Most Shopify brands sort collections manually based on best-sellers, newcomers, and sometimes even instinct.
But what happens when you let the right data do the merchandising instead?
Readers.com is a family-founded brand that set out to make reading glasses more affordable, accessible, and enjoyable. What began as a small team with a big mission has grown into a trusted online destination offering stylish, high-quality readers backed by fast shipping and friendly service.
With hundreds of products and a customer base spanning varied reading needs, the Readers.com team faced a growing challenge:
How to surface the right products to the right shoppers, without relying on instinct or spending hours manually reordering collections.
And while their merchandising was clear and user-friendly, it wasn’t always optimized for sales velocity or profit.
They also didn’t want to dive head-first into a new strategy without testing the strategy and automation effects against their current setup.
This was a job for Kimonix’s merchandising collection management, product sorting, and A/B testing features.
With Kimonix, Readers.com ran two 30-day A/B tests, comparing collections that were:
Managed by Kimonix’s profit-driven merchandising platform
Manually curated by their team
Both versions received a nearly equal amount of traffic.
Therefore, the difference in performance is due to the upgraded merchandising strategy (i.e., automated product sorting) and not outside factors like better or more exposure.
After running the two A/B tests that compared Kimonix automated vs. manual merchandising, Readers.com found that Kimonix-managed product sorting and collections were substantially better. The Kimonix-managed and tested collections saw:
41% higher revenue
36% higher conversion rates
32% more units sold
15% more product views
And drastic increases in overall inventory health
…than the manually managed collections.
With Kimonix, inventory health was more balanced. This meant:
Sales were spread across a wider range of products, including slower-moving items
A more balanced sell-through helped reduce dead stock, keeping inventory fresh and profitable
In contrast, manual management showed a flat inventory health, where mostly best-sellers sold well, while other products stayed stagnant.
This can lead to excess inventory that ties up capital and increases risk.
Kimonix collections factored in:
Profit margins
Inventory levels
Product freshness
Smart segmentation
Instead of relying on static lists or guesswork, Kimonix dynamically sorted collections using real-time store data, factoring in profit margins, inventory levels, product freshness, and shopper preferences and behavior.
This gave Readers.com the merchandising optimization they needed to drive smarter conversions, move more inventory, and increase revenue without increasing traffic.
Higher Revenue!