1. Skillshare Drives Creativity and Inspires Discovery
Skillshare, the world’s largest online learning community for creativity, offers more than 30,000 classes to over 785,000 students.
This fast-growing edtech brand sets a model example for using AI to optimize email marketing. The team leverages predictive recommendations in automated campaigns to increase both efficiency and personalization. These recommendations match each user with courses suited to their unique needs based on behavior, activity, and interests.
Results: Their personalized weekly newsletter sees a 71% higher CTR than other emails.
Using AI, they optimize send times with a time optimization approach, which also helps to best serve their large global audiences and generate new ideas through GenAI for copywriting and A/B testing.
Key takeaway: Skillshare combines predictive recommendations and timing optimization to personalize and scale engagement efficiently.
2. Slickdeals Increases Loyalty and Engagement with AI
Slickdeals is powered by a vibrant community of 12 million shoppers who love to find, post, share, vote, and comment on deals. The company stands out as a shining example of how AI can drive engagement and nurture a devoted user base.
At the core of their strategy is a focus on converting new users into daily active participants and maximizing customer lifetime value (LTV). The team uses predictive scores to measure engagement levels and place users into different segments based on activity.
These segments aren’t static—they update dynamically as a user’s engagement changes over time. Based on these changes, Slickdeals adjusts message frequency to stay relevant.
This data-driven approach has resulted in a 26% increase in engagement rates when optimizing for open and click probability.
Predictive scores also play a key role in identifying waning interest, which enables the team to proactively intervene with churn-prevention messages. By leveraging AI-powered recommendations, Slickdeals delivers the right message at the right time to re-engage users effectively.
These recommendations power a range of campaigns—from post-purchase journeys and abandoned browse flows to their popular daily newsletter.
Key takeaway: Dynamic segmentation and predictive recommendations allow Slickdeals to keep shoppers engaged and coming back for more.
3. Udacity Unlocks Hyper-Personalization Using Data & AI
Udacity is on a mission to upskill the world’s workforce through the power of knowledge. Creating a connected and engaging learning environment is critical as online learning continues to grow. As a company that teaches the world about the applications of data and AI, the team at Udacity knows the power of data and AI.
“AI is my best friend. Especially because I’m wearing multiple hats… you’re looking at data, you’re writing copy, you’re building campaigns, you’re analyzing results, and a lot of what AI does within email tools could be done with human intervention, but it just takes way more time” says Lauren Reiterman, CRM Manager at Udacity.
The team leverages AI-powered recommendations to personalize messages, dynamically matching students with the right content and personalized programs based on their unique learning history.
Recommendations have been key in helping the team drive conversion and engagement – from course discovery to course completion. In fact, thanks to AI, the team has saved 10 to 15 hours a month as well as doubled the number of syllabus downloads.
Key takeaway: AI personalization increases conversion efficiency and reduces manual effort for lean teams.
4. Sweetwater Develops Lifelong Relationships With Every Customer
Sweetwater, a leading online music retailer, treats every customer interaction as an opportunity to deepen relationships through data.
The marketing team leverages AI to enrich those interactions, using predictive models to identify customers most likely to engage. With that insight, they tailor messages based on each shopper’s musical preferences and browsing behavior.
One predictive segmentation test focused on users ‘likely to click’ led to a 25% increase in email click-through rates. Sweetwater’s extensive product catalog and rich content are enhanced by AI-powered recommendations that ensure each customer receives relevant, personalized suggestions.
Their AI strategy doesn’t stop there. Predictive scores also guide campaign targeting, ensuring the right message reaches the right person at the right moment.
Key takeaway: Sweetwater blends deep customer insights with real-time personalization to foster long-term loyalty.
5. Carparts.com Personalizes Experiences with AI Recommendations
CarParts.com is the leading online auto part and accessories retailer. Their goal: help everyday drivers get back on the road by making it simple and convenient to shop for auto parts online. Their approach is another great example of the power of AI and 1:1 recommendations.
With a catalog of over 1 million SKUs, the team relies on AI to recommend relevant products and content based on each user’s vehicle type, browsing activity, and behavior. These personalized recommendations span across web and email channels, driving higher engagement and satisfaction.
This approach has delivered a 400% increase in click-through rate. On top of that, the marketing team saves 50 hours per week by automating time-consuming tasks that once required engineering support.
Key takeaway: Scalable personalization boosts performance and increases marketing team efficiency.
6. Artifact Uprising Keeps Customers Engaged All Year Long
Artifact Uprising helps customers create lasting memories through printed photo books, gifts, and more. As a company that promotes personalization, they put an emphasis on ensuring they go above and beyond to personalize experiences for their customers.
By leveraging rich customer data and AI, they take personalization to the next level. Given the seasonal and event-driven nature of the photo printing industry, keeping customers engaged even after the busy season is crucial.
Using recommendations, the team is able to provide the most relevant recommendations based on each user’s behaviors, project history, interests, and more.
AI helps the team personalize essential campaigns such as abandoned projects, sending timely and relevant messages, scaling their campaigns, and eliminating time-consuming manual tasks.
Recommendations also provide a great way for Artifact Uprising to learn and understand more about their customers and the other products they are interested in – ultimately resulting in more sales opportunities and driving lifetime value.
Key takeaway: Even in cyclical industries, AI helps maintain momentum and drive lifetime value.
7. Zumper Uses Predictive Recommendations to Match Renters to Homes
Zumper is an end-to-end rental marketplace that aims to make renting a place to live as easy as booking a hotel. Their dynamic business model makes it critical to stay on top of availability, pricing, user preferences, and levels of user intent.
AI plays a critical role for their marketing team, helping them match close to 100 million users with the perfect home from over half a million apartments. With a constantly changing catalog, it’s key for the team to be able to surface the right apartments for each user and help them discover new listings by matching user preferences and browsing behavior.
By leveraging data-driven, 1:1 recommendations they are able to effectively match users with listings and content personalized to their individual criteria, such as price, room size, term length, pet-friendly, and more.
These recommendations automatically update as user preferences evolve throughout their apartment search.
“Recommendations are really the lifeblood of our re-engagement,” says Russell Middleton, Co-Founder of Zumper.
Key takeaway: Real-time personalization enables deeper engagement in fast-moving markets.
