AI Campaigns Turn Global Brands into Personalisation Labs

Artificial intelligence is no longer a background tool in retail operations. Brands including Coca-Cola, Nike and Starbucks are using the technology to create campaigns that respond to individual preferences across millions of interactions. According to IDC's April 2025 analysis, AI technologies could generate a cumulative economic impact of US$22.3tn by 2030. That projection points to how marketing departments are viewing AI as a mechanism for growth rather than operational support.

According to McKinsey's State of AI 2025 survey, 88% of organisations now report using AI in at least one business function. That figure was 78% one year earlier. The shift could suggest that enterprises are moving from pilot projects to integrated systems that adapt based on customer data.

The campaigns these three brands have launched show different approaches to using AI in marketing. Each one addresses a specific problem or opportunity in how the brand engages with its audience. The implementations reveal how marketing technology is evolving from broadcast messaging to systems that learn from individual interactions and adjust in real time.

Coca-Cola's multilingual Santa campaign

The Coca-Cola Company launched its "Create Real Magic" holiday campaign in 60 days using Azure AI. The campaign enabled conversational interactions with a digital version of Santa across 43 markets and 26 languages. More than 1 million users engaged with the experience in three weeks.

"It all started with an iconic asset and a magical idea," says Pratik Thakar, Vice President and Global Head of Generative AI at Coca-Cola. "We wanted to create a first-of-its-kind holiday campaign by bringing to life the famous Sundblom Santa popularised by Coca-Cola back in 1931."

The campaign is part of a US$1.1bn commitment to cloud-based and gen AI capabilities through an expanded partnership with Microsoft announced in April 2024. That investment was expanded from an initial US$250m agreement in 2020.

Using Azure AI Foundry and global speech services, Coca-Cola created a custom Santa model that conversed in real time with more than 1 million people. The campaign allowed users to create personalised snow globes based on holiday memories they shared with Santa.

Pratik explains that the company wanted to create something new while staying authentic to its heritage. "With Microsoft's support, we co-created tools to solve complex technical challenges like multilingual lip sync for Santa's avatar," he says.

The technical achievement demonstrates how marketing campaigns can now operate across language barriers without losing the nuance of conversational interaction. The system processed regional dialects and cultural references specific to each market, adjusting tone and content based on local holiday traditions. This level of localisation would have required separate creative teams for each territory under traditional campaign structures.

Beyond marketing campaigns, Coca-Cola uses AI across operations. The Freestyle touchscreen fountain now collects customer preference data that informs product innovation and marketing strategies. The company analyses weather patterns, purchase history and social media engagement to deliver campaigns targeted to individual users.

The Freestyle machines generate data on flavour combinations that customers create themselves. Marketing teams use this information to identify emerging taste preferences before they appear in broader market research. Several limited-edition products have originated from patterns identified in Freestyle usage data, showing how operational technology can feed directly into campaign development.

Nike's conversational shopping assistant

Nike uses RFID technology in its House of Innovation flagship stores to recognise customers as they enter. The system offers personalised shopping suggestions based on data from their Nike profile including colour preferences, sports interests and foot measurements.

The Nike Fit feature scans customers' feet using smartphone cameras. According to Nike, 60% of individuals wear shoes that do not fit correctly. The technology captures 13 visual data points to create 3D foot models. That approach could reduce returns and improve customer satisfaction.

In March 2025 Nike introduced NikeAI Beta, a conversational AI assistant. The tool marks a shift in how customers interact with the brand by replacing browsing with conversation.

"It's a meaningful shift in how we connect our athletes with products that fit their needs, moments and goals," says Muge Erdirik Dogan, Executive Vice President and Chief Technology Officer at Nike.

The launch of Nike Adapt Link followed in March 2025. The sneaker contains embedded machine learning algorithms that adjust to the wearer's foot in real time using biometric sensors. Muge describes the product as the first AI-designed sneaker.

The conversational interface learns from each interaction, building a profile of how customers describe their needs. This linguistic data reveals patterns in how different demographics talk about athletic performance, comfort and style. Marketing teams can use these insights to adjust campaign messaging and product descriptions to match the language customers actually use rather than relying on focus group feedback.

According to Digital Commerce 360, Nike's online sales could reach US$8.15bn in 2025. That projection is supported by AI-driven personalisation that tailors product recommendations to individual users.

Starbucks's Deep Brew platform

Starbucks has built AI platforms through Deep Brew, powered by Microsoft Azure. The system analyses data from 17 million mobile app users and the broader Starbucks Rewards programme to deliver personalised recommendations, optimise store operations and predict inventory needs across 38,000 locations worldwide.

Deep Brew examines purchase history, location data, weather conditions and local events to craft tailored product suggestions. According to The AI Tool Report, the platform has produced a 30% increase in return on investment and 15% growth in customer engagement compared to earlier marketing methods.

"Advanced technology, the ability to deploy quickly and some advanced brains is a really nice unlock for Starbucks," says Brian Ames, Lead Manager of Data Science and Analytics Operations at Starbucks.

Customisable menu boards at drive-thru locations use AI to suggest items based on weather, time of day, store inventory and individual purchase history. Mobile orders now account for over 30% of US transactions according to The AI Tool Report.

Former Chief Operating Officer Roz Brewer previously said that every store in every country has its own personality. "Every store in every country has its distinctive personality, on top of other factors like weekday, time of day, temperature, amount of traffic," she said.

The Deep Brew system identifies micro-trends at individual store level that would be invisible in aggregated national data. A location near a university campus might show different purchase patterns during exam periods, whilst stores in business districts adjust recommendations based on meeting schedules inferred from order timing. This granular approach means marketing messages can reflect local context rather than applying uniform campaigns across regions.

The platform also tracks how customers respond to promotional offers, learning which types of incentives drive behaviour change for different segments. This feedback loop allows marketing teams to test messaging variations at scale and identify which approaches generate the strongest response before committing to broader campaigns.