For any cross-channel strategy to be successful, it must have the ability to effectively provide personalized product recommendations to customers each time they interact with a brand. Emarsys Predict is an analytical recommendation engine that uses machine learning algorithms to engage customers with the products most likely to resonate with them. From the website, to email, to mobile, today’s consumers have an ever-increasing expectation of a hyper-personalized buying experience, and thus a relationship with the brand.
However, as with all cross-channel strategies, there are challenges to reaching that level of personalized product recommendations. The only way to truly engage with customers is to communicate with each one as an individual, which is seemingly impossible for even the most sophisticated marketing teams. There is simply too much data to create personal recommendations at a scale that would engage a database of hundreds or thousands of potential consumers.
Emarsys’ Predict is a highly innovative personalization engine that allows marketers to individualize specific content for each recipient, with a wide variety of options from which to choose. Discover just what Predict is, and, most importantly, how it can create a major advantage for your brand.
What is ‘Predict’?
As mentioned above, Predict is a powerful recommendation engine that analyzes the behavior data collected from e-commerce retailers and uses it to deliver personalized recommendations to all customers across email, mobile, and web.
Predict is also a self-learning marketing solution that can intelligently create real-time, personalized content based on a customer’s interactions with a brand online and in-store. It is not only flexible, but also measurable and reliable, and sits on top of an exceptionally lightweight client-side integration.
Data is generated while a customer is logged into an e-commerce site, accesses a shop through a tracked link in a branded campaign, or engages with the brand in a variety of other ways. This data is compiled in a centralized database where each user’s data is tied together with their unique digital ID (e.g. their email address) to create a unified customer profile.
But what about anonymous customers? Their data is still collected into the centralized database, contributing to general affinity models covering an entire product catalog.
Created with three separate solutions, Predict works within email, web, and mobile platforms. Each vehicle has its own way of interacting with customers and providing personalization across multiple channels. It performs this task seamlessly, and can be the critical difference for customers who expect true 1:1 relationships with brands.
4 Essential Ways Predict Will Benefit Your Business
Engaging with customers on an individual basis across all channels and devices will greatly improve their experiences and increase ROI for the brand. With just a few hours of investment in the implementation process, Predict can begin to make a difference to every aspect of your marketing activities by presenting the right content to the right people, at the right time, and in the right place. This creates a positive impact on the brand’s bottom line in just a matter of days.
By taking advantage of the Emarsys unique method to identify each customer throughout all marketing channels, personalization can be taken to an entirely new level. Here are four essential ways that Predict can benefit your business and help drive results.
1. Newsletter Recommendations
Email can be one of the best ways to reach customers with targeted brand messaging. Though they have already opted in, providing relevant, customized product recommendations within the email can make a big difference. In fact, any email campaign can be improved by adding personalized content, catalyzing up to five times more clicks than regular content.
2. Repurchase Campaigns
Customers that have already purchased and have had a satisfactory experience are more likely to purchase from a brand again. Marketers can assist in that, along with targeting existing customers with relevant products based on their most recent shopping behavior.
3. Abandoned Carts
According to eMarketer’s Q1/2016 research, the digital shopping cart abandonment rate is 74.3% worldwide. Recouping even a fraction of that revenue can be a huge payoff for e-commerce brands; placing related products alongside items left behind in abandoned cart campaigns creates better cross- and up-sell opportunities.
4. Overall Browsing Experience
Having to search through pages and pages on a website looking for something specific can be a frustrating shopping experience, but capturing subtle, deeper relationships that develop as customers interact with a website results in highly accurate modeling of behavioral patterns and affinities. That knowledge allows a recommendation engine to update product recommendations, particularly while the visitor is browsing, resulting in up to four times more conversions.
Final Thoughts
Customer expectations are only going to continue evolving. Luckily, marketing technology is evolving right alongside it, as personalized shopping experiences become more and more important for, and expected by, customers. Tailored communications and recommendations across all channels are a must to build customer loyalty at the highest level.
Learn more about how Emarsys Predict works, how it can benefit businesses, and the data that proves it.
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