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Optimizing and Testing the Experience of Buying Eyeglasses Online
Eyebobs is an online retailer of premium quality eyewear, originally retailing readers, they have since expanded to include sunglasses and prescriptions. We partnered with eyebobs to audit their existing site, providing tangible recommendations, both for the customer experience and their ecommerce team.
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Apps & integrations on this project.
Conducting a Comprehensive Site Audit
We focused our audit on site performance, product matrix, and user experience. We reviewed eyebob's existing integrations and identified opportunities to streamline their app ecosystem. Through collaborative workshops between the Barrel and eyebobs teams, we learned about how the their team is structured and how they manage product data for the site.
Streamlining the Product Discovery Experience
We shared opportunities with eyebobs to refine their setup to help users quickly find and customize the right lenses for them. We identified opportunities within their style quiz to capture customer data and share results via email, as well as personalize future marketing communications.
Optimize Related Products to Drive AOV
We identified an opportunity to increase AOV by serving the customer dynamic cross-sells in cart and checkout through Rebuy. These cross-sell suggests can be tailored to the products in the cart, and even A/B tested to ensure optimal performance.
Iterate UX Flows by Testing with Real Audiences
To gain real insights from eyebob’s target audience, we tested our wireframes using Helio and iterated on the designs to create a purchase flow that incorporated user insights, best practices, and our expertise in the eyewear space. While Helio has a wide range of audiences, we targeted users who wear readers and/or prescription eyewear.
Strengthen the Relationship With Existing Customers
Knowing eyebob’s high customer return rate, we recommended the creation of a personalized customer journey (or site experience) for a repeat customer leveraging Nosto with tailored product recommendations based on their previous purchase.
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