Retail

BOGS Increases Revenue 8.4% With Product Recommendations

SiteSpect’s recommendation engine seamlessly integrated with our existing systems, and the ability to A/B test different configurations allowed us to make informed decisions that directly improved our bottom line. SiteSpect helped us in our understanding of our product attributes, and the results exceeded expectations.
David Cook
Former VP of Marketing at BOGS Footwear
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Introduction

User experience experimentation and personalization is critical in online retail, enabling businesses to make agile, data-driven decisions to increase engagement and revenue. This case study explores how BOGS Footwear, a brand under Weyco Group, leveraged SiteSpect to refine its online product recommendation strategy and achieve significant revenue results.

Buyer Persona

When Weyco’s BOGS Footwear brand aimed to increase revenue and engagement, it looked to the lessons learned from its sister brand Florsheim, adding SiteSpect Product Recommendations to the user experience. The two brands have distinct buyer personas, with Florsheim customers primarily seeking men’s casual and dress shoes, and BOGS catering to a broader audience, including farmers, workers, and professionals who value functionality and durability. Additionally, Florsheim’s product line focuses on style and color sensitivity, whereas BOGS offers seasonal products that appeal to customers who purchase multiple times throughout the year. BOGS also differs in the marketing of stylish, all-weather boots popular with men, women, and children.

Objectives

The objectives for BOGS Footwear’s product recommendation engine were clear:

  1. Reduce manual merchandising efforts.
  2. Enhance user self-discovery.
  3. Increase revenue per user.

Experiment Design

The process of introducing new product recommendations for BOGS Footwear began with careful experiment design, focusing on key metrics such as clickthrough rates, add-to-cart actions, and time spent on the page. Part of this process forced BOGS to think more critically about their product line and the relationships between products. During this stage, SiteSpect helped BOGS navigate through a product line review and product attribute classification process.

Execution

BOGS conducted A/B testing to compare the performance of SiteSpect’s recommendation engine against their baseline KPIs, in-house solutions, and other manual processes. Product recommendations were deployed across the homepage and product detail pages (PDPs) and granularly tested. As the recommendations were rolled out, BOGS recognized the importance of clear category definitions and filtering. Continuous monitoring allowed for iterative adjustments to product recommendation rules, ensuring they resonated with the diverse needs of BOGS’ customer base. Complementary recommendations, showing items shoppers most often purchased together were introduced and refined to maximize relevance and user engagement.

Results

The collaboration with SiteSpect yielded significant insights and improvements for BOGS Footwear:

  • Revenue Growth

    The implementation of SiteSpect’s recommendation engine led to a noticeable increase in revenue, driven by enhanced user engagement and effective product suggestions. BOGS saw an initial 3.7% increase in revenue per user, and an additional 4.7% increase once iterating further with product recommendations, for a total increase of 8.4%.

  • Understanding Buyer Personas

    The project highlighted the importance of tailoring recommendation strategies to the specific needs of different buyer personas. BOGS customers responded well to recommendations that balanced color and functionality, while also catering to family-oriented shopping behaviors.

  • A Well-Structured Catalog

    The success of the recommendations was closely tied to the organization and clarity of BOGS’ product catalog, enabling more accurate and meaningful suggestions and the ability to recommend products with similar style groupings (e.g. a product bought with rainbows on it might produce a recommendation of boots with a print of stars, unicorns, or teddy bears on them, where something with trucks on it might produce recommendations of boots with a pattern of tools or rocks on them.

  • The Power of Recs + A/B Testing

    The combination of product recommendations and A/B testing proved a powerful tool for optimizing the customer experience, leading to sustained improvements in key performance indicators (KPIs).

SiteSpect has become an integral part of our digital strategy. The lessons we learned from implementing recommendations for Florsheim were invaluable, and SiteSpect’s flexibility allowed us to apply those to BOGS with great success. We’re excited to continue optimizing our other brands with their support.

– Ryan Wittmann, Manager, Business Insights & Growth Marketing at Weyco Group

BOGS

8.4+
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