With Recommendations Web, you can quickly add dynamic, personalized product recommendations anywhere on your website. Here’s how to get started.
Cart recovery is consistently a high-performing campaign. Here are a few tips for optimizing the customer experience and maximizing your success.
Leverage custom business rules and predictive models to automate dynamic, personalized product recommendations your ecommerce website.
When done well, product recommendations can be a powerful tool for connecting with consumers. Here are a few dos and don’ts for how to get it right.
With this extension of our recommendations offerings for email, you can easily add dynamic, personalized product recommendations anywhere on your website.
Why are loyalty campaigns so important, and how can email marketing personalization help you elevate them so they stand out from the competition?
What does it take to turn a shopper from customer to loyalist to advocate? A shopping experience that exceeds their expectations at every turn.
If you show your customers you get them and make it easy for them to find what they’re looking for, they’ll be sure to come back to you time and time again.
It’s time to make more space in our trophy case! We’re very excited to announce that we’ve won a Bronze Stevie® Award for Recommendations Premium.
Check out these three email marketing tactics that can increase open and click-through rates, conversions and customer lifetime value for your brand.
Getting the right product in front of the right subscriber at the right time is paramount. Are you making the most of your product feed in your email campaigns?
Learn about the four types of decision-making in software and which techniques offer the greatest potential to generate revenue for your brand.
Learn how a custom product feed can super-charge revenue generation for your brand.
Ask these questions to break through the hype and uncover a commerce marketing solution’s potential to add value for your business.
Learn how we designed our product recommendations engine for powerful search and gave users the flexibility to choose a predictive model.