Unless you’ve been living under a rock, you’ve probably spent some time on sites like Amazon, Netflix, or Spotify. Think about the last time you used one of these platforms.
Maybe Amazon recommended a cute case to go with your new Kindle. Or maybe you opened Netflix and saw that the first recommendation was exactly what you were looking for — like the company could read your mind.
These companies generate awareness by recommending their products to new and existing customers. They may be one of the largest companies around, but that doesn’t mean your business can’t follow their lead.
You can also leverage personalized product recommendations to enhance your customer base and grow your business.
What are Personalized Product Recommendations?
As you might expect, the most important whatsapp and digital marketing aspects of personalizationProduct RecommendationsThe key is that they are personalized . This means that any product recommendations that customers receive from your website and marketing materials will be relevant and useful to them. To achieve this, companies like yours need to leverage data about past and current user behavior.
Today, purpose-built e-commerce applications and platforms simplify the creation of personalized product strategies.
Collaborative filtering
Intuitively, visitors to your website are categorized as either first-time or returning customers. First-time visitors are the hardest to make recommendations for – you don’t have any past user data to gain insights from!
This type of recommendation method is built for unique visitors to e-commerce websites. It will provide all recommendations based on the entire pool of user data you have at your disposal. This means that every new user will be directly targeted for bestsellers.
But as users browse your site, the platform will be able to start segmenting them into preference profiles orBuyerPreference profiles can be based on information such as purchase history, geographic location, age, and browsing device. Of course, you may not know all of this information initially.
Content-based filtering
Content filtering eliminates the unknown for users. Instead, all recommendations are made based on product categories and attributes. This means that search results and product page recommendations will always suggest relevant and comparable products.
Text data, such as description, style,Ratings and ReviewsAll of them provide a wealth of information to guide relevant and useful recommendations. Products are grouped by size, color, fit, style or other identifiers.
Assume that the customer will be interested in all similar or related products.
Hybrid Recommender System
Hybrid recommender systems combine disposal as wellanother option user intent and content-based data together. Using both approaches together gives you the best of both worlds.
For example, a new user lands on a product page. You can choose bestsellers or content-based recommendations. However, when that user creates an account during checkout, you can use collaborative filtering to come up with shopping cart recommendations.
Most e-commerce businesses will find it most effective to use a two-pronged approach.
Increase Average Order Value (AOV)
Today’s customers expect increasingly personalized experiences.
Research shows that product recommendations as part of a personalization strategy can increase AOV by up to369%.
Reduce shopping cart abandonment rate
Shopping cart abandonment will always be the bane of e-commerce existence. There are many reasons why cart abandoners leave, but any time they hit the back button there is a risk.
Personalized cart recommendations can be a great opportunity for upsell or cross-sell. They can also save customers from hitting the back button to try to find another product they just put in their cart. In other words, cart recommendations remove friction from the checkout process.
Better attract customers
When you attract an audience, you buildCustomer Loyaltyand increase customer lifetime value (CLV). A Microsoft study found70%of consumers say a qatar data company’s understanding of their individual needs influences their loyalty.
Personalized product recommendations are an easy way to start attracting and satisfying more customers.
Higher conversions
Personalized product recommendations remove friction, build engagement, and increase AOV — all of which translates to higher conversions for your brand.
Accenture research found65%Consumers are more likely to purchase from a real estate agent if the agent is recognized, remembered, and receives relevant recommendations.