In this case study, we'll show you how we would personalize the web experience on Urban Outfitters's website to increase sales by adding recently viewed products based on the first-party data Urban Outfitters has.

Before diving into the personalization, let's look at what Urban Outfitters does:

Urban Outfitters

Urban Outfitters is a lifestyle retailer dedicated to inspiring customers through a unique combination of product, creativity, and cultural understanding.

Urban Outfitters now operates over 200 stores in the United States, Canada, and Europe, offering experiential retail environments and a well-curated mix of women’s, men’s, accessories, and home product assortments.

The Background of the Personalization Journey

On its product pages, Urban Outfitters has

• product details

• reviews

• ‘just for you’ recommendations

• often viewed with products

However, Urban Outfitters doesn't have a recently viewed products section either on its homepage or product pages.

We believe that there is a huge opportunity lying under 'recently viewed products' because of creating a better customer experience by improving the product navigation.

The Opportunity

If someone is interested in buying a certain product from your online store, why not make it as easy as possible?

You can do this by adding the "recently viewed products” feature to your online store. This will allow customers to be able to see which items have been viewed recently. In other words, these are the products they showed the most interest in.

Adding 'Recently Viewed Products' Personalization

Step 1: The Tech Stack

To create personalized recently viewed products, Urban Outfitters needs to leverage website behavior and first-party data they have.

Moreover, in order to create the best possible personalized experience, we'll source all of the data points made by the same visitor under one merged profile - whether the user is signed in or not.

In this way, all website behavior will be stored under the same profile, allowing us to create a seamless personalization experience.

For this personalized experience, Urban Outfitters will need the following tech stack:

• Contentful as a content source

• Ninetailed as an experience API

Step 2: Defining Hypothesis and Methodology

It's no secret that browsing is an essential part of shopping.

We all browse around stores, searching for the best products and clicking different products over and over again.

Wouldn't it be helpful if there were some gentle reminders for visitors?

If a visitor has already viewed a product, then the visitor has shown interest. And if the visitor has shown interest, s/he is more likely to purchase the product. Therefore, it makes sense to show visitors' recently viewed products.

You might think that this is a simple solution, but it's actually used by some of the biggest names in online sales, like eBay and Amazon - and has proven to be very successful.

We hypothesize that by displaying a visitor's recently viewed products, Urban Outfitters can remind them of what they've previously expressed interest in, increasing the likelihood of them clicking through and making a purchase.

Step 3: Defining Personalization Signals

To create a seamless customer experience with personalized recently viewed products, we'll use the following signals:

• Products Viewed: The previous activity allows personalizing where the user left shopping via showing recently viewed products.

Step 4: Personalization Journey

To create the personalized version for Urban Outfitters, let's define our user's personalization journey:

1. A visitor lands on the Urban Outfitters' website.

2. Then the visitor visits product #1

3. Next, the visitor goes to another product page, product #2

4. Before leaving the page, the visitor scrolls down to the "Recently Viewed Products" section and sees product #1

5. After that, the visitor checks another product: product #3

6. On this page, the visitor scrolls down and sees product #1 and product #2 in the "Recently Viewed Products" section

The Result: Before vs. After

So far, we have talked about the hypothesis, methodology, signals to use, and required technology stack.

Now let's look at the visuals to better understand it.

As we defined earlier, the visitor checks three different products. Firstly, the visitor views the ‘UO Sage Wild Flower Chart T-Shirt’ (product #1). On the second product page, the visitor sees the following screen:

The visitor views ‘UO Ecru The Great Wave Graphic T-Shirt’ (product #2) as a second item. After that, the visitor checks another product: product #3. On this page, the visitor scrolls down and sees the following "Recently Viewed Products" section:

The Bottom Line

Personalization is a continuous journey, which means that once one implementation is completed, companies will return to the beginning of the framework to analyze acquired data, discuss new ideas, hypothesize further improvements, and so on.

Through continuous learning and experimentation, this strategy enables various teams

• content marketing,

• growth,

• product management,

• development

to create meaningful personalization experiences.