How AI-powered personalization is revolutionizing mobile marketing

AI-driven personalization in marketing has transformed the way marketing strategies are devised. As per a report by McKinsey, brands engaging in personalization gather 40% more revenue than others, and according to a study by Adobe, around 67% of consumers want personalized content and experiences. The global AI-based market is estimated to grow at a CAGR of nearly 13%. The Artificial Intelligence market in India is predicted to reach $6.26 billion in 2024 with a CAGR of around 28.65% within the years 2024-2030, hitting a market volume of nearly $28.36 billion by 2030 as per Statista.

Marketing powered by artificial intelligence enables brands to target their products and services tailoring to the specific tastes and preferences of the consumers with customised product recommendations. AI allows brands to gather and analyze vast amounts of customer data to derive insights about consumer behavior and devise marketing communication strategies accordingly. This results in higher consumer engagement and conversion rates leading to greater revenue and profit levels, reducing the time and capital required to analyze such large volumes of data. As per a report, AI-powered personalization establishes stronger relationships with consumers making them feel understood and valued. This, in turn, results in greater brand loyalty. Moreover, AI has the power to create personalized and diversified content that resonates greatly with the target audience. AI also enables predictive analysis, estimating the purchase behavior of the consumers and reducing chances of customer churn by targeting the right and relevant consumers who are more likely to buy a brand’s products and services.

For instance, e-commerce platforms such as Myntra, Amazon, Flipkart, etc., utilize AI-driven personalization methods and recommendations for curating products and collections that match the preferences and requirements of the target consumers. Netflix and Spotify utilize AI to recommend content and playlists that match the customer behaviour on the platform, catering to their specific interests and preferences. Personal care brand Sephora’s Beauty Insider Program utilizes product recommendations that are personalized to improve customer retention and loyalty. Starbucks’ mobile app uses AI to provide personalized discounts and offers by tracking the user’s purchase history, and location and by remembering the favourite drinks of the customers as per a report in PRmoment India. In this way, AI enables one-to-one brand experience and consumer engagement, fostering greater trust for the brands.

Adgully spoke with a cross-section of industry experts who provided valuable insights on how AI-powered personalization is transforming consumer engagement in mobile marketing.

Ayush Nambiar, Director, Flags Communications, noted, “AI-powered personalization is truly transforming the way brands engage with consumers. Today, we’re surrounded by an overwhelming amount of data, and the key for brands is how they mobilize this data. By using techniques like machine learning, brands can capture and analyze vast amounts of consumer data, which allows them to create highly personalized communications. This enables brands to not only connect with consumers in real time but also to address the strengths, weaknesses, opportunities, and threats that emerge from this data. The real benefit for brands is that it leads to deeper engagement, stronger loyalty, and, ultimately, higher conversion rates.”

Manas Gulati, Founder, ARMWorldwide, pointed out how the market today has become highly competitive, with consumers’ attention span becoming limited. He added, “Their choices are vast, which makes it harder for brands to capture and retain their attention. A blanket marketing approach, once considered effective, is no longer enough to keep consumers engaged.”

In response, personalization emerged as a powerful strategy, allowing brands to connect with consumers on a more meaningful and individual level. AI-powered personalization transforms how brands interact with consumers in mobile marketing, enabling them to deliver highly relevant content uniquely tailored to individual preferences.

“With advanced algorithms and deep consumer data insights, AI allows brands to predict what users want before expressing it. This shift is creating more engaging experiences that resonate with consumers personally. A prime example is Amazon, which uses AI to recommend products based on a user's past interactions, enhancing the shopping experience. Additionally, incorporating AI into mobile marketing opens up numerous opportunities for brands to enhance engagement, refine personalization, and improve ROI. Personalized content, such as push notifications and in-app messages, has proven to drive higher user engagement, leading to repeat purchases. In fact, according to Accenture, 91% of consumers are more likely to engage with brands that offer tailored recommendations and promotions. AI-driven personalization allows brands to deliver highly relevant and customized experiences across all consumer touchpoints, ensuring that the content resonates with users’ evolving preferences and behaviours, ultimately benefiting the brand.” Gulati elaborated.

Karishma Gupta, Partner, Deloitte India, said, “AI-powered personalization is revolutionizing mobile marketing by enabling brands to create highly customized and dynamic experiences that foster deeper consumer engagement. Through the use of machine learning, deep learning, and big data analytics, brands can now provide personalized content, offers, and recommendations in real-time.”

Enhanced Customer Targeting: By analyzing large datasets, such as browsing behavior, previous purchases, and social media interactions, AI can predict customer needs and preferences. For example, Starbucks’ Deep Brew platform customizes offers and suggestions based on factors like the customer’s time of day, order history, and even external influences such as the weather, making the experience more personalized and relevant.

Real-Time Content and Offers: AI enables brands to tailor content dynamically, ensuring that consumers see products that align with their interests. Sephora’s Virtual Artist is an example of this, using AI to let users virtually try on makeup and receive personalized product recommendations based on skin tone and preferences.

Localized Marketing Campaigns: AI is also used to adapt marketing strategies based on regional preferences. Swiggy, for instance, customizes food suggestions according to local tastes, while Nike sends location-based promotions, such as running shoes tailored for urban areas.

The AI-driven approach increases engagement by delivering targeted, location-specific offers. AI-driven personalization offers several benefits for brands, enabling them to create more relevant and engaging customer experiences that ultimately drive loyalty and conversions.

Higher Customer Retention: Personalized marketing efforts powered by AI increase relevance, leading to better retention rate. Spotify’s AI algorithms curate Discover Weekly playlists based on users’ listening history, keeping them engaged and increasing retention.

Marketing Efficiency: Flipkart uses AI-driven systems to personalize content and display the most relevant advertisements to users. These systems estimate how likely a customer is to click on an ad and how that click translates into a purchase. By optimizing both the customer experience and revenue generation, Artificial Intelligence is revolutionizing how Flipkart operates and enhancing overall efficiency and innovation.

Increased Conversions: Personalization leads to improved customer experiences and higher conversion rates. Myntra, for example, employs AI to provide product recommendations tailored to individual style preferences with its ‘My Stylist’ AI, reducing cart abandonment and boosting sales.

Prof Ashish Desai, Associate Professor of Information Management and Analytics at SPJIMR, elaborated, “When we travel, we create memories; when we speak, we leave impressions; when we walk on sand, we leave footprints. Similarly, using a mobile device leaves a digital footprint through SMS, call records, geolocations, and websites visited. Mobile applications and platforms leverage this data, often referred to as ‘Big Data’, for personalization. This data is collected with user consent at the time of app download and processed using advanced computing power and skills. AI enables mobile marketing companies to analyze vast volumes of data in real time, identifying trends and offering personalization. It adjusts content and advertisements based on user interactions. For instance, if a user explores specific products, AI triggers related ads or notifications. Similarly, it can predict user behaviour, such as promoting a music genre a user often plays after ordering a burger, thereby anticipating needs and offering suggestions before users request them.”

He further added, “Mobile applications do not sell consumer data, but provide marketing services to brands. Brands use this data through ‘Data as a Service’ to profile customer segments and develop personas that align with their requirements. This helps create engaging, tailored consumer experiences and enables effective ‘calls to action’, especially for low-involvement, instant-gratification, or low-cost products. Compliance with data protection laws is crucial. Applications must ensure informed consent, transparency in data collection, and robust security for storage. AI now analyses digital footprints in real time, allowing brands to deliver personalized content and predictive insights. This empowers marketers to anticipate needs and craft strategies tailored to individual users or address a ‘segment of one’.”

"AI-powered personalization is changing the way we view mobile marketing by enabling brands to create hyper-targeted, contextually relevant experiences at scale. Unlike traditional segmentation, AI allows marketers to analyse massive datasets in real time, learning from user behaviour, preferences, and even micro-interactions to deliver precisely customised content. This leads to increased engagement, higher retention, and improved conversion rates. AI-powered personalization offers several key benefits for brands. It helpsROI by precision targeting, which minimises wasted ad spend and boosts campaign efficiency. Personalised experiences also cultivate stronger customer loyalty by creating deeper emotional connections, making customers feel seen and valued. Furthermore, AI systems enable real-time adaptability, adjusting content or offers based on changing user behaviour to ensure relevance at every touchpoint. In essence, AI-powered personalization is a technological advancement and a paradigm shift in how brands engage with consumers" said Sindhu Biswal - CEO & Founder of Buzzlab.

 Rajesh Ghatge, CEO - Wondrlab Technologies & Founding Team Member (Wondrlab) shared: "AI-powered personalization has emerged as a game-changer in mobile marketing. By harnessing the power of AI, brands can now deliver hyper-personalized experiences that resonate with individual consumers. Personalized experiences foster a sense of loyalty and belonging. By tailoring content, offers, and recommendations to individual preferences, brands can elevate customer satisfaction and build lasting relationships. AI-driven personalization enables brands to deliver highly targeted messages at the optimal moment. This precision significantly boosts conversion rates and drives sales. By identifying high-value customer segments, brands can allocate marketing budgets more effectively. This reduces wasted spend and maximizes ROI. Personalized interactions deepen customer relationships, encouraging repeat purchases and brand advocacy. This translates to a higher customer lifetime value. Take the case of a beauty retailer, the brand can leverage AI to analyse customer purchase history, browsing behaviour, and social media activity. This data-driven approach could be used to recommend products, offer personalized discounts, and send targeted marketing messages. This personalized strategy is most likely to increase customer engagement and sales."

"AI-powered personalization is truly an important consumer engagement in mobile marketing. At its core, it enables brands to connect with users on a more individual level by delivering experiences tailored to each person's preferences, behavior, and interactions. For example, studies show that 80% of consumers are more likely to purchase from brands offering personalized experiences (Epsilon). By analyzing real-time behavior, brands not only increase engagement and loyalty but also stay ahead of shifting trends. It's about creating connections that make users feel understood, not marketed to. For brands, the benefits are huge. Personalization boosts engagement by making marketing feel more relevant and timelier, which increases the chances of a conversion. But it doesn’t stop there; personalized marketing also builds stronger loyalty, as consumers are more likely to stick with a brand that really 'gets' them. And by understanding consumer behavior in real-time, brands can stay ahead of the curve, adjusting their approach as trends and preferences shift. In short, AI-powered personalization helps brands become more adaptive, responsive, and valuable to their customer" said  Sahaan Suman K, Founder of Bubble Network.

Role of AI-driven data analysis in enhancing mobile marketing strategies

AI-driven data analysis plays a pivotal role in fine-tuning mobile marketing strategies, said Ayush Nambiar, explaining, “It allows brands to dive deep into consumer behaviour, predict trends, and tailor their messaging accordingly. The real power of AI is that it evolves – learning from the data it processes and continually refining its techniques. AI is nothing but data, responding to data based on data. However, with this power comes responsibility. Brands need to balance personalization with privacy by being transparent about how they collect and use data. Consumers should have control over their information. If handled responsibly, AI-powered personalization can greatly enhance the customer experience without violating privacy.”

AI’s ability to process vast amounts of data to provide precise insights has the potential to make mobile marketing campaigns more effective and user-centered. Its ability to analyze consumer behaviours, preferences, and trends allows for highly personalized marketing, ensuring that users receive content tailored to their interests. Real-time analysis further enhances this by enabling campaigns to adjust quickly to shifts in consumer behaviour, keeping strategies current and effective.

Manas Gulati elaborated on this, citing the example of a food delivery app predicting when a user is likely to order dinner based on past habits, then send a well-timed notification with a discount on their favorite dish. “Moreover, AI improves targeting by identifying specific audience segments, enhances efficiency through automation, and refines user experiences by analyzing feedback to improve app designs. Maybe you have noticed how some apps seem to “know” exactly what you want – that’s AI working behind the scenes to make your experience effortless. For example, Netflix’s recommendation engine, driven by AI, suggests content tailored to individual preferences, resulting in 80% of the content watched being influenced by these insights. Additionally, AI allows brands to optimize targeting, improving the relevance and impact of mobile campaigns,” he added.

At the same time, Gulati cautioned, “However, the use of AI in personalization comes with privacy concerns. Consumers are increasingly cautious about how their data is being used. Studies show that 79% are worried about data privacy. To balance personalization with privacy, brands must adopt transparent data practices. Additionally, offering opt-in choices and clear communication about data usage can help maintain consumer trust. Ultimately, AI’s ability to optimize marketing efforts while safeguarding user privacy helps businesses build stronger relationships with their audience. Brands can maintain a competitive edge and cultivate customer loyalty by protecting data and providing relevant content.”

Karishma Gupta commented, “To enhance mobile marketing strategies, AI-driven data analysis plays a crucial role by delivering real-time insights, forecasting trends, and enabling hyper-targeted campaigns that deeply resonate with customers.

Real-Time Insights and Predictive Analytics: AI continuously analyzes customer interactions, adjusting marketing strategies in real time. Amazon’s recommendation engine, for example, processes customer actions on the fly to suggest products immediately, resulting in increased engagement and sales. Similarly, Walmart’s AI system, for example, predicts when customers are likely to need certain items, sending them personalized promotions and reminders.

Campaign Execution Efficiency: AI identifies high-performing ad formats, channels, and timeframes, enabling brands to allocate budgets effectively and maximize ROI. Simultaneously, AI-powered tools optimize messaging and creatives for different audience segments, ensuring campaigns remain relevant and impactful. (Example: Salesforce Einstein)

Seamless Customer Journey: AI automates data processing and analysis, reducing the time and resources needed to create personalized marketing campaigns. HDFC Bank’s EVA, an AI-powered virtual assistant, not only improves customer support, but also assists in generating leads and recommending financial products, which boosts efficiency and reduces operational costs.”

Sindhu Biswal - CEO & Founder of Buzzlab commented: "AI-driven data analysis acts as the nerve centre of modern mobile marketing strategies. It transforms raw data into actionable insights by identifying patterns, predicting future behaviours, and automating decision-making processes. This capability enables marketers to design campaigns that feel intuitive and preemptive, significantly enhancing user engagement and satisfaction. As the saying goes, with great power comes great responsibility. So is the case when it comes to balancing personalization with privacy demands. Brands must prioritise transparency by clearly communicating how they collect and use data, garnering trust through openness. Privacy-first personalization techniques, such as federated learning and anonymized data analysis, enable customised experiences without compromising individual privacy. Additionally, adhering to regulatory frameworks like GDPR and CCPA is essential, as compliance is not optional but a fundamental requirement for ethical AI usage. The future will belong to brands that can ethically navigate this dual mandate of personalization and privacy, proving that consumer trust is the ultimate KPI."

 Rajesh Ghatge, CEO - Wondrlab Technologies & Founding Team Member (Wondrlab) noted: "AI has  revolutionize mobile marketing by enabling hyper-personalized campaigns by Identifying User Segments. By analyzing vast amounts of user data,AI algorithms can identify intricate patterns and behaviors, clustering users into highly targeted segments. This granular segmentation goes beyond traditional demographics like age and gender, considering factors such as:

• App Usage Patterns: AI can analyze how frequently users open the app, the time spent within it, and the specific features they engage with.
• In-App Purchases: By tracking purchase history, AI can identify high-value customers, impulse buyers, and those with specific product preferences.
• Push Notification Interactions: Analyzing user responses to push notifications can reveal preferences for certain messaging styles, times, and content.
• Geolocation Data: Understanding users' physical locations can help target location-based promotions and tailor content to local interests.

With these insights, marketers can create highly targeted campaigns that resonate with specific user segments, increasing engagement and conversions.

Further AI-powered predictive analytics can help mobile marketers identify users at risk of churning before they take action. By analyzing a multitude of factors, such as app usage frequency, in-app purchases, and customer support interactions, AI can predict churn probabilities for individual users.

Early detection of churn allows marketers to implement timely retention strategies, such as:

• Personalized Offers: Tailored discounts, loyalty rewards, or exclusive content can entice users to stay engaged.
• Proactive Customer Support: Reaching out to at-risk users with proactive support can address their concerns and improve satisfaction.
• Targeted Marketing Campaigns: Reminding users of the app's value proposition and highlighting new features can rekindle interest.

By proactively addressing churn risks, businesses can reduce customer attrition and maintain a loyal user base."

He further added: " Lastly AI can optimize mobile ad spending by identifying the most effective channels and audiences. By analyzing real-time data on ad performance, AI algorithms can:

• Identify High-Performing Channels: AI can determine which channels (e.g., Meta, Google, Instagram) deliver the best ROI, allowing marketers to allocate budgets accordingly.
• Optimize Ad Creative: AI can analyze the visual and textual elements of ads to identify the most effective combinations, improving click-through rates and conversions.
• Real-Time Bidding: AI-powered bidding systems can automatically adjust bids in real-time to maximize the chances of ad impressions and clicks, ensuring optimal ad spend.
• Audience Segmentation: AI can identify the most receptive audience segments for specific ad campaigns, ensuring that marketing efforts are targeted to the right people.

By leveraging AI to optimize ad spend, businesses can maximize their return on investment and achieve better results with their mobile marketing campaigns.

While personalization is a powerful tool, it's crucial to balance it with consumer privacy concerns. To build trust and maintain a positive brand reputation, responsible brands have been seen to prioritise 

• Transparency : Clearly communicating data collection practices and how user information is used.
• Offering  Control: Empowering  users to manage their privacy settings and opt out of personalization.
• Implementing  Robust Security: Protect user data with advanced security measures.
• Comply with Regulations: Adhere to relevant data privacy regulations, such as GDPR and CCPA."