Executive Summary
Snow Peak, a high-end Japanese camping gear company, embarked on a transformative journey to enhance its online shopping experience. Recognizing the potential of its quality products, Snow Peak aimed to elevate its conversion rates and better engage site visitors. The primary challenge was the opportunity to improve conversion performance through a more optimal presentation of product information, social proof and brand values.
To address these topics, Shopify’s Growth Services team was engaged to conduct a comprehensive CRO audit and design overhaul. Through data-driven strategies and innovative designs, we transformed their homepage and product pages to enhance user engagement, social proof, and product navigation.
As a result Snow Peak increased their conversion rate by 35% and generated 600,000 USD additional revenue within 6 months.
The Challenge
Snow Peak wanted to translate its superior product quality into online success but struggled with various strategic challenges. They had a lower conversion rate compared to similar merchants on Shopify. We quickly identified high bounce rates on the homepage and product pages.
Heatmaps revealed that most homepage interactions happened on a single product recommendation section. The section had multiple hard to read tabs and did not provide visitors with easy catalog access. Visitors were forced into specific products right away and there was no motivation for them to explore the brand and catalog further. We also observed usability issues on product pages that prevented users from exploring the products’ features easily. The product images were hidden in a small carousel and social proof was underutilized, with customer reviews poorly highlighted.
We concluded that we needed to enhance the homepage by offering a quick and easy way to understand the brand values and the company benefits, as well as optimize the way how visitors can easily explore the catalog based on different intentions. We also saw the need to improve navigation and assurance on product pages, ultimately leading to a higher desirability to purchase a product.
The Solution
The Snow Peak team, in partnership with Shopify’s Growth Services team, implemented a suite of targeted CRO features, resulting in a significant transformation. During the project, we conducted an in-depth data analysis and usability research to identify high impact store optimisations. We also turned those recommendations into a visual design that was ready to be implemented by the Snow Peak team.
Fast Trust Building
Data revealed there were around 80% first time visitors. This led to the conclusion that we needed to find a way to build trust with first time visitors quickly. Homepage elements now include a prominent direct communication of service benefits of free shipping, Snow Peak’s lifetime guarantee, great reviews and ease of returns. This aimed at simplifying user understanding and fostering connection. After presenting the features, we also delivered a consistent design document that quickly showcased and communicated our recommended changes to the merchant.
Data-Driven Catalogue Entry
The homepage was revamped using data-driven collection banners and product recommendations. A data analysis revealed which collections visitors mostly accessed and purchased products from. These could then directly inform which collections and product recommendation slots to showcase on the homepage. We also combined those user-oriented aspects with brand storytelling elements.
Social Proof and Benefit Prioritization
We conducted a sophisticated AI-driven mining process of the existing product reviews shown on product pages. The diagram below shows the flow from the reviews export through the aggregation per product and analysis of each single review via ChatGPT.
Processing huge amounts of reviews can be challenging with tools such as Spreadsheets. That is why we used an R Script that greatly enhances efficiency when aggregating and grouping the review data. For the mining process, we used the following ChatGPT prompt to extract the product benefits customers were interested in.
You take on the role of an experienced data analyst. Your answers are precise and can directly be used for additional data processing. Take your time to analyze the provided text and only respond if you are confident that your answer achieves a high standard of quality.
I need you to extract a comprehensive list of positive features from the following concatenated text of product reviews, along with their respective frequencies and example quotes. The reviews of the product to be analyzed are here:
{insert all reviews of the product to be analyzed here}
With each review separated by a dot and whitespace. Please ensure the output includes:
1. Positive features that likely contributed to the buying decision.
2. The frequency number indicating how often each positive feature was mentioned.
3. An example quote directly illustrating each feature extracted from the reviews.
If there is only a single review, analyze it fully. If no reviews are present or feature extraction is deemed impossible, simply output a hyphen: - . Ensure that you do not include general statements related to the merchants' business practices, such as fast shipping. You should output either a full list of feature tuples, a single feature tuple, or a hyphen. Make sure to be as precise as possible when stating the positive features and do not be very general. No additional comments or texts should be added.
An integration of ChatGPT in Google Sheets made applying this prompt on Snow Peak’s vast catalog highly efficient. As we specified specific separators like semicolons and hashes in the prompt, it was easy to go back into our R Script and transform the ChatGPT output into a usable format. The table below shows an example output of what this looks like:
This provided a big list of per-product benefits that customers are mostly interested in, prioritized by their mention frequency and example quotes. With this data, we could identify review highlights confirming the most interesting product feature. We then showed those prominently on product pages to provide social proof as confirmation of the products’ most important features, ultimately enhancing credibility.
We also used the review insights to inform how Snow Peak can present their products’ features effectively and prioritize what they are interested in most. This was designed and implemented through a modular section with the top three mentioned features, text descriptions and photos.
Enhanced Navigability and Engagement
Through an improved overall structure on product pages, we enhanced the discoverability of visual aspects and product features. On desktop, visitors can now explore product features easily by scrolling through all high quality product images vertically. Using a focused sticky “call to action” bar, we could further achieve faster pathways to purchase. Optimized product recommendations also provided context-based fitting add-ons and alternatives to improve engagement.
The Results
Post-implementation, Snow Peak experienced substantial improvements in several important areas. Through these focused CRO changes, Snow Peak’s conversion rates increased by 35% and they made $600,000 USD additional revenue within 6 months.