Boost Customer Interaction Through AI-Driven Suggestions
The Power of Self-Service Recommendation Studio
Creating smart personalized product recommendations can be powerfully engaging for customers, but you don’t need an expanded team of data scientists and machine learning engineers for you to see success. The beauty of our self-service Recommendation Studio is that it works out of the box and provides you with all the tools you need to be successful with a small marketing team.
Within the Recommendation Studio UI, you can configure unlimited recommendation schemes. You have complete control over defining what type of content to include or exclude, mix and match recommendation types, and set backfill rules to ensure users always receive the most relevant offers, products, and content. You can also preview recommendations for any user or segment.
Sweden-based online marketplace Tradera increased sales by 131% with personalized recommendations. Alexandra Tham, Online Marketing Manager at Tradera, said: “Our small, time-constrained team has been able to deliver personalized, 1:1 product recommendations across our website, mobile app, and email campaigns at scale, which we could not do with our previous solutions.”
Similarly, Zumper, which connects property owners and managers with renters, scaled leads by 384% using predictive recommendations. Russell Middleton, Zumper co-founder, said, “If we had stuck with our old system, we’d need to add a number of people across the board, data scientists, data engineers, and marketers, to achieve the complexity of what Blueshift does for us today.”
If you have your own external recommendations, you can upload them into Blueshift as recommendation feeds and combine them with our AI-powered recommendations. Test, experiment, and optimize the best-performing combination to drive engagement and conversions.
Learn more about the inner workings of AI recipes in a blog post written by Blueshift senior data scientist, Anmol Suag. In this article, Anmol discusses how to rank recommendations inside recipes. And in this article, we discuss using Auto-encoders to find similar items to recommend.
The power of AI is within the reach of every retailer and digital media company. Give your customers a reason to love your brand even more by putting the most relevant content and products in front of them. Our recommendations experts are here to help you get started. Explore our interactive demo, or talk to our experts today.
Unlocking Personalized Recommendations
Creating personalized product recommendations doesn’t have to be a daunting task requiring a large team of experts. With the self-service Recommendation Studio, you can easily tailor recommendations to engage your customers effectively. The flexibility of this tool allows you to customize recommendation schemes, mix and match types, and ensure relevance with backfill rules.
Success Stories
Tradera and Zumper are two examples of companies that have significantly boosted their sales and leads through personalized recommendations. By implementing AI-powered solutions like Blueshift, these companies have achieved remarkable results without the need for extensive resources.
Enhancing Recommendations
By combining your own external recommendations with AI-generated suggestions, you can further enhance the effectiveness of your product recommendations. Experimenting with different combinations and optimizing performance can lead to increased engagement and conversions.
Deep Dive into AI Recipes
For a more in-depth understanding of how AI recipes work, check out blog posts by Blueshift’s senior data scientist. Learn about ranking recommendations and using Auto-encoders to find similar items for recommendations.
Frequently Asked Questions
1. Can I customize the types of recommendations in the Recommendation Studio?
Yes, you have complete control over defining what type of content to include or exclude, mix and match recommendation types, and set backfill rules to ensure relevance.
2. How can I combine my own external recommendations with AI-powered suggestions?
You can upload your external recommendations into Blueshift as recommendation feeds and experiment with different combinations to optimize performance.
3. Are there success stories of companies using personalized recommendations?
Yes, Tradera and Zumper are examples of companies that have seen significant sales and lead growth through personalized recommendations.
4. Is AI-powered recommendation technology accessible to every retailer and digital media company?
Absolutely, the power of AI is within reach for businesses of all sizes. Implementing personalized recommendations can help enhance customer engagement and drive conversions.
5. How can I get started with implementing personalized recommendations for my business?
Explore Blueshift’s interactive demo or talk to their experts today to kickstart your journey towards implementing personalized recommendations for your brand.
