party data, identity graphs, or tracking infrastructure, so it’s easier on your media budget. By aligning ads with page context, brands can also see real business results, such as: Lower cost per thousand impressions (CPM): Since contextual ads are served based on the content of the page rather than user profiles, they often have a lower price tag — especially in verticals where access to behavioral segments may be more competitive. Reduced cost-per-acquisition (CPA): More relevant impressions mean fewer wasted clicks and better ROI. Lower cost-per-click (CPC): On networks like Google Display, CPCs for contextually targeted ads can be as low as $0.45, especially in e-commerce and consumer goods sectors. Higher conversion rates: Ads placed in relevant environments outperform generic placements, which increases the likelihood of action and conversion. Higher lifetime customer value (LTV): Users who arrive at your site from contextually aligned ads are more likely to convert and become repeat customers, driving long-term revenue. Quick and easy setup, built to perform Contextual campaigns can also be launched quickly, often within a day, and produce immediate results. One powerful option is Experian’s Contextually-Indexed Audiences, which combines real-time analysis from over two million websites with access to more than 1,400 trusted audience segments. Available through top demand-side platforms’ contextual marketplaces and Audigent private marketplaces (PMPs), this solution offers a scalable way to reach high-intent consumers without cookies or IDs. Getting started is simple. With a few inputs like relevant topics, keywords, or content categories, you can activate ads in environments where your audience is already engaged. And the best part? The ease and speed to launch doesn’t mean you’re sacrificing results. Because your ads show up alongside content your audience is already interested in, they feel timely and relevant, which leads to more clicks, stronger engagement, and better overall performance. Personalized experience based on known interest Consumers crave personalization. In fact, Deloitte conducted a 2024 study that found 80% of consumers want personalized brand experiences and spend 50% more with the ones that do. Contextual targeting meets that expectation by delivering relevance in the moment without tracking users’ online behavior.Experian’s Contextually-Indexed Audiences use contextual cues across the web to find common sets of audiences and identify where high-intent audience segments tend to show up. This helps advertisers deliver relevant, privacy-safe messaging to consumers who are more likely to engage, thereby building trust, capturing attention, and increasing performance while respecting user privacy. Brand safety Contextual targeting even helps brands avoid reputational pitfalls. With the help of AI and NLP, today’s contextual tools can assess what a page says and how it says it. That means you’re not just protecting user privacy but also your brand by ensuring your ads appear in relevant, trustworthy environments that reflect your values. Contextual targeting examples Contextual targeting works across nearly every industry, helping brands connect with audiences based on the content they’re consuming in the moment. Here are a few examples of this in action across verticals. Contextual targeting for automotive buyers Most car buyers don’t just walk onto the lot. They arrive informed, having begun their journey online, researching makes, models, financing options, trade-in values, and credit requirements. It’s during this discovery phase that contextual targeting shines. Advertisers in the automotive space can serve ads alongside car reviews, dealership comparisons, or articles about electric vehicle tax credits, connecting with shoppers actively gathering information and signaling strong purchase intent. When your ad appears in the middle of that research journey, it feels like the next logical step. Contextual targeting also helps local dealerships and national brands stay top of mind during key decision-making moments without relying on third-party cookies. Contextual targeting for first-time parents New parents are one of the most information-hungry audiences online. From sleep training and stroller reviews to feeding schedules and baby-proofing tips, they consume a massive amount of content across various topics. That content provides a rich canvas for contextual targeting. Brands selling baby gear, wellness products, insurance plans, or parenting services can place ads on relevant articles and forums, connecting with parents when they’re researching their options and making purchase decisions. Contextual targeting for political campaigns Contextual targeting helps political advertisers connect with voters in relevant, mission-aligned environments. In a time when misinformation and divisiveness can influence public perception, maintaining this control is more critical than ever. With contextual targeting, campaigns can place their ads alongside trustworthy, high-quality content that addresses issues relevant to their supporters, whether it’s local policy, national news, or editorial commentary aligned with their platform. Advertisers can also avoid content that may contradict their message or brand values. The future of contextual targeting While Google no longer plans to fully deprecate third-party cookies, the industry has already moved forward. Most marketers have invested in cookieless solutions, and that momentum isn’t slowing down. As contextual targeting becomes even more essential to future-proofing media strategies, its effectiveness depends on the quality and responsibility of the data behind it. That’s where Experian leads the way. Experian Marketing Data as the foundation At the core of Experian’s contextual targeting capabilities is Experian Marketing Data: a rich, privacy-compliant data set built from verified offline sources. This foundational data powers everything we do and fuels the full suite of Experian’s audience and targeting solutions. Marketing Attributes and Audiences One of the key products built from this data is Marketing Attributes, which transforms raw information into detailed, privacy-safe variables like lifestyle preferences, financial behaviors, and media habits. These attributes form the building blocks of Experian Audience solutions, allowing you to create highly specific segments tailored to your goals. When applied to contextual targeting, these segments help you align your messaging with the types of content your ideal audiences are consuming in real time. We’ll help you activate contextually relevant campaigns using real audience insight to place the right message in the proper environment at the ideal moment. Contextually-Indexed Audiences Powered by Experian Marketing Data, Contextually-Indexed Audiences brings a new level of precision to contextual targeting. By analyzing traffic from over two million websites and apps, we offer access to 1,400 audience segments (like luxury shoppers or frequent travelers) that are most likely to visit specific content. This lets you place your message in environments where your target customers already are, combining contextual relevance with data-driven intent. It’s a smarter, privacy-safe way to reach the right people without relying on cookies or user tracking. You can activate these audiences instantly through the top demand-side platform’s contextual marketplace or partner with Audigent to create a custom PMP. A PMP offers more control and flexibility and allows you to enhance campaign performance with additional performance optimization capabilities and activation across any media-buying platforms. Experian collaboration with Audigent and Peer39 Experian and Audigent partner to deliver SmartPMPs, or private marketplace deals that give advertisers access to premium inventory and privacy-first data activation in one streamlined solution. What makes this partnership unique is Audigent’s supply-side integration. Instead of only running audience segments through the DSP, SmartPMPs pair Experian’s high-performing audiences with curated inventory from thousands of publishers, all accessible through a single deal ID. This supply-side approach unlocks: Better reach across CTV, display, video, and more Stronger performance through real-time supply optimizations Personalized campaigns that don’t rely on cookies or user-level identifiers We’ve also partnered with Peer39 and Audigent to expand contextual targeting capabilities further. These partnerships make it possible to match Experian syndicated audience segments, including geo-indexed and behavioral data, to contextual signals in real time. Advertisers can now run fully cookieless campaigns with exceptional scale and performance by indexing Experian Marketing Data through our identity graph and activating through platforms like Audigent’s Hadron ID or Peer39’s integrations. In one beta test with Audigent, a major national advertiser used this solution to run a 15-day campaign that exceeded CTR benchmarks by 25% with no cookies or IDs. Talk to an Experian team member today The future of digital advertising is about trust as much as performance. Turn to Experian for help reaching your audience in the right environments using ethically sourced, privacy-first data. We help brands run scalable, contextually aligned campaigns built for today’s privacy landscape and tomorrow’s performance goals. With tools like Marketing Attributes, Contextually-Indexed Audiences, and Audigent PMPs, we make it possible to connect meaningfully without crossing privacy boundaries. Let’s talk about how we can help you lead the way. Latest posts

Supply-side platforms (SSPs) are expected to deliver more than inventory—they’re being asked to support sell-side targeting strategies, campaign results, and proof of performance. To meet that demand, SSPs need more than access to inventory. They need better data, better tools, and a way to bring it all together. Experian’s solutions for SSPs We built Experian’s solutions for SSPs with that demand in mind. By combining identity resolution, audience targeting, and third-party measurement, we help platforms move beyond basic transactions. Whether you’re doing sell-side targeting, supporting direct deals, or looking to support campaign validation, our tools make it easier to create value for buyers—and keep them coming back. Our solutions that help SSPs: Resolve identity across digital touchpoints using our industry-leading Digital Graph Build differentiated audiences using over 2,400 Experian Audiences and Partner Audiences in Audience Engine Support advertiser-direct relationships with tools to create, activate, and host custom segments Measure real outcomes like in-store visitation and sales through Outcomes, our third-party validated reporting suite Together, these capabilities allow SSPs to produce data-driven deals, increase addressability, and meet buyer demand for smarter, more measurable media. Campaign snapshot: Yieldmo + Experian Yieldmo, an advertising platform known for its creative formats and data-informed approach, has already put this solution to work. Here’s how they built a custom strategy for a major athletic retail client using Experian\’s joint solution for SSPs. The challenge: Drive in-store traffic and reach new buyers Yieldmo supports a leading athletic retailer’s seasonal campaigns focused on in-store traffic. This advertiser wanted to reach new buyers—specifically those who might otherwise shop with a competitor. To do this, they needed access to strong audience segments with reliable data and the flexibility to act quickly across channels. This was the first time Yieldmo applied Experian Audiences to this retailer’s campaigns. The stakes were high: the client was looking for better in-store outcomes and a more streamlined activation workflow. The solution: Experian\’s activation solution for SSPs Using Experian’s Audience Engine, which includes our proprietary and third-party data marketplace, Yieldmo built a flexible, high-performing media plan that spanned display inventory and included both conquesting and primary in-store shopper segments. The team selected and activated: Apparel and footwear audiences built from Experian and partner data providers In-store shopper segments targeting retail behavior signals Competitive purchasers to capture likely buyers from other athletic brands Our data marketplace allowed Yieldmo to combine Experian Audiences with Partner Audiences from providers like Alliant, Circana, Sports Innovation Lab, and Webbula—all in one place. Manual audience creation used to take days. Now, Yieldmo can build and activate campaigns through a streamlined, self-serve workflow. By working in the Audience Engine platform, Yieldmo was able to avoid multiple contracts and manual requests. They filtered audiences by brand, tailored segments to their goals, and launched without delays. “Experian’s data marketplace in Audience Engine fills a critical gap—letting us quickly search by brand, build smarter conquest segments, and activate custom audiences fast.”Abby Littlejohn, Director of Sales Planning, Yieldmo The results: Expected lift in store visits While final in-store lift results are pending, the early performance metrics are promising: Click-through rates are at and above historical benchmarks across both conquesting and primary shopper segments. Using Audience Engine’s self-serve tools, Yieldmo created audiences faster and more easily. They reduced their workload by minimizing the need for manual data wrangling. “We include Experian audience segments in 80% of formal RFPs. Between contract simplicity, data quality, and campaign results, Experian has become our go-to for third-party audience targeting.”Nelson Montouchet, AVP, Strategic Partnerships, Yieldmo Download the full case study Bring this to your platform Whether you’re looking to monetize more effectively, build deeper advertiser relationships, or stand out with sell-side targeting offerings, we designed Experian’s solutions for SSPs to do exactly that. With our industry-leading Digital Graph, over 2,400 syndicated audiences, partner data, flexible self-serve tools, and outcome-based measurement, SSPs can now move faster and go further—without compromising scale or precision. Get in touch with our team Latest posts

After another week under the sun at Cannes Lions 2025, one thing is abundantly clear: our industry is done talking about possibilities — it’s ready to act. From speaking engagements to packed suite meetings, and even stateside through our “Can’t Cannes” activations, the appetite for change was real — and we were right at the center of it. A front-row seat to innovation Experian made a powerful impact across the Croisette, partnering with Audiostack, Basis, Infillion, IQVIA, Magnite, NextRoll, Odeeo, OpenX, The Female Quotient, and the Unplugged Collective x The Digital Marketer, to contribute to some of the week’s most insightful conversations. Our thought leaders were everywhere—on stage, in studio interviews, at executive roundtables—offering a clear voice on retail media growth, pharma advertising disruption, AI innovation, and identity-driven personalization. Three themes that defined the week 1. AI gets real If 2024 was the year of AI buzz, then 2025 is the year AI found its footing. Conversations shifted from “what if” to “what now.” While the promise of AI was front and center, conversations with clients and partners highlighted that we’re still in the foundational phase. Real-world applications—from creative optimization to predictive segmentation—are gaining traction, but long-term value will depend on robust data architecture and trustworthy identity frameworks. MiQ and PMG debuted AI-integrated platforms that demonstrated how AI can automate creative, optimize budget allocation, and personalize media in real time. AI has moved from sidekick to strategist. \”Last year it was all about AI, but in a very general sense. This year, it’s about specific applications — a clear sign AI is evolving from a talking point into product.”Budi Tanzi, VP, Product 2. Outcomes > impressions Outcomes may have been a buzzword at Cannes, but as several industry leaders pointed out, simply saying “we drive outcomes” isn’t enough—it risks sounding like table stakes. In today’s performance-driven environment, what matters is how companies define and deliver those outcomes in unique ways. The most compelling conversations weren’t about generic promises, but about clear strategies: challenging assumptions, leaning into strengths, and making specific choices that tie data, media, and technology to measurable impact. \”By using consistent identity across planning, activation, and measurement, marketers can connect ad exposure to real-world outcomes—whether that’s an online conversion, an in-store visit, or a new customer relationship.\”Chris Feo, Chief Business Officer 3. Curation isn\’t just a tactic Curation is quickly becoming the industry’s preferred approach to cutting through complexity. As marketers contend with signal loss and inconsistent inventory quality, the shift from broad access to intentional activation is gaining momentum. At Experian, we see curation not just as packaging, but as strategic alignment—where identity, data, and inventory come together in purpose-built environments that reduce waste, enhance safety, and drive performance. \”Supply-side data activation and optimization, aka “curation,” is an alternative to the traditional approach to data activation. Unlike the traditional DMP-to-DSP activation flow, curation allows buyers to leverage supply-path data more directly. The upshot? Improved performance and pricing for media agencies and brand advertisers.\”Drew Stein, Managing Director, Audigent Bringing the Cannes experience stateside Not everyone can make it to the South of France—so we brought Cannes to them. Our “Can’t Cannes” events in the U.S. offered local clients a first-class experience filled with insights and networking, minus the jet lag. Final takeaways This year’s festival made one thing clear: real progress requires more than innovation; it requires integration. And that’s where Experian is focused—connecting identity to activation, and data to outcomes, in ways that are practical, scalable, and privacy-resilient. If I had to sum it up? AI is progressing from abstract to application Curation beats clutter Partnership is power And everyone’s aligned around performance We’re grateful to have been part of these conversations and even more excited about where they’ll lead next. Let’s continue the conversation If you\’re exploring how to connect identity to performance, or simplify the way you activate, measure, and grow, we’d love to talk. Latest posts