Is Your Shopping Experience Truly Personalized? How Brands Can Do It Better

By Dawn Allcot
Personalization
October 21, 2020
hyper-personalization and online shopping

E-commerce shoppers today, more than ever, expect a personalized experience. With brands like StitchFix promising consumers tailored recommendations based on their body type and lifestyle, traditional retailers must also find ways to create hyper-personalized experiences that replace what consumers enjoy about shopping in stores.

But is personalization just a buzzword? Traditional approaches, including using too-broad market segments, fail to account for subtle differences in customer preferences. To take your overall online shopping experience to the next level, it’s crucial to understand your customers on a more granular level than your current technology may allow.

The Role Emotional Context Plays in Hyper-Personalization

You may already be personalizing your digital experience based on customers’ demographic data and purchase history, and that’s a great place to start. However, there’s an opportunity to do more. To truly understand your customers on an individual level, you have to move beyond broad segments and understand their why — the emotional context for why they do or don’t purchase a specific piece of clothing.

But is personalization just a buzzword? Traditional approaches, including using too-broad market segments, fail to account for subtle differences in customer preferences. To take your overall online shopping experience to the next level, it’s crucial to understand your customers on a more granular level than your current technology may allow.

Moving Beyond Basic Product Data

The reality is that attaching a small handful of product attributes may not be enough to meet today’s demand for personalization. Suppose the product attributes in your catalog are thin, inconsistent, or even inaccurate. It will be impossible to understand why a customer likes or dislikes an individual product after they tap “add to cart” (or decide not to).


Descriptive data should dive deep into all the details that customers may love or hate about a product — and that goes for both subjective and objective qualities. Think fabric, cut, color, fit, and embellishments as well as their style personality and the occasion they’re shopping for.

Lily.AI’s deep learning technology and computer vision can assign 10 times more attributes to any product compared to other platforms. You may be using 5-9 attributes per product, but our platform will provide 20-30 per product, with over 15,000 total possible tags.


After enhancing your product catalog with this enriched data, we can help you deliver better search results, recommendations, or personalize other areas of the digital shopping experience. But even
further, we can formulate a more detailed picture of how individuals feel about their bodies and why they purchase what they do.

It’s Not Just The Data; It’s What You Do With Your Data

You know data is crucial; that’s not new. But could you be leveraging your data in a way that’s more impactful for your customers? An enriched catalog paired with behavioral data about how customers engage with your website is a powerful combination when it’s put to work. What attributes are they consistently engaging with, and what does that tell you about them?

If someone is always buying plunging necklines, cropped denim, or vertically striped shirts, that reveals style preferences, yes, but it also indicates how your customer feels about their body type. Our algorithm is coded to make these connections.


It will create a detailed profile that breaks down preferences like whether they want to enhance their bust or make their torso appear longer. Do they have short arms, wide hips, or broad shoulders? Stylistically, are they boho-chic, or do they gravitate toward dramatic embellishments? What do these attributes say about their body type? You can use these details, combined in a single profile, to customize the digital experience throughout the customer journey — from search results to emails to complete-the-look recommendations and more.

What Many Top Fashion Brands Get Wrong About Hyper-Personalization

In addition to grouping customers into broad buckets and not using product data to its maximum benefit, e-commerce retailers have to avoid two common traps: delivering a disconnected customer experience across touchpoints and relying too much on traditional search algorithms.


Past research has shown that your ​ digital experience impacts in-store sales​ as well, not just online sales.So, if consumers have a poor experience with your brand online, it may leave them with a poor impression of your brand overall. And unfortunately, a study from the ​ Baymard Institute showed that 61% of all e-commerce sites​ had below acceptable search performance. This dramatically impacts the likelihood of customers finding the products they love.


Instead, empowered with enriched product data and a detailed psychographic profile of each customer, you can personalize the digital experience across multiple touchpoints. You can leverage Lily.AI’s technology not only to deliver robust on-site search results but also to tailor communications, product pages, and more based on a customer’s individual preferences.


Bottom line: Hyper-personalization is about building deeper relationships with your customers. And true personalization occurs when you can understand their emotional context. This helps you help them discover clothing that makes them look and feel their best. Without that emotional element, personalized shopping remains more of a marketing buzzword than today’s truth.

Ready to learn more? Get in touch with us to ​ discover how Lily.AI can enhance your customers’ digital experience​.

References: 

1. https://baymard.com/blog/ecommerce-search-query-types 

2. https://www.sailthru.com/marketing-blog/data-divide-moving-beyond-disconnected-ecommerce-marketing/