Have you ever recommended a movie or a book you loved to someone – and then felt surprised when they didn't like it? Giving good recommendations for anything, whether it be books, movies, clothes, or cars, is difficult, especially if you don’t know much about the person. For retailers, giving product and service recommendations is even more challenging. But with marketing personalization and trackable customer insights, you can take the guesswork out of suggestions that will resonate with your customers.
Personalization is the method or strategy of using audience analysis and data to meet the individual needs of a consumer. It’s done by collecting and processing information on customers’ interests, demographics, and behaviors to create more relevant content and messaging that provides more value.
Customers appreciate being offered something that’s relevant to them as individuals. In fact, consumers have come to expect this kind of service from brands today. The more a marketer can accomplish this, the greater the consumer’s likelihood of repeat visits, purchases, or engagements. According to an Accenture study, over 75 percent of consumers are more likely to purchase from retailers that know their name and purchase history and provide recommendations that are appropriately on-taste.
Recommendation Tools for Retailers
Amazon is a pioneer when it comes to personalized product recommendations, which forms a vital part of their remarkable success. According to a McKinsey retail report, “35 percent of what consumers purchase on Amazon... comes from product recommendations.” But unlike Amazon, most brands still struggle with disconnected marketing tech stacks and cobbled-together data infrastructures that make it difficult to effectively offer recommendations.
Fortunately, tools exist today that allow marketers to personalize and hyper-personalize at a level previously unseen. Forward-thinking brands are already spending major dollars on marketing technology for personalization and the data it requires.
If consumer data is the fuel for achieving previously impossible levels of personalization and consumer-centric engagement, then marketing technology is the vehicle that allows you to deploy messaging across every channel. And it allows you to do so in a way that ensures every automated message feels personal, every intelligent product recommendation appears hand-picked, and the timing and channel of communication is always right. Taking the analogy one step further, artificial intelligence (AI) is the engine that drives hyper-personalization, using data to analyze buying patterns, to properly promote or provide a customized experience.
AI: Unlocking the Hyper-Personalized Future of Marketing
Marketers are beginning to recognize AI as the game changer they’ve been waiting for. AI engines developed specifically for the needs of engagement marketers can boost personalization and individual relevance by automatically turning consumer insights into on-taste messages – and they can do it at a scale that is beyond the wildest imaginations. In fact, AI-based product recommendations have been shown to boost conversion rates by up to 20 percent.
“For years marketers struggled to collect and centralize data, analyze and identify the relevant data, and make this data actionable,” said Alexei Kounine, AI Lead at Selligent Marketing Cloud. “AI heralds a change. It takes away the heavy lifting from marketers and can essentially deliver one-to-one marketing that had previously been talked about, but was never possible before.”
Recommendations Based on Behavioral Marketing
AI-based recommendations can be drawn from a specific customer’s behavior, or statistical calculations or items added to a wish list. Retail marketers need to ask questions such as: What do customers need at this very moment, or what are they actively searching for? And what do they own already? Marketers can then inject moments with relevant answers and recommendations via mobile push-notifications and dynamic content that serves individual offers synced to the moment of open.
As the most important aspect, Alexei Kounine points out that product recommendations can be implemented in real time across all channels for true omnichannel personalization. “Whether it's an email, a graphical component on the website, or a mobile push notification, the universal consumer profile is the same, so the real-time recommendations will be accurate and up to date.” Plus, marketers maintain full control over what offers are displayed to which customers based on what kind of behavior – and let the AI engine do the rest.
How Useful are Recommendations?
Obviously, performance numbers vary between customer profiles (number and type of products, traffic), but here are some findings which are a general indicator of recommendation performance across a number of shops. Visitors who click on recommendations are more valuable customers because:
They visit more product pages: Visitors who never click on recommendations often visit just one product page, whereas users who do click on recommendations typically visit between 3–6 product pages.
They are more likely to add more products to their cart: Visitors who click on recommendations add between 20–90% more products (depending on the type of products the shop is selling; the lower the price of the product, the higher the increase).
They are more likely to come back to the website.
For retailers and any brand trying to increase customer engagement and the conversion rate of its online shop, personalized product recommendations are essential. And with all the tools available for marketers today, it’s never been easier to inject every message with a human touch. However, the technology related to the science and algorithms used for implementing personalization and recommendations is not something that should trouble or encumber a marketer. These features should be available right out of the box in your marketing cloud, easily integrated and easy to use for marketers. Selligent Marketing Cloud has been natively built as a one-stop platform for marketers to easily inject personal relevance into every message, for every single consumer. The platform constantly collects data and powerfully uses it to understand the behavior of each visitor, making it actionable on all channels and offering relevant recommendations to satisfy each customer.