Market research shows that online apparel retailers suffer from stockout rates of 17.8% and up, which cause 25% of all abandoned carts. According to Deloitte, 72% of consumers say that finding a sale item out-of-stock decreases their willingness to shop with that retailer. Online stockout has a serious impact on profitability. IBM estimates that retailers lose more than $93 billion in sales due to out of stock inventory every year.
Most retailers have from 20-60% of their inbound links (from Google & social) leading to stockout pages - where each click has little chance to convert to sale! Stockout costs you lost sales via website bounces & abandoned carts due to a dead-end shopping experience. Solving stockout helps you to:
We've created an HTML widget that fits effortlessly on your product details page. Give it a try here.
How does it work? Our engine's Artificial Intelligence analyzes each product's image and delights your shoppers by showing them the most similar-styled alternatives.
Our stockout widget mitigates the dead-end stockout shopping experience by leading shoppers directly to the most similar looking alternatives in your inventory.
The Pcsso Stockout Widget is perfectly suited for retailers who experience medium or high inventory turnover. Our engine makes use of product styles, colors, brands & price. We don't use your sales data, so we're able to adapt quickly when there's updates to your inventory. Pcsso delivers a delightful shopping experience, even when products go out of stock!
| Pcsso Visual Suggestions | Other Engines | Manual Curation | No Recommendations | |
|---|---|---|---|---|
| Easy to setup | × | ? | - | |
| Automated | × | × | ||
| Covers full inventory lifecycle | × | |||
| Optimized for high turnover industries | × | |||
| Strengths |
Recommendations for new SKUs are instantly available & relevant. Recommendations stay relevant throughout the entire inventory lifecycle - from a SKU's launch, to when it's in its prime, to long after it's sold out. No purchase or browse history, nor any user-identifiable data, is needed. Ability to show visually similar items everywhere on your site: useful both on-site and in-app. |
Works best on mature SKUs, with high volume of purchases. | Fine grained control | No cost |
| Weaknesses |
It works best on products where style & the look are essential, i.e. apparel, furniture & similar. |
Very poor for seasonal inventory: cold boot problem means long delays before newly added items receive relevant suggestions. Often you must share business critical data with 3rd Party recommendation system (i.e. SKU-level purchase & user session data). Recommendations can be very random & completely unrelated to what the person was looking for. Recommendations unavailable / irrelevant for out of stock items. |
High cost, time consuming. Difficult to staff and manage. Does not scale, impractical to maintain full catalog coverage over time. |
+25% cart abandonment increase due to stockout. Difficult for users to navigate products - bad shopping experience. Reduced sales. |