AI in Retail Media: Latest Trends and Benefits

The rapid rise of e-commerce platforms and retail media networks has changed the way brands connect with consumers. Now digital experiences are an integral part of the interaction between retailers and shoppers. Amid this shift, online shopping platforms have transformed into powerful advertising platforms that can deliver highly efficient ads. However, such changes wouldn’t have been possible without relevant technologies, and AI is one of them. What is the role of AI in retail media? That’s one of the key questions that we will answer in this blog post.

AI-powered tools are now essential for processing vast datasets and optimizing ad targeting to drive sales and customer engagement. But how can retailers achieve this? Let’s dive deeper into this topic.

Role of Artificial Intelligence in Retail Media

AI can revolutionize retail media by making ads smarter, more efficient, and more personalized. By enhancing every stage of the marketing journey, it allows brands and retailers to maximize their benefits.

Here are the key examples of using AI in retail media.

• Hyper-personalization. With the help of AI, businesses can get access to dynamic profiles of individual shoppers. Such profiles are created based on insights into their behavior, purchase history, and real-time intent signals. This procedure allows brands to deliver tailored, relevant ad messages. Such personalized ads can drive sales, ensure a higher return on ad spend (ROAS), and boost customer loyalty.
• Programmatic advertising. AI-powered programmatic platforms can analyze billions of data points practically in no time, which makes it possible to detect the most relevant places to publish ads for the right audience. Such tools help businesses optimize ad spend by bidding efficiently on high-value impressions.
• Dynamic creative optimization (DCO). Artificial intelligence enables brands to create automated, high-performing ad creatives tailored to different audiences and contexts. For example, AI can adjust headlines, images, colors, and calls to action based on user behavior, geolocation, and purchase stage. Generative AI in retail media also plays an important role today. Such tools can be used to create adaptive ad messages and visuals that can be automatically changed based on real-time conditions like cultural events or seasons.
• Dynamic pricing. AI can efficiently adjust product prices and promotional offers in real time based on various factors, including ongoing demand trends, inventory level, competition, and customer behavior. Such tools ensure that products are priced competitively and profitably. If the demand for some items has skyrocketed, the price will go higher as well. At the same time, AI can identify price-sensitive customers and provide personalized discounts to increase conversion rates.
• AI-driven sponsored products and search ads. Artificial intelligence can be applied to optimize paid search and sponsored product ads to maximize visibility and engagement. This technology can predict the likelihood of a shopper clicking on an ad and adjust bidding strategies accordingly to maximize ROAS. It also can enhance search algorithms to prioritize the most relevant products in search results and ensure relevant ads appear in high-impact placements for relevant keywords.
• Automation and real-time insights. As well as in any other industry, AI in retail media can automate multiple routine and time-consuming tasks, including but not limited to media buying, audience targeting, and budget allocation. Apart from automating media planning and campaign workflows, AI can provide actionable insights. It can analyze ad performance in real time and automatically adjust campaigns to improve efficiency. Such data can also be used for planning future campaigns.
• Predictive analytics. Predictive models help brands and advertisers anticipate trends and allocate ad budgets effectively with maximum ROI. Moreover, provided recommendations help to avoid situations where ads actively promote items that are out of stock.

AI Technologies Used in Retail Media

AI’s impact on retail media is driven by a range of advanced tools that enhance personalization, automation, and decision-making. But what are the underlying technologies that make these innovations possible?

Machine Learning (ML)

ML algorithms demonstrate high efficiency in processing massive datasets, identifying patterns, and detecting similarities. That’s why they are often applied to analyze consumer behavior, preferences, and purchase history to refine audience segmentation.

Apart from that, the use of this technology enables real-time ad targeting and bid adjustments. Thanks to ML, advertisers and brands can be sure that their ads reach the right consumers at the right time.

Natural Language Processing (NLP)

The achievements made in the development of NLP prepared a solid foundation for the creation of advanced chatbots and virtual assistants. Conversational AI in retail can handle customer inquiries, assist with product recommendations, and provide instant support while reducing load for human agents.

NLP enhances voice search accuracy and allows shoppers to find products using descriptive queries.

Apart from this, NLP-powered AI tools are able to assess customer feedback from reviews and social media. This process helps brands understand consumer sentiment and refine marketing strategies.

Computer Vision

This technology can greatly facilitate and streamline the search process for consumers. When images are used in place of text, users can quickly locate the necessary items.

Moreover, computer vision is used for in-store analytics. Such solutions rely on cameras to track customer movement, shelf engagement, and dwell time. Gained insights help optimize store layouts and enhance merchandising strategies.

AI-Driven Recommendation Engines

AI can analyze browsing history and purchase behavior to suggest relevant products for each user. It can also enhance cross-selling and upselling by predicting complementary products that a shopper may need.

AI in Retail Media: Real-World Examples

AI technologies play a crucial role in transforming retail media, enabling more precise targeting, enhanced customer engagement, and improved operational efficiency. But how do these technologies translate into real-world applications? Let’s explore how major retailers are leveraging AI to enhance their retail media strategies.

Visual search and conversational interface by ASOS

The visual search feature became available to ASOS online shoppers in the UK in 2017. Being powered by AI, this tool can detect the shape, color, print, and many other parameters in the uploaded image to offer similar options. This opportunity greatly streamlines the search process and inspires discovery.

https://www.asosplc.com/

In 2024, in cooperation with Microsoft, ASOS introduced AI Stylist, a new Azure OpenAI-powered conversational interface that will help customers discover new looks faster and more easily.

Amazon DSP and AI-powered ads

Amazon is continuously expanding the range of its AI-powered tools. In 2024, Amazon Ads launched new generative AI tools for advertisers: AI Creative Studio and Audio Generator. Now brands can use all media formats, including images, video, and audio, to deliver their engaging content to consumers.

https://www.aboutamazon.com/news/

At the same time, the company announced a range of innovations for its demand-side platform (Amazon DSP). For example, it enhanced its automated optimization tool dubbed Performance+. It uses AI and advertiser input to automate audience relevancy and campaign optimization for lower funnel goals. The tool drives a 51% improvement in customer acquisition costs and now will include remarketing and retention tactics.

Challenges of Implementing AI in Retail Industry

Real-world examples from leading companies show that AI implementation in retail media can be highly successful. However, adoption of this technology isn’t always seamless, as there are certain factors that can pose significant barriers. Though at the moment it isn’t possible to fully eliminate them, retailers and businesses behind retail media systems can try to address these issues to minimize their negative consequences.

Data privacy and regulatory compliance

Retail media relies heavily on consumer data to personalize advertising and improve targeting. However, privacy laws like GDPR and CCPA that are in force in different jurisdictions require businesses to be more transparent and responsible with data collection and usage.

According to these regulations, businesses are obliged to obtain user consent before collecting data, provide options to decline data sharing, and allow users to access or delete their data. Non-compliance can lead to serious fines and reputational damage.

How to address this issue?

• Implement transparent data collection practices with clear consent mechanisms;
• Make privacy policies easy to understand;
• Clearly explain how customer data is collected, stored, and used;
• Allow users to view, modify, or delete their data;
• Provide easy opt-out options for personalized ads and tracking;
• Anonymize data used for AI training and allow AI models to learn from user data without revealing personal information;
• Encourage users to willingly share data through loyalty programs and surveys;
• Encrypt all stored and transmitted data to prevent unauthorized access;
• Conduct frequent internal audits to ensure adherence to the relevant privacy regulations;
• Cooperate with external compliance officers to identify potential vulnerabilities.

Bias in AI algorithms

AI models can’t be fairer than the data they are trained on. If the training data contains biases, AI can only reinforce them in retail media campaigns.

This assertion is absolutely true in relation to any type of data retail media tools may need, including gender, ethnicity, income level, location, and many other parameters.

How to address this issue?

• Use diverse and representative data to train AI model;
• Conduct regular audits of AI models and datasets to identify and mitigate bias;
• Implement fairness-aware AI algorithms to avoid discrimination of any social groups;
• Introduce human oversight and ethical AI governance frameworks.

The right balance between personalization and trust

Personalization is a key advantage of AI in retail media. However, over-personalization can seem frustrating and even frightening, which can lead to privacy concerns. Consumers want to see that their needs and preferences matter, but they don’t want to feel like somebody is watching them 24/7.

Many consumers don’t know how their data is used or why they get certain recommendations. Their ignorance can result in distrust in such systems.

How to address this issue?

• Implement explainable AI to make recommendations more transparent and understandable to consumers;
• Avoid bombarding users with repetitive ads for the same product;
• Provide value in exchange for personalization, such as exclusive discounts or loyalty rewards tailored to purchases;
• Deliver ads based on real-time context, such as the content a user is viewing.

Future of AI in Retail Media

With all the benefits that this technology brings to retail media, it’s obvious that AI is here to stay. But how will it develop in this space? What are the new tendencies that brands and retailers should watch out for? To find the answers to these questions, examine the key trends expected to shape the retail media industry soon.

Trend 1. AI-powered virtual stores and metaverse shopping

AI will continue its development. And it is expected that the next stage of retail media evolution will be the introduction of AI-powered virtual shopping environments, where digital-first, immersive experiences will become a standard.

Smart virtual assistants will recommend items to shoppers, who can use digital avatars to try on clothes.

At the same time, voice-activated commands and gesture-based interactions will ensure a hands-free experience and increase the inclusivity of online shopping.

Trend 2. Further AI adoption for omnichannel retail strategies

Omnichannel strategies presuppose the integration of all available channels and touchpoints, including online and offline platforms, to deliver consistent experiences for customers. Artificial intelligence helps to accumulate both in-store and online shopping data, which gives retailers a 360-degree view of consumers.

Wise use of AI tools increases ad efficiency and drives conversions while also positively impacting customer satisfaction.

Omnichannel Retail Media: How to Implement Your Advertising Strategy Across Platforms

Read our article to find out what value omnichannel retail media can bring and how to overcome its most common implementation challenges.

Trend 3. Autonomous AI shopping agents

Future AI agents will act as personalized shopping assistants that will help consumers make real-time purchasing decisions. They will be able to seek products based on users’ requests, compare prices, and suggest the best deals.

Additionally, such agents will be able to automatically reorder frequently bought items when supplies are low based on users’ preferences and habits.

Trend 4. Investment growth in AI for retail media

With the success of retail media networks and AI’s role in it, investments in this space are expected to keep growing.

Experts predict that the retail AI market will reach a size of approximately $52.94 billion by 2029. To put it in perspective, this market volume was $4.84 billion in 2021.

It is expected that retailers will continue to invest in AI to gain a competitive edge and deliver superior customer experiences.

Final Word

We won’t exaggerate if we say that today AI is shaping the retail media landscape, making advertising strategies smarter and more result-oriented. While enhancing customer engagement, brands can maximize their ad efficiency and boost sales.

As the retail media industry continues to expand, AI will play an even greater role in automating processes, building seamless omnichannel interactions, and offering new unique shopping experiences. Namely, AI will make this space more dynamic and creative than ever before.

And while today the use of AI may be viewed as a competitive advantage and innovation, quite soon it can become a must for every retailer that wants to stay afloat.