In today’s fast-evolving digital ecosystem, where customer journeys are no longer linear and consumer expectations are at an all-time high, the ability to deliver unified, hyper-personalized, and measurable experiences has become the ultimate differentiator for brands. In this exclusive conversation with Tech Achieve Media, Medhavi Singh, Country Head at Criteo India, shares how artificial intelligence is transforming commerce by connecting fragmented data, enabling intelligent personalization at scale, and powering the next era of marketing and retail. Medhavi also offers deep insights into how businesses can harness AI-driven innovation to future-proof themselves in an increasingly competitive landscape, including breaking down data siloes to leveraging generative AI for real-time content and campaign optimization.
TAM: How is AI transforming the way brands and consumers interact across diverse platforms to create seamless and unified experiences?
Medhavi Singh:AI is fundamentally transforming the way brands and consumers engage by enabling personalized, relevant interactions at every stage of the shopper journey. Through advanced data analytics, AI can anticipate consumer needs, tailor content and product recommendations, and deliver consistent messaging across digital touchpoints. It bridges gaps between platforms, ensuring that consumers experience a unified journey regardless of where or how they engage.
Also read: Navigating India’s Retail Media Boom – Medhavi Singh, Criteo India
For me, the real value lies in how AI lets us bring together fragmented touchpoints into consistent, meaningful conversations, whether on websites, apps or retail media networks. This level of intelligent personalization improves engagement, reduces consumer drop-offs, and enhances the overall shopping experience. What we ultimately create is a more connected, efficient, and frictionless path to purchase that respects user preferences while driving better outcomes for businesses.
TAM: How do data siloes hinder seamless customer experiences, and what role does AI play in breaking down these barriers to enable a more cohesive strategy across platforms?
Medhavi Singh: Data siloes limit visibility and hinder brands from delivering coherent, meaningful customer experiences. When data is scattered across systems, marketing messages often become disjointed or redundant. AI emerges as a powerful solution by seamlessly integrating data across previously isolated systems, employing machine learning algorithms to identify patterns within disparate datasets, and generating unified customer profiles that update in real-time across all platforms.
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What excites me is how this empowers marketers to align creative, targeting, and timing strategies seamlessly across platforms. As a result, AI helps brands replace fragmented customer journeys with cohesive, context-aware experiences that enhance both customer satisfaction and business performance.
TAM: What strategies do AI-powered solutions employ to deliver measurable business outcomes, and can you share some recent success metrics?
Medhavi Singh: In the current digital landscape, AI-powered solutions are essential for businesses to stay competitive, agile, and customer-centric. They enable organizations to process vast amounts of data in real time, extract meaningful insights, and make faster, smarter decisions.
At Criteo, our Commerce Media Platform processes billions of daily shopper intent signals to predict purchase behaviour and adjust campaigns dynamically. Key strategies include AI-driven audience scoring, dynamic creative optimization, and intelligent bid management ensuring each ad impression maximizes relevance and conversion potential.
For example, Maison MRKT, a leading digital marketing agency deployed Criteo’s commerce growth solutions to successfully boost performance for their client Xirena through fast, goal-driven campaign activation. In a one-month test, the AI-optimized approach delivered a 23% higher ROAS, a 40% increase in sales, and a 20% revenue surge, all at comparable spend. The streamlined setup and rapid launch enabled Maison MRKT to efficiently drive measurable growth and maximize marketing impact.
So, you can clearly see, how these outcomes demonstrate how AI not only improves targeting and campaign efficiency but also consistently delivers tangible, scalable business value for brands.
TAM: How is generative AI redefining hyper-personalized shopping experiences, and what challenges does it overcome in achieving scalability?
Medhavi Singh: Generative AI is redefining hyper-personalized commerce by creating dynamic, tailored content at scale. It automates ad creative, product recommendations, and promotional messaging in real time, based on individual preferences and behaviours. It also enables brands to go beyond basic segmentation and instead create uniquely engaging experiences that adapt in real time to changing behaviours. This overcomes traditional scalability challenges associated with personalization, where brands struggled to manage millions of unique customer journeys. By automating insights and creative generation, generative AI ensures relevance at scale.
Through its Commerce Media Platform, Criteo is at the forefront of this evolution by using AI to analyze billions of shopping intent signals daily, dynamically optimize ad creatives, and deliver performance-driven personalization that boosts conversions and ROI for brands. This approach not only elevates consumer engagement but also allows brands to scale personalization efficiently without compromising on precision.
TAM: As AI reshapes commerce, how should retailers and brands rethink their technology investments to remain competitive and future-proof?
Medhavi Singh: As AI continues to reshape commerce, retailers and brands must rethink their technology investments by prioritizing hyper-personalization to remain competitive and future-proof. In an era where every shopper is unique, traditional one-size-fits-all approaches no longer deliver results. AI enables businesses to process vast amounts of data in real time, unlocking deep insights into individual preferences, behaviours, and intent. The future will belong to businesses that can connect data from diverse sources, predict consumer intent, and automate decision-making across media, retail, and commerce ecosystems.
By leveraging this intelligence, we have the ability to create tailored experiences, from personalized product recommendations and dynamic pricing to bespoke marketing campaigns, ensuring that each customer interaction feels relevant and meaningful. Investing in AI-driven personalization not only enhances customer satisfaction and loyalty but also drives higher conversion rates and long-term business growth in an increasingly competitive landscape.
TAM: What emerging trends in AI commerce do you foresee reshaping the retail industry in the next five years, and how can businesses adapt?
Medhavi Singh: AI-driven commerce is poised to fundamentally reshape the retail industry, and I truly believe we’re only just beginning to see its full impact. With the rise of hyper-personalization, predictive analytics, autonomous shopping experiences, and AI-powered customer service, the expectations of today’s consumers are evolving rapidly, and retailers will need to harness AI to meet them. From product recommendations and dynamic pricing to real-time inventory management, AI is becoming essential to delivering personalized, seamless experiences at scale.
Retail media networks will become essential for advertisers seeking first-party data access, while generative AI will automate content creation, making hyper-personalization scalable. Predictive commerce will emerge, allowing AI to anticipate consumer needs before explicit intent signals surface. Additionally, AI-powered automation platforms will simplify campaign management and optimize full-funnel strategies in real time. Brands that invest early in AI-driven MarTech, build strong data partnerships, and focus on agile, context-aware personalization will gain a competitive edge in this evolving landscape.
To stay competitive, businesses must invest in unified data infrastructure, ethical AI practices, and agile digital transformation strategies that enable continuous learning, experimentation, whilst keeping personalization at its core.
