# Slickdeals Boosts CTR With Personalized Recommendations > Source: https://www.recombee.com/case-studies/slickdeals > For the complete site index, see [llms.txt](/llms.txt). To integrate Recombee, see the developer documentation at https://docs.recombee.com/llms.txt. [Success Stories](https://www.recombee.com/case-studies) # AI Product Recommendations With Highly Volatile Inventory and User-Generated Content Slickdeals [E-commerce](https://www.recombee.com/domains/e-commerce), [Deal Aggregators](https://www.recombee.com/domains/deal-aggregators) [Product Recommendations](https://www.recombee.com/product-recommendations) ![](https://www.recombee.com/img/case-studies/slickdeals.png) Slickdeals is the largest social platform for shopping, dedicated to helping savvy shoppers score deals on the products they love with insight from millions of real people. With a high number of available products and the continually evolving content, smart product recommendations were a must. Recombee handled this specific use case with huge success and helped Slickdeals to provide the best-picked deals that are remarkable for their worth, quality, and timeliness. 70% Increase in CTR to Detail Page Views 30% Increase in CTR to Affiliate Links ### Situation * Highly volatile and fast-changing inventory with user-generated content. * 25 million users. * Slickdeals team of experts curates the frontpage. ### Requirements * Recommendations of time-sensitive deals and coupons. * Immediate response to recent deals. * Recommendations based on customers’ votes and feedback. * Real-time personalization for every individual user. ### Solution * **“Just For You”** section on the homepage. * **Custom made business rules** for old and expired deals. * **A complex ensemble of** incrementally-trained ML models: * **Collaborative filtering models** accelerated through sparse locality-sensitive hashing. * **Natural language processing** using deep recurrent neural networks. * **Image processing** using deep convolutional neural networks. * Fully leveraging Recombee technology for **real-time data processing:** * Most models designed for **incremental training and live updates.** * **Queued processing** of new incoming data (with constant reprioritization) for near-real-time deep-learning models. * **Discovery of hot deals through** reinforcement learning and contextual bandit models. ### Benefits & Results * **70% increase** in CTR to a product detail page. * **30% increase** in CTR to affiliate links. * Improvement of user experience and engagement. * Real-time personalization for every individual user. ### Scenarios ![slickdeals](https://www.recombee.com/img/case-studies/scenarios/slickdeals-1.png) #### Just For You Main personalization strategy behind this scenario is to provide unique experience for every individual user who visits Slickdeals homepage by offering the newest, diverse and most relevant deals. “Recombee was able to handle our very specific use case around providing recommendations with a highly volatile inventory of user- generated content. Placing recommendations on our homepage was a huge success — 70%+ higher product detail page views and 30%+ higher clickthroughs. The Recombee team is a great partner in helping solve our unique use cases, and we look forward to continue working with them.” **Daniel Uhm** Product Manager at Slickdeals ![Slickdeals](https://www.recombee.com/img/logos/slickdeals.svg) ### About Slickdeals Slickdeals is one of the top 100 most visited sites in the U.S. with 25 million users in its social shopping network. Their members are connecting with each other to share the most up-to-date deals and coupons and Slickdeals helped them to save over $6.8 billion by offering a messaging platform, as well as shopping resources like its free Android or iOS applications and browser extensions for Chrome and Edge. 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