Competition on the digital shelf is fierce, and shoppers have seemingly infinite options. If they don’t feel seen by your brand, they’ll happily take their business elsewhere.
And shoppers aren’t always loyal to even their favorite brands, as nearly 75% of shoppers have tried a product from a new brand instead of their go-to, according to Salsify’s “Ecommerce Pulse Report: Q4 2025.”
You can connect or reconnect with shoppers by offering personalized sales and discounts tailored to their past behavior, and it’ll likely drive purchases. But that’s only part of an effective strategy.
Mariya Babaskina, VP of marketing at Yogi, a consumer feedback analysis platform, helps break down what goes into creating an effective personalized shopping experience, along with examples of how to achieve it.
If everything you know about your shoppers is made of figures and percentages, that’s actually not much at all. Like any great relationship, it takes a concerted effort to listen to how they actually feel.
“Most personalization strategies focus on behavioral data — clicks, purchases, and engagement — but these metrics only tell part of the story. The other half comes from what consumers actually say about products.”
— Mariya Babaskina, VP of Marketing, Yogi
By analyzing product-level feedback, such as reviews, brands can eliminate guesswork and use real consumer insights to drive personalization strategies that resonate across different segments, according to Babaskina.
To create an effective personalized shopping experience, brands must strike a balance between human sensibility and modern tech, such as AI shopping assistants and natural language processing tools.
Brands that create an effective personalized customer experience must recognize that personalization lives in the details, is authentic across channels, and evolves like a living system.
Yogi’s data shows that personalization at scale requires acknowledging that each retail channel, demographic, or region may value different aspects of a product.
“A message that resonates with one audience may fall flat with another,” Babaskina says.
Image Source: Sephora
For example, Supergoop’s Unseen Sunscreen reveals how consumer priorities and even language shift across retail environments.
“Personalization is not always about changing the product, but about adapting the story to match what each audience values most,” Babaskina says.
Much like how AI search tools can apply preferences and parameters to bring shoppers to the exact right product faster, authentic personalization closes the language gap between brands and consumers.
“When brands listen to how consumers describe their experiences, they can translate those phrases and metaphors into product copy that feels relatable and real."
— Mariya Babaskina, VP of Marketing, Yogi
Yogi presents an example of this idea in action, where a leading skincare brand’s product detail page (PDP) gets down to the nitty-gritty, while a specific user story adds a first-person perspective.
Both describe the same result but in entirely different emotional registers.
“Using actual consumer language in campaigns and PDPs will make storytelling more resonant and human,” Babaskina says, making it a powerful advantage as we enter the era of agentic shopping.
This era refers to the evolution of ecommerce powered by agentic AI — semi- or fully autonomous systems that can make decisions and take action on their own.
Personalization can’t stay stagnant. Humans are dynamic, and as consumers, their preferences evolve.
Babaskina recommends that brands monitor sentiment over time (in real-time, even), and adjust messaging, imagery, and positioning as necessary to combat waning interest.
“Personalization becomes a living system that learns, listens, and adapts in real time to what people care about most,” Babaskina says.
Image Source: Starbucks
Behemoth brands like Starbucks and Amazon use real-time feedback from support chat transcripts, social media comments, reviews, mobile app data, and so on to perform sentiment analysis.
Sentiment analysis tools can scan text and automatically determine the author’s attitude toward a topic, which brands can leverage to improve customer service, boost brand reputation, and, of course, create a personalized shopping experience.
“Personalization today requires connecting two worlds: the structured data that powers digital shelf management and the unstructured insights that reveal what people truly care about,” Babaskina says.
This merge, if successful, helps you reach a whole new level with shoppers. They can become more than just figures and percentages, but dynamic contacts that help drive brand advocacy through reviews and evolution through feedback.
“When those worlds inform each other, personalization stops being about segmentation and starts being about understanding,” Babaskina says.