Customer Stories / Retail & Wholesale

2022
Company Logo

Dress the Population Increases Conversion Rate by 28 Percent with Personalized Product Discovery Using Amazon Personalize

Learn how retailer Dress the Population partnered with Obviyo to increase its conversion rate by 28 percent using Amazon Personalize.

350 percent higher revenue

per visit for shoppers who interacted with recommendations

28 percent increase

in conversion rate

Sustainable ML solution results

in 72 hours

48 percent of revenue influenced

by personalized recommendations

14 percent of visits saw engagement

with recommendations in 3 days

Overview

A common barrier to the use of personalization technology is the misconception that machine learning (ML) models need months of training to be effective. For Dress the Population, a seller of high-quality and luxury women’s clothing, ML-driven personalization took only a few days to deploy on Amazon Web Services (AWS).

Dress the Population collaborated with Obviyo, an ecommerce marketing company and AWS Partner, and implemented its intelligent product recommendations solution powered by Amazon Personalize, which developers can use to build and deploy curated recommendations and intelligent user segmentation at scale without any ML expertise. Using the solution, Dress the Population increased conversion rates by 28 percent.

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Opportunity | Using ML to Power Product Discovery and Increase Sales

Dress the Population has been selling high-end luxury clothing to retailers like Neiman Marcus and Nordstrom since 2011. The company achieved success by selling its products in these premium brick-and-mortar stores, and it realized that it would need to adapt the benefits of this in-person shopping experience to a digital marketplace if it were to achieve the same success online.

Shoppers at premium brick-and-mortar stores enjoy help from staff and brand representatives in discovering the right products. Dress the Population wanted to replicate that experience online by contextually recommending items customers would like. The company realized it could increase product discoverability using ML to curate a personalized online shopping experience for each customer. However, it lacked the ML expertise to build, train, and maintain sophisticated models. Further, the company wanted to roll out these personalization capabilities to its customers as quickly as possible.

Dress the Population engaged Obviyo and implemented Obviyo Recommend, an ML product recommendation app for Shopify that delivers hyperpersonalized recommendations for customers based on their behavior and interests. Obviyo Recommend is powered by Amazon Personalize, which can adapt to browsing behavior in real time—an essential capability when trying to unlock the revenue potential of new shoppers.

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Obviyo Recommend has exceeded my expectations. And the Amazon Personalize algorithms continually learn customers’ preferences in near real time.”

Shoshana Ritzle
Vice President of Marketing and Creative, Dress the Population

Solution | Personalizing the Digital Shopping Experience and Increasing Conversion Rates by 28 Percent

Organizations can connect Amazon Personalize with their existing websites, applications, text or push notification systems, and email marketing systems with ease by working with AWS Partners like Obviyo to quickly build a range of personalization capabilities. Dress the Population uses Growth Bots, ready-to-go components of Obviyo Recommend that are powered by Amazon Personalize and blend branded content with personalized recommendations. These bots help shoppers find products of interest and improve upsell opportunities. The product recommendations quickly proved to be highly relevant and effective. In just 24 hours, Obviyo implemented 13 Growth Bots for Dress the Population, each using a different personalization strategy.

As soon as the Growth Bots went live, Amazon Personalize algorithms took over to rapidly learn and adapt to live visitor behavior. Within 72 hours of the company deploying Obviyo Recommend, 14 percent of all site visitors engaged with product recommendations, and 48 percent of all sales involved at least one engagement with personalized recommendations. Using the Growth Bots, Dress the Population interacted with different visitors at different stages of their shopping journey and quickly saw the positive impact on its sales. After implementing Obviyo Recommend, Dress the Population’s revenue per visit for shoppers who engaged with personalized recommendations was 350 percent higher than it was for those who did not. And within 14 days of launching its recommendations, Dress the Population saw a 28 percent lift in its conversion rate.

Results

Results of Revenue

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Outcome | Accelerating Revenue Growth and Enhancing the Customer Experience

Using Obviyo Recommend, Dress the Population quickly and cost effectively launched personalized recommendations. The company increased engagement with its online customers and achieved significant revenue growth within just a few days. “Obviyo Recommend has exceeded my expectations,” says Shoshana Ritzle, vice president of marketing and creative at Dress the Population. “And the Amazon Personalize algorithms continually learn customers’ preferences in near real time.”

About Dress the Population

Dress the Population makes luxury clothing created from premium materials that is attainable through its in-person and online stores while offering fair working conditions throughout its supply chain.

About the AWS Partner Obviyo

Obviyo is a software company that develops Obviyo Recommend, a Shopify application for providing near-real-time personalized product recommendations to drive new revenue growth and deliver a brand-specific online shopping experience.

AWS Services Used

Amazon Personalize

Amazon Personalize allows developers to quickly build and deploy curated recommendations and intelligent user segmentation at scale using machine learning (ML). Because Amazon Personalize can be tailored to your individual needs, you can deliver the right customer experience at the right time and in the right place.

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