How Advanced Consumer Insights Push Website CX and Product Design to The Next Level

Marketing teams who know their customers well are delivering memorable CX and more desirable products

Consumer insights and marketing teams go together like peanut butter and jelly.

Consumer insights fuel personalized marketing, which is all around us now. From entertainment, to ordering food, to social media, to shopping for socks, we’re always seeing website offers claiming “recommended just for you,” or “trending this week” while we’re online. And in 2022, personalization is evolving faster than ever.

Powerful AI algorithms can figure out what we want by filtering our clicks (A.K.A our consumer behavior and preferred product data) and then deliver uncannily accurate personalized recommendations. And as it turns out, these recommendations can triple conversion rates and 6x revenue per visitor.

For the ecommerce teams of marketing and sales people, brand managers, product managers, UX designers, product designers, executives and company stakeholders of all kinds, consumer insights are a shared company resource that transcend everything from product development to the customer experience at the point of sale.

Consumer insights: the big picture

Considered from a higher level (i.e. above and beyond the bottom lines of conversions and sales numbers), consumer insights help ecommerce teams in two mission-critical ways:

(1) They provide preference profiles for creating unique CX
(2) They enable user-generated product design

Preference profiles, unique CX… and brand building

The more you know about your customers, the better CX you can provide and these days CX matters more than ever.

Former CDO of L’Oréal, Lubomira Rochet, spearheaded a customer centricity campaign that stressed the importance of building personalized consumer relationships.

In a 2018 interview with Commonwealth, Rochet explained,

“digital technology has changed the way we market. An important goal is having the ability to build rich, personalized consumer relationships and to create content that engages consumers and makes them happy to share it.”

In practice this works because the AI gets to know customers one at a time and creates preference profiles that can offer unique customer experiences, as L’Oréal did with their Shu Uemura cosmetics brand.

Mockup of “Tania Lee’s” preference profile, which would be used to create a personalized discount pop-up on a moisturizer she actually likes, packaged in a shade she likes, available in the price range that matches her purchase history.

With real-time consumer insights, the Shu Uemura site offers discounts on items that the shopper is actually interested in — especially for return visitors. But even for new site visitors, the AI begins compiling a preference profile within 3–5 clicks.

In the Shu Uemura scenario illustrated above, Tania Lee’s preference profile creates a discount offer pop-up on a moisturizer that matches her price range, favorite colors and preferred attributes. Conversions on pop-ups like these skyrocketed Shu Uemura online revenue in 2020 by 149%!

With this data in hand you can personalize your CX more effectively with automatic cross and up sells that solve the problem of information overload while shopping online.

Showing shoppers what they intend to buy saves them time, reducing friction during the browsing experience and eliminating the omnipresent online pain point of information overload.

The delightful surprise factor: a unique experience

If done well, consumer insights can inform personalized recommendations that are extremely memorable. A case in point is the delightfully unplanned purchasing decision, as described by Hubspot Marketing Blogger, Amanda Zantal-Wiener:

“Those who know me are aware of my borderline obsession with hip hop, which is also the motivation for a lot of my online shopping behavior. Clearly, Amazon has taken notice… the purpose of my most recent visit to Amazon was to check out its personalization features for this article. But then, I discovered that Rapper’s Delight: The Hip Hop Cookbook was in my recommended books. Did I buy something I don’t need? Sure. But I also was left delighted by the fact that it was brought to my attention with very little effort… the best part about it, for the user, is the resulting discovery of new things that we like — whether it’s a book, a tool, or an article.” Source: Hubspot, These 9 Brands Take Personalized Marketing to a New Level

A delightful product recommendation is one you like but perhaps weren’t expecting.

This is how Amazon uses consumer insights to shape the shape CX of their marketplace. An awesome experience like stumbling upon the rapper’s delight hip hop cookbook is delightful and memorable. Shoppers remember these kinds of things.

How to get advanced consumer insights and personalized CX on your branded website

Indeed, memorable experiences form the “personalized customer relationship” envisioned by CDO of L’Oréal, Lubomira Rochet. Her idea is to get the these Amazon-like experiences on your own website and in doing so begin building your own brand capital instead of Amazon’s.

For big sites like L’Oréal and especially for smaller SMB fashion ecommerce sites, the most advanced website personalization solutions from SaaS providers have also proven to be the easiest to implement — especially for teams without inhouse data teams specializing in machine learning. Smaller sites have been able to grow business quickly and achieve up to 5x ROI.

In the short term, personalized product recommendations increase cross sells dramatically with increased average order value exceeding 2x on average. Long term, improved customer insights let brands create the delightful ecommerce experiences that build brand love customer loyalty.

Consumer insights and user-generated product design

The consumer insights derived from AI-driven recommendation systems provide real-time user feedback that product designers can use to align what they make with what customers want.

User-centered design (UCD) is a long standing standard for in the design world that “calls for involving users throughout the design process via a variety of research and design techniques so as to create highly usable and accessible products.” Source: International Design Foundation

SaaS providers specializing fashion ecommerce can now provide detailed insights on length (shown below), as well as design, color, pattern, material or any other customized attribute they need.

Preference analysis feature optimized for fashion ecommerce showing length, design, color, pattern, material.

The answers to these questions provide insights about interaction with your product — how it is viewed, valued, and compared with other products based on features, price, season, etc.

In effect, these insights add another layer of context for product designers to consider besides the traditional context of use.

Source: International Design Foundation

But even for ecommerce merchants who don’t actually design their products, consumer insights provide value for selecting why some products do better. With access to preference analysis, merchants can identify the most desired attributes of a given product.

By analyzing customer preferences, I can easily find the most-clicked products, the shared attributes of the things added to the cart most often, the items with the most purchases and a lot more. That helps me learn more about customers and our products. Source: Case Study: Digging Into Customer Data on Socks Site Turns 5x ROI

So whether for product design or product selection, consumer insights are valuable to merchants of all sizes.


Consumer insights are central to ecommerce success nowadays because personalization has become common online and shoppers expect to see it.

This is especially true of the digital native Generation Z and the Millennials, who are willing and able to pay more for online experiences that reach out to them as individuals.

For fashion ecommerce the latest benchmark is fashion-first optimization. Marketers can use data-driven marketing to get in touch with their consumer’s desires and preferred aesthetics.

About offers fashion-optimized, image-based AI personalization for 1:1 onsite shopping experiences, authentic email marketing campaigns and preference analysis insights.

On average, our clients double their order value and triple their conversion rate because shoppers on their websites are more engaged by the industry-leading accuracy of our personalized recommendations. has been featured in Forbes Top 25 ML startups and Analytics Insights Top 10 companies.

Sign up for a free 14-day trial today and start growing your business on day one.




Our mission is to empower merchants. Our technology lets merchants understand fashion-savvy customers and create unique shopping experiences that grow their businesses. 1000+ ecommerce shops using saw a 2x increase in AOV and 3.3x increase in conversion rate.

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Ian Mckinnon

Ian Mckinnon

Content Strategist

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