Why Psychographic Segmentation is the Future for E-commerce

by Kirsten Lamb
Industry Trends
December 2, 2020
psychographic segmentation

As a result of the coronavirus pandemic, e-commerce is predicted to increase 20% YoY by the end of 2020. Many brands have already seen up to a 97%increase in e-commerce sales. You may be wondering how to make the most of this boom in online shopping, stay competitive and explore new ways to improve your customer experience.

Personalization has always been a key marketing tactic in the world of e-commerce,but basic customer demographics spun into over generalized customer person as aren’t enough. You can use refined psychographic segmentation to understand your current and prospective customers on a granular level – and boost your sales accordingly. Let’s dive in.

The Pitfalls of Basic Personalization

In one poll, 68%of organizations say they have a documented strategy for personalization. And the basis of personalization has always been customer segments. These are typically based on customer personas crafted from demographic data such as age, gender, job title and income.

Unfortunately,grouping target customers in this way can often translate into fuzzy, untargeted marketing and poor product positioning, as each group has radically different interests, desires and pain points, and they will respond to messages in dramatically different ways.

Failing to Attract the Millennial and Gen-Z Shoppers

Basic personalization fails to reflect the diversity of everyday shoppers. Millennial and Gen-Z shoppers, two key target markets for e-commerce brands, are culturally fluid – they reject stereotypes, gender and social norms and prefer to mix bargain finds with high-end items.

In particular, Gen Zers look at consumption as an expression of individual identity – something that retail brands struggle to tap into with over generalized customer personas and blanket segmentation based on basic demographic data. McKinsey highlights their craving for personalization, dubbing Gen Z as “identity nomads.”  

This coming-of-age shopper that so many fashion brands want to attract highlights the fragility of customer personas based on traditional demographics. To attract shoppers, retailers need to dig deeper into what drives shoppers’ purchasing decisions and use this granular data to personalize their shopping experience.

The New Way of Personalizing Shoppers’ Experiences

To ensure a competitive advantage, fashion brands need to go beyond basic demographic segmentation to offer a truly personalized experience for every individual shopper. McKinsey & Company recently highlighted the importance of highly personalized experiences saying, “When executed well, such experiences enable businesses not only to differentiate themselves but also to gain a sustainable competitive advantage.”

In recent years, more fashion brands have been using psychographics to create personas based on personality traits, personal values, lifestyle, passions and attitudes. But even that has its challenges. How do you use that information at scale?What does that say about whether a shopper likes cap sleeves or denim skirts? How do you learn about a shopper’s individual preferences and emotional drivers and use that to truly personalize their experience?

Psychographics help brands target a “particular kind of shopper,” yet still often fail to understand shoppers at the granular level. Consumers in the same demographic and psycho social categories often have wildly different tastes,interests, and opinions and cannot be squeezed into a few basic customer personas.

Give Your Customers What They Really Want

Lily AI can help you refine personalization and better target shoppers by understanding each customer’s emotional context. To enhance a customer's digital experience, it needs to be as personal as possible.

From the identity nomads of Generation Z to a woman looking for the perfect party dress – one that fits just right and reflects her style – consumers are looking for clothes that reflect who they are and work for their body type. Lily AI combines customer behavior data with product data to uncover what makes each shopper tick – from their favorite and least favorite physical features to their clothing style.

Get Granular with Targeted Psychographic Segmentation

Lily AI is the only technology on the market that can predict psychographics on a granular level, an asset for e-commerce brands looking to go beyond personalization based on over-simplified psychographics and demographics. Learn more about how using Lily AI will help you improve your customer experience.

Kirsten Lamb is a content marketing writer, copywriter, and content marketing strategist with a specialized focus on B2B and B2C e-commerce. She has written for Woo Commerce, NuOrder, and Selz - among others.


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