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    Business

    Posted By Wanda Rich

    Posted on July 3, 2025

    Featured image for article about Business

    By Vinod Sivagnanam

    The illusion of choice in personalized e-commerce

    Think back to your last online purchase… Ask yourself how you chose to buy this item. Where, when and how did the purchase journey begin? Odds are an AI-driven algorithm nudged you into making this purchase.

    In today’s algorithm-powered systems, e-commerce is no longer a neutral space for consumer choice. It is a meticulously engineered experience driven by Artificial Intelligence (AI).Leading retailers deploy personalization engines that analyze real-time behavioral signals, historical purchases, and aggregated demographic data to shape what products, content and ads customers see.

    Retailers have a strong incentive to use personalization – companies that excel at personalization drive 40% more revenue than their competitors that do not (McKinsey, 2021) and up to 30% of e-commerce sales can be attributed to these systems. Yet this revenue maximizing strategy comes at the cost of eroding customer trust. Two-thirds of consumers exposed to these personalization algorithms report negative experiences, often citing feelings of manipulation (BCG, 2024). As AI agents begin to handle entire shopping journeys, an autonomy crisis emerges where customers are no longer truly “shopping” but are instead being “shopped” by invisible systems designed to optimize conversion, not conscious choice.

    Made for me: Why shoppers crave personalization

    Shoppers increasingly embrace personalized e-commerce experiences because these algorithms streamline purchase decision-making and enhance search relevance. At its core, these systems satisfy modern shoppers’ desire for convenience and transform routine transactions into meaningful, user-centric experiences. The perceived benefits of personalized experiences are so high, that tailored recommendations have become an expectation and cause frustration when absent (McKinsey, 2021).

    The autonomy trap: when personalization transforms into manipulation

    But the very systems that offer ease and delight may also restrict autonomy in subtle and systematic ways. Personalization in e-commerce comes with the promise of enhanced convenience and reduced friction by tailoring recommendations that are highly relevant to individual customers. However, with enough behavioral and clickstream data, these powerful systems train themselves to provide recommendations which may obscure the line between meaningful choice and algorithmic steering. With highly curated ads, search results, and dynamic pricing and promotions, customers are increasingly interacting with online platforms aimed at maximizing engagement and conversion. Even if a customer chooses not to engage with a recommendation, it adds behavioral signals to the system, arming it with more data to make the next recommendation more relevant. While customers initially feel empowered to make quicker purchase decisions with personalization, over time they lose exposure to alternative product choices which significantly reduces decision diversity. Furthermore, algorithmic decision-making can unintentionally reinforce demographic biases. At scale, personalization transforms from a tool for relevance into a mechanism of control – shaping customers’ perception of the product selection available to them and compromising their choice agency. Instead of enabling informed choices, algorithms begin nudging behavior toward outcomes that primarily serve business interests.

    This raises an important question: who is personalization serving? The customer or the retailer’s business objectives?

    Hyper-relevant or just plain creepy?

    Ever talked about a product with friends and later seen it pop in your online ads or product recommendations?

    Shoppers are becoming increasingly aware to the subtle changes in their online shopping journeys.As AI systems become more sophisticated in tracking and predicting customer behavior, many are beginning to feel an unsettling sense of exposure. Many customers feel that AI systems “know them too well” and express discomfort with how accurately AI systems anticipate their needs and interests (BCG, 2024). The notion of “hyper relevance” can lead to feelings of being surveilled, with users questioning how much of their personal data has been harvested to feed recommendation engines. In some cases, this can trigger behavioral backlash, with shoppers disabling personalization features, shopping anonymously, or avoiding e-commerce platforms altogether.

    Responsible personalization: a true competitive advantage

    While personalization and AI tools have unlocked undeniable convenience and commercial value, they must be kept in check to maintain customer autonomy. The penetration of personalization in e-commerce has introduced significant ethical concerns about customer autonomy. Over time, shoppers may become reliant on algorithmic curation to the point where independent decision-making atrophies. The subtle erosion of autonomy is compounded by the fact that consumers are rarely aware of how much their experience is being shaped behind the scenes. Left unchecked, this dynamic risks turning shoppers into passive participants in their own purchase journeys, increasingly disconnected from the broader marketplace and their own critical evaluation skills.

    Retailers must strike the right balance between personalization and customer autonomy in a way that builds trust and long-term sustainability. This may come in the form of providing transparency into why products are recommended and allowing them to influence or adjust the personalization parameters. Ultimately, responsible personalization is not just a compliance necessity, it’s a strategic advantage. The challenge retailers and technologists face is not about adopting personalization, but to build it responsibly while ensuring shoppers remain in control, empowered and informed.

    When shoppers feel they are in control of the purchasing journey and have a better understanding of the recommendations presented to them, they are more likely to trust the platform and engage with it in deeper, more meaningful shopping experiences. The future of e-commerce depends on whether AI serves the shopper’s intent or quietly replaces it.

    References:

    • McKinsey & Company. (2021). Retail speaks: Seven imperatives for the industry.

    https://www.mckinsey.com/industries/retail/our-insights/retail-speaks-seven-imperatives-for-the-industry

    • McKinsey & Company. (2021). The value of getting personalization right—or wrong—is multiplying.

    https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying

    • Boston Consulting Group. (2024). What Consumers Want from Personalization.

    https://www.bcg.com/publications/2024/what-consumers-want-from-personalization

    About the author

    Vinod Sivagnanam is a technology and product leader with deep expertise in digital commerce, AI personalization, and customer experience. He focuses on building data-driven platforms that balance innovation with user trust and writes about the evolving relationship between consumers and intelligent systems.

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