CustomerX 2026: AI Commerce, Retail Media and the Future of Customer Experience

Artificial intelligence continues to dominate the agenda at the largest marketing and technology conferences of 2026. Following discussions of AI transformation at international industry events, CustomerX 2026, held October 14–15 in London, continued the conversation.

Organized by RetailX Events, the conference brought together representatives from e-commerce, retail, advertising platforms, technology companies, and financial services.

Participants included representatives from TikTok, Tesco, Kingfisher, Wayfair, Unilever, Reckitt, Just Eat, and other major companies.

The central theme of CustomerX was Connected Commerce, the integration of different sales channels, advertising platforms, and digital services around customer needs.

However, much of the program focused on practical applications of artificial intelligence, from optimizing products for ChatGPT and automating Retail Media to AI agents, personalization, and new models of consumer engagement.

AI Search and Answer Engine Optimization

One of the most timely topics at CustomerX was how generative artificial intelligence is changing the way consumers search for products.

Instead of traditional search, where users explore multiple websites themselves, AI assistants can compare products, analyze their features, and generate ready-made recommendations.

For manufacturers and retailers, this creates a need to optimize product information not only for Google Search but also for ChatGPT, Gemini, and other AI systems.

What Product Data Means for AI Recommendations

This topic was addressed in presentations by Jason Forbes, CEO and co-founder of XEO360, and Stephen Edwards, Head of Agency at Tesco Media.

Speakers examined the role of product attributes, descriptions, and benefit claims in shaping recommendations generated by AI search engines.

Particular attention was paid to Product Detail Pages (PDPs). Product information needs to be sufficiently detailed, structured, and consistent for AI systems to interpret product attributes correctly.

Another challenge is maintaining consistency in product information across manufacturer websites, retailer online stores, and independent sources.

When product attributes, descriptions, and benefits differ across platforms, generating accurate recommendations can become more difficult.

Measuring AI Search Performance

A separate part of the discussion focused on measuring AI Search performance.

Tesco Media has access to purchasing behavior data from members of its Clubcard program. Such data could potentially help examine the relationship between products appearing in AI recommendations and actual sales.

For now, however, this is about developing measurement approaches rather than a ready-made, universal system for attributing purchases originating from ChatGPT.

Retail Media: AI, Automation, and Unified Performance Measurement

Retail Media was one of the central themes at CustomerX 2026. Organizers dedicated a separate Commerce Media Think Tank to the subject, bringing together discussions of technology, advertising inventory monetization, and performance measurement.

Representatives from Mars Europe, Kingfisher, Koddi, ISBA, Wayfair, OTTO Advertising, Rohlik Group, Moloco, OMD, Coop Media Network, and Kevel participated in the discussions.

Speakers included Nick East, Head of Retail Media at Mars Europe; Tom Blanchard, Senior Manager, Retail Media & Data Monetisation at Kingfisher; Paul Dahill, Managing Director, Sales EMEA at Koddi; and Clare O'Brien, Associate Media Advisor at ISBA.

Retail Media Network Architecture

One area of discussion concerned the architecture of Retail Media Networks.

Major retailers are developing their own advertising platforms, enabling manufacturers to promote products directly within online stores and use data on shopping behavior.

However, the development of these platforms brings challenges related to integration with traditional advertising systems, interoperability limitations, and differences in performance measurement methodologies.

AI-Driven Campaign Management

Another focus was the use of artificial intelligence in Retail Media management.

Representatives from Wayfair, OTTO Advertising, Rohlik Group, and Moloco discussed opportunities to use AI for campaign automation, inventory management, and performance optimization.

An important question is which tasks genuinely benefit from automation and which still require human expertise.

Business-Outcome-Based Media Planning

Changes in media planning approaches were also discussed separately.

Representatives from Mars Pet Nutrition, OMD EMEA, Coop Media Network, and Kevel examined the shift from selling individual ad placements toward planning campaigns around advertisers' business objectives.

Under this model, Retail Media should not be evaluated in isolation but as part of the overall media mix alongside Paid Search, Paid Social, video advertising, and other channels.

This requires comparable attribution methods, incrementality measurement, and analysis of advertising investment performance.

Social Commerce: TikTok and the Changing Customer Journey

Another important conference theme was the influence of social platforms on the process of discovering and purchasing products.

Much of the discussion centered on TikTok, which is gradually combining the functions of an entertainment platform, a search engine, and an e-commerce channel.

From Product Discovery to Purchase Intent

Giulia Yang, Growth & Partnership Manager at TikTok, presented the concept of a new customer journey shaped by social platforms and artificial intelligence.

In the traditional model, consumers first recognize a need, then search for a product, compare options, and make a purchase decision.

On social media, this sequence is changing.

A user may discover a product through an algorithmic recommendation, a creator's post, or a community discussion before developing any specific purchase intent.

AI tools complement this process by making it possible to quickly compare product attributes, obtain recommendations, and explore alternatives.

TikTok Shop and Cross-Channel Attribution

CustomerX also devoted attention to TikTok Shop and the impact of social commerce on sales beyond the platform itself.

A shopper may first encounter a product on TikTok but purchase it later through the brand's online store, a marketplace, or a traditional retailer.

This creates additional challenges for marketing analytics.

Evaluating TikTok performance solely through purchases made on the platform may overlook the influence of paid ads and organic content on branded search demand and sales through other channels.

For this reason, Social Commerce is increasingly viewed as part of a brand's overall commerce strategy rather than a standalone sales channel.

AI Personalization and Conversion Rate Optimization

Personalization of the customer experience also featured prominently in the CustomerX program.

Discussions focused on using AI and customer data to increase engagement, shorten the path to purchase, and improve conversion rates.

Interactive Video Commerce: Storyly and Sephora

One practical example was Storyly's work with Sephora.

Storyly representatives explored the use of interactive video content in mobile e-commerce applications.

Instead of traditional static product cards and banners, retailers can use short videos, product demonstrations, and interactive formats directly connected to product selection.

Such solutions make it possible to combine content and commerce actions within a single interface.

For example, shoppers can watch a demonstration of a beauty product and navigate to the corresponding product page without having to search for it in the catalog themselves.

This approach sits at the intersection of personalization, mobile UX, and Conversion Rate Optimization.

Wearable Data and Customer Personalization

Another aspect of personalization was discussed by representatives from Third Space, Vitality, and Holland & Barrett.

The discussion centered on using data from wearable devices and digital services to create more personalized customer interactions.

Unlike traditional loyalty programs based primarily on purchase history, these models can account for users' daily activities and individual preferences.

Alongside new personalization opportunities, managing user consent, ensuring transparency in data processing, and protecting personal information are becoming increasingly important.

Connected Commerce: Partnerships Beyond Traditional Retail

One distinctive feature of CustomerX was its discussion of commerce opportunities at the intersection of different industries.

The concept of Connected Commerce assumes that the customer experience is not limited to interacting with a single brand, store, or platform.

For example, watching a movie, traveling to an airport, or planning a trip can create several consumer needs at once.

Companies can use these situations to develop partner products, additional services, and joint advertising offerings.

Commerce Opportunities in Home Entertainment

Representatives from Just Eat, VEVO, and TikTok discussed commerce opportunities associated with entertainment at home.

An evening spent watching entertainment content may also involve ordering food, engaging with social media, and shopping online.

In this model, streaming services, delivery platforms, and social networks become participants in the same consumer occasion.

Contextual Commerce in Travel

Another example concerned the travel industry.

Representatives from Tripadvisor, Holiday Extras, and Pernod Ricard examined the commercial potential of engaging with airport passengers.

Within a relatively short period, travelers may use transportation services, make purchases, visit restaurants, and interact with advertising messages.

For companies, this creates opportunities for contextual advertising and personalized offers tailored to a particular stage of the journey.

Both discussions illustrate an evolving approach in which commercial offers are shaped not only by a user's membership in a particular audience but also by the current context and consumer intent.

Agentic Commerce: AI Agents and Automation of Commerce Processes

A separate part of CustomerX focused on Agentic Commerce, the use of AI agents to automate individual stages of product selection, purchasing, and commerce management.

AI Agents Across Multiple Platforms

During the CommerceAI Think Tank, participants discussed scenarios in which AI systems can independently analyze offers, compare product specifications, and perform actions on behalf of users.

This differs from traditional applications of AI in e-commerce.

While recommendation algorithms help shoppers choose products within an online store, AI agents could potentially interact with multiple independent platforms.

For example, an agent may be tasked with finding a particular product, comparing offers from different sellers, and generating recommendations based on price, delivery terms, and other requirements.

Automation Inside Retail Organizations

Another discussion focused on using AI to automate retailers' internal processes.

Representatives from Kingfisher, Booking.com, and Karo Healthcare took part in a discussion about the transformation of business models under the influence of artificial intelligence.

Topics included the automation of commercial functions, the use of data to create additional products, and the development of new revenue streams.

Within the broader program, participants also discussed demand forecasting, pricing management, and applications of AI in operational processes.

Agentic Commerce was therefore considered not only as a new interface for interacting with shoppers but also as a potential tool for changing internal e-commerce processes.

Conclusion: AI Is Becoming the Foundation of Digital Commerce Transformation

CustomerX 2026 continued a trend seen at the year's largest marketing and technology conferences: artificial intelligence has evolved from a standalone discussion topic into a common element across nearly every area of digital business.

From AI Experiments to Business Transformation

At the same time, the substance of these discussions is gradually changing.

While earlier conversations focused primarily on the capabilities of generative AI and experiments with new tools, companies are now increasingly discussing specific business processes that can be automated or redesigned using artificial intelligence.

• AI Search is changing how consumers discover and compare products.
• Retail Media is using automation to manage campaigns and measure performance.
• Social Commerce is creating new consumer behavior patterns.
• Agentic Commerce is opening up opportunities to automate product selection and commercial transactions.

Against this backdrop, the concept of Connected Commerce is taking on added significance.

The boundaries between search, advertising, content, and purchasing are becoming less distinct, and companies are seeking to bring these processes together into a unified customer experience.

CustomerX 2026 demonstrated that AI transformation in e-commerce is no longer being discussed as an isolated technology initiative, but as part of a broader reassessment of marketing strategies, commerce processes, and business models.