How Recommendation Engines Build Customer Relationships
Marty went to the supermarket, and in a dizzying sea of products, something caught his attention. In the row of endless chocolate bar wrappers and familiar logos, he saw a message that spoke to him: “You’re not you when you’re hungry.”
Marty chuckled. He felt seen and understood. The brand knew him. It was an instant connection.
Why is Snickers’ global campaign still so effective 10 years after it was first launched? Because it acknowledges universal emotions that consumers don’t necessarily voice, but to which they can relate unconsciously.
Harvard professor Gerald Zaltman said, “95% of purchasing decisions are subconscious. Consumers are driven by unconscious urges, the biggest of which is emotion. Emotion is what really drives the purchasing behaviors, and also, decision-making in general.”
When it comes to eCommerce, shoppers gravitate towards brands and products that make them feel seen. Showing the right product at the right moment enables brands to communicate that they see, know, and understand their customers at the unconscious level — their unspoken tastes and their immediate needs.
Recommendation engines may seem at a glance like a simple tool or an on-site novelty. But the reason they’ve become table stakes for brands and retailers is because they pinpoint shopper desires and enhance their experience, building lasting connections and influencing purchase decisions.
When recommendation engines are done right, brands sell not only a product but also a feeling to their customers. When they’re not, they can be jarring to shoppers and even push them to browse elsewhere.
This post will break down how recommendation engines strengthen bonds with customers.
Brand Affinity Relies on Emotional Connections With Shoppers
The most successful brands today have customer touchpoints that are experience-based and emotion-based. In a digital-first, post-pandemic world, personalized experiences make the all difference, pushing brands that leverage them ahead of the competition.
Consumer behavior has changed a lot over the past few months. According to the Business of Fashion and McKinsey & Co., building an online community is now an absolute necessity. And at the same time, consumers are newly choosy about which communities they want to be a part of. They are shifting loyalties to brands that truly get them—their unconscious thoughts, values, lifestyle, and preferences.
Recommendation engines are a critical part of the shopping experience and a breeding ground for creating engaging connections that lead to these brand communities.
Recommendations Engines Are Shoppers’ Digital Concierge
When shoppers want to find their way around a crowded shopping center or department store, they go to the concierge. In an instant, the person manning the booth points them in the right direction to find what they’re looking for.
Featuring a recommendation engine on an eCommerce website or app is like providing shoppers with an associate that can shop with them. Throughout the journey, recommendation engines surface the most relevant products that match not only the consumers’ initial search intent but also their previous and current browsing behaviors.
Recommendation engines provide shoppers with a curated selection of products that reflect their unique tastes. This creates a personal and engaging experience and paves the way for true brand love and the revenue that accompanies that. Gladly reported that “eight of 10 people will go out of their way to spend more money with the brands they love.”
Recommendation Engines Are the New Reference Group
In consumer behavior studies, there’s a concept called the “reference group.” It refers to the people in consumers’ social environment that influence their cognition, norms, emotions, and behaviors in a given situation—like choosing which products to buy.
Word-of-mouth is responsible for 20% to 50% of all purchasing decisions. Moreover, Nielsen found that consumers (83%) trust the recommendations of friends and family most, followed by brand websites (70%), and online consumer opinions or reviews (63%). Social media further amplifies shoppers’ reliance on word-of-mouth in the decision-making process.
When recommendation engines are layered with social proof, like star ratings, best seller tags, style tips, or user-generated content, you combine personalized product recommendations with a sense of relatability and community that is as irresistible as having a best friend pick out an outfit they know is perfect for you on a shopping trip.
Recommendation Engines Deal in Inspiration
Consumers typically fall into two groups: goal-oriented or experiential shoppers. According to researchers Mary Wolfinbarger and Mary Gilly, goal-oriented shoppers want their digital purchases as fast as possible. On the other hand, experiential consumers are motivated by ‘the thrill of the hunt.”
The pandemic has pushed more kinds of shoppers online, and experiential shopping is gaining traction as consumers look to online shopping as another form of entertainment they can safely partake in from home.
This means that brands and retailers have added opportunity to inspire shoppers and give them that thrill of finding a cushion, a necklace, or a tie that speaks to them. With a recommendation engine that truly understands your shoppers’ tastes, you can create an inspirational buyer journey that will make them want to come back.
The Not-So-Secret Sauce: True Personalization Is the Key to Powerful Product Recommendations
Unfortunately, only a handful of brands see the full value that recommendation engines can provide. In a future where 75% of consumers say they want more human interactions, cookie-cutter recommendation engines, in which sequencing algorithms are based on the behavior of thousands of similar customers, will be obsolete.
Product recommendations that are truly personalized combine the individual actions of shoppers with the basic sequencing algorithms. Using visual AI, it then supplements this data with details about the images of products that shoppers are interacting with, the visual attributes that appeal to them.
Combining the image data with written descriptions and behavioral data provides a more accurate, individualized representation of shoppers’ preferences at that exact moment. As a result, they’re able to explore products that reflect their unique tastes and styles when and where it matters the most.
Recommendation engines that work in this way create highly customized and engaging experiences that put consumers’ desires front-and-center. They can transform generic shopping journeys into emotionally driven, individualized experiences.
Shoppers Fall in Love With Brands That Exceed Expectations
Based on a Lithium survey, the majority of shoppers will likely “spend more on products and services from a brand that makes them happy (80%), a brand they love (80%), and a brand to which they are loyal (80%).”
In fact, 82% of top-performing companies pay close attention to the human experience around digital and technology for this reason.
As a variation on a digital concierge, recommendation engines understand, meet, and exceed customer expectations by honing in on key customer needs:
- Instant – Products are shown at the exact moment consumers desire them.
- Unique – Shoppers are seen as individual people, not just a data point, with products that appeal specifically to them.
- Delightful – With personalized visual inspiration at every turn, recommendation engines bring shopping back to its roots as a leisure activity.
This personalized and empathetic approach is the foundation of customer loyalty.
As Cognizant put it, going forward, standout customer experiences “will not be about having a large variety of products, as it has been in the past; rather, it will involve winning over consumers with thoughtful curation of products and experiences.” True recommendation engines are a mainstay in a retail world calling for genuine human interactions and meaningful personalization.