Hyper-personalization and the AI-driven commerce revolution

Sasha McKenzie, Deal Lead, Wellington Access Ventures
2025-03-31
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The views expressed are those of the author at the time of writing. Other teams may hold different views and make different investment decisions. The value of your investment may become worth more or less than at the time of original investment. While any third-party data used is considered reliable, its accuracy is not guaranteed. For professional, institutional, or accredited investors only.

Since the earliest days of commerce, financial and technological innovations have continually changed the ways in which goods and services are exchanged. As Figure 1 shows, in recent decades, platforms that enable such methods as online shopping, mobile pay, peer-to-peer payment, buy-now-pay-later, among others, have fundamentally altered relationships between buyers, sellers, and products. In our view, the next tectonic shift is already underway: AI and machine learning will transform consumerism, leading to unprecedented degrees of personalization in many industries.

Figure 1
Evolution of digital commerce

To achieve hyper-personalization, the next wave of AI will likely push the consumption ecosystem beyond its current state. AI tools should be able to leverage the oceans of data that already capture a customer’s browser history, “dwell time” on specific products, and digital footprints on social media, to infer that same person’s emotions, opinions, viewing environment, and even their metabolic data. Rather than corralling consumers toward “similar items,” the software will likely match offerings with the specific contours of a customer’s personal identity. Historically, retailers simply leveraged a consumer’s online data to deliver targeted ads. While this should remain true, the power will return to consumers, as the search for specific products and services becomes more tailored to their preferences.

Enhanced online search

AI can enable visual search and interpretive computer-vision capabilities that simplify and personalize the consumer experience to a degree previously unimaginable. Through machine learning and predictive analytics, AI-powered software can help shoppers identify products quicker and deliver customized suggestions for substitutes at similar (or varying) price points. Computer vision will likely process a consumer’s 3D visual information and rapidly analyze this data, deriving insights on a customer’s mood and feelings about the item, in addition to its fit. This level of accuracy can allow brands to deliver content, products, and services to consumers while supplying precise inventory management details for retailers.

A search for, say, a “red cashmere sweater under US$100” may leverage algorithms that recommend brands and sizes that perfectly fit the customer’s body while also filtering through their social media preferences to show that their trusted network of influencers, friends, and experts also use or recommend the product. Collectively, this information can provide powerful validation and reassurance in the purchase decision.

Bespoke products at scale

In addition to helping consumers identify and purchase existing products that are perfect for them, AI will be able to facilitate mass markets for bespoke products produced at scale. In particular, the health, wellness, and beauty categories are candidates to amplify this approach. Consumers’ quest for longevity presents a gaping hole and a tremendous opportunity for companies to tap the science behind longevity. Customers — not least of which include 77 million US baby boomers — want to live longer, looking and feeling their best as they age. AI will help companies deliver targeted, personalized solutions to concerns like hair loss, wrinkles, and hyperpigmentation, for instance, and make those solutions more affordable and accessible to consumers.

AI has given formulators the ability to test and iterate formulations quickly, yielding more effective products that deliver enhanced results on a molecular level. These new formulas can help companies overcome customer-related “pain points,” where solutions to date have been adequate, but not necessarily transformative. Thanks to AI, consumers should be able to order vitamins that contain the precise levels of nutrients their specific body needs. Using personal metabolic data, supplement companies will be able to fulfill orders that optimize levels of various vitamins and minerals specific to a customer’s physiology. Generic, one-size-fits-all vitamins and supplements may eventually be a thing of the past. This same model can be applied to cosmetics, hair care, and a range of personal wellness and beauty products.

Brick-and-mortar renaissance

Finally, brick-and-mortar stores, the supposed dinosaurs in the age of digital commerce, will once again shine thanks to AI and augmented reality. AI may be able to help stores morph from being transactional hubs to offering immersive experiences. They can become experiential playgrounds, delivering shopping experiences so multidimensional, so emotionally resonant, that making a purchase will become a memorable, sensory journey. Retailers should be able to connect with consumers on a deeper level. Customers can shop while listening to personalized playlists. They can see customized digital art exhibits or attend personally crafted culinary tastings. The technology will be able to suggest alternatives to help a customer create an outfit they love in real time. 

The in-store renaissance may also be a function of a shift in recent consumer behavior. Research has begun to reveal consumers’ weariness of certain aspects of e-commerce, leading to a phenomenon known as “the great unsubscribe.” Shoppers, tired of the barrage of inbound, impersonal promotions via email or on social media, are hungry for experiences. While this trend has been forming for many years, the advent of AI has accelerated the potential for retail stores to become destinations worthy of a trip off the couch.

Investment opportunities we are watching

Companies that understand the power of AI in commerce and embrace the shift toward hyper-personalization will be able to explore software that:

  • Creates efficiencies in the purchase process by narrowing choices and improving consumer outcomes
  • Manages inventory, optimizes inventory purchases, and streamlines logistics
  • Gathers and interprets data on customer demand, sales patterns, emerging trends, and sell-through
  • Minimizes product returns and maximizes conversion rates
  • Expedites sales, lowers costs, and builds customer loyalty
  • Uses machine learning to simulate real-world experiences throughout the purchase process
  • Provides individualized “social proof points” that offer validation of social acceptance
  • Accelerates content creation on social media, emails, or in-store marketing

Expert

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