Netflix, H&M, Starbucks: AI-led Marketing Strategies

The way brand equity is built and sustained is changing. 

As companies leave the experiential phase of AI, marketing teams are increasingly seeing the technology as a core tool for managing market reputation and identity.

In fact, research from McKinsey finds that AI could improve marketing ROI by up to 30%, while 86% of marketers say they are excited by the potential of AI in a marketing function.

Using AI in a branding strategy, however, requires teams to move away from traditional, static guidelines and focus instead on creating more fluid, intelligent systems.

Building this out can help marketing leaders build a more agile approach to branding – freeing up creative teams to focus more on high-level strategy and ensure that brand identity remains distinct and authentic.

Personalisation in the AI era

When creating a marketing campaign, it can be easy to forget the amount of noise it has to cut through. 

According to research by the University of Southern California, in the 1970s, people were exposed to approximately 500 advertisements per day.

Today, that number stands closer to 5,000 – with adults seeing an average of 2 million thirty-second commercials each year. 

Tailoring advertising to individual consumers can help with that.

Research by McKinsey finds that AI-driven personalisation can improve customer satisfaction by 15% to 20%, while Campaign Monitor found that 73% of consumers report that they would rather do business with brands that personalise their email communications. 

To truly personalise campaigns, marketers need to move towards more individualised, real-time interactions.

Using AI makes it possible for a company to analyse and act on consumer signals almost instantly, helping brands deliver more tailored experiences. 

Instead of creating a rigid, pre-scheduled campaign, AI tools can evaluate historical engagement, browsing behaviour and other situational factors to promote relevant content. 

Rapid responses

Since the advent of social media, marketers have been under more pressure to respond to trends. 

Traditional marketing models would often involve weeks of planning and execution to deliver a campaign – whereas today, some teams will have just a few hours to be a part of a key cultural moment. 

According to Adobe, more than one in five marketers feel the need to respond to trending topics daily or a few times per week, with 37% reporting burnout from the pressure of doing so. 

While many marketers are successful with this approach – with Adobe finding that 10% reporting to Adobe that trend-based content has led to referrals via LLMs, and 79% saying they gained new followers by taking part in a viral moment – 39% of marketers report content they made to take part in a trend failed due to rushing, making poor execution one of the most cited causes of failure for trending content. 

By using AI monitoring systems, brands can continuously evaluate digital forums  to identify emerging trends.

From there, marketing teams can generate and scale content – making it possible to rapidly create content that fits a trend while following brand guidelines. 

Improving customer experiences

But brands are using AI for more than online promotion – many companies are also using it to reinforce their brand messaging in person. 

For companies such as Starbucks, which makes premium customer experience a key part of its branding strategy, AI can help speed up processes and offer a smoother experience for customers. 

By bringing AI into in-person operations, brands can move beyond digital engagement to deliver a seamless, high-quality customer journey. 

This allows companies to consistently reinforce their brand identity and value proposition in physical settings, ensuring that efficiency enhancements directly support a premium and cohesive customer experience.

Netflix - Calibrated

In the US alone, Netflix has more than 5,000 titles on offer, available to an audience of 81.44 million users across the nation, according to the platform. 

To best match this wide-ranging audience with the titles that will keep them returning to the platform, the company has been increasing its use of AI-powered personalisation. 

To attract users to specific titles, Netflix uses personalised thumbnails and banners, with the platform’s recommendation engine dynamically assigning artwork variants based on user history.

Consumers regularly watching action movies, for instance, are more likely to see an action-heavy sequence as the thumbnail for a movie than a user who typically watches comedy movies. 

The company also introduced conversational search, which allows users to search for shows using natural phrases, such as saying they’re looking for something funny and upbeat – rather than having to manually search through a static comedy section. 

By personalising the user experience through AI, the company is simplifying it, making platform use more intuitive and engaging – helping to better retain users in the long term. 

H&M - Agility

Fashion marketing and promotion is changing faster than ever – particularly for high-street fashion brands like H&M, which are driven by sped up trend cycles often fuelled by social media. 

This has created an environment where fashion brands are continuously releasing and advertising new products, with the traditional Spring/Summer, Autumn/Winter trend cycle largely replaced by 52 ‘Micro-Seasons’ over the course of a year. 

But promoting this expanded product offering takes time – which is why H&M has begun showcasing new products using digital twin technology.

First launched in 2025, the company is using digital replicas of real human models to promote new products across social media and wider marketing campaigns. 

This allows H&M to place models in settings that may previously have been a logistical challenge, give the company complete control over the fit and styling of the clothes and reduce the environmental impact of international travel for models. 

Using AI, H&M can also remain agile – responding to new trends as they come and scaling international campaigns without the need for cost-heavy shoots.

Starbucks - Bespoke

Customer experience is a huge part of Starbucks’s branding strategy. 

The company’s business model and brand identity have been built around offering a premium experience to customers, from its positioning as a third place to its focus on personalisation. 

To strengthen that brand positioning, Starbucks has developed Deep Brew, its proprietary AI engine.

By studying customer purchasing history, Deep Brew can offer them bespoke drink recommendations and promotions, while also using predictive algorithms to schedule the right number of baristas for busy periods – helping customers have a smoother in-store experience. 

Initiatives such as these are being led by CEO Brian Niccol, who has been pushing a ‘Back to Starbucks’ rebranding campaign since taking on the role in 2024.

This strategy is focusing on revitalising the brand’s original identity as a welcoming space for customers and moving away from overly transactional service. 

Ultimately, the integration of AI allows Starbucks to offer bespoke interactions such as these, supporting its goal of returning to its roots