Related Products: Product Recommendations in Mobile Apps

Related Products: Product Recommendations in Mobile Apps: The prime motive of any online business is retaining customers. This is only possible if we offer our customers a better user experience.

One can inlay a better user experience only if they analyze the customers’ shopping mindsets and improvise their online stores likewise.

A very layman example we can consider is offering product recommendations to our customers on the Mobile App Builder as they carry on with other purchases and navigating the store.

Importance of Product recommendations or Related Products

Related Products or product recommendations may seem a little something to us, but entrepreneurs know how crucial they are for an online business.

Rendering recommendations for products can develop an interest in the customers’ minds to purchase those products.

Most of the time it has been seen, customers do end up purchasing the products listed in the Related Products section; along with the other purchases.

Use Case Scenario: for Related Products

For instance, you visit a sports online store for buying a yoga mat. As soon as you visit a product, a few more products in the product recommendation section appear as per your product search.

These products may include, such as, dumbells and yoga ball, or a yoga CD maybe.

As soon as you lay your eyes on these product recommendations, you may like the yoga CD and dumbells; and perhaps you may end up buying these two products as well.

This is a very common scenario with us customers, in one way it’s beneficial as well; we don’t have to purchase again and again.

How do the recommended products work?

The concept of Related Products may seem simple, but behind the scenes are extremely crucial.

The well-sorted and precisely analyzed product recommendations that display for the customers is the outcome of extremely convoluted algorithms; that study user behavior rigorously and thereafter produces personalized product recommendations.

The product recommender systems is another one that adds to the technology stack.

It implements accumulated data and predefined algorithms; to analyze and exhibit products or services that customers may want to purchase.

The major goal of such systems and algorithms is to fulfill customers’ expectations and demands and enforce users’ engagement in a store.

There are various strategies that associate with Related Products. Let us take a deep dive and explore them in detail.

Strategies Associated with Related Products

Strategy as the name suggests is a step taken to identify the appropriate opportunity that yields fruitful results.

In the case of Related Products, it is essential to identify the right prospects and recommend suitable products that abide by each customers’ expectations.

This enhances the user experience and instigates the customers to make a purchase.

Moving on, let us explore the strategies associated with Related Products below:

• Automatic: It takes into consideration the available customer data or context at a given point of time and automatically recommends appropriate products to the customers.
• Most popular: It displays recommendations for products that are presently most popular in a store.
• Most popular in category: These include product recommendations that are presently most popular within a product category that a customer is viewing.
• User Affinity: These product recommendations match each customer’s preferences based on the browsing approach.
• Bought together: These are recommendations that display matching products that can be purchased with the product(s) that customers are currently viewing.
• Similar products: This provides product recommendations that are linked with the product that is being currently viewed by the customer.
• Recently viewed: It provides recommendations that each visitor has recently viewed.
• Recently purchased: Displays product recommendations that are purchased with a product that is being viewed by the customer.
• Last purchased: Recommends products from a customer’s recent purchase.
• Hybrid strategies: It includes a combination of any of the above strategies.

Benefits: Mobile App Builder Related Products

As business entrepreneurs, it is our prime responsibility to integrate features that promote user engagement and at the same time ease the purchase process of the customers.

For that reason, the Product Recommendations or the Related Products feature has become vital that of every mobile app.

Having said that, our customers prefer a purchase process that is swift: and help them save some time and money.

So, business entrepreneurs integrate the Related Product section in their apps that instigate customers to buy in bulk.

This section may display products that are based on the customer’s previous purchases.

Suppose, last time the customer wished to buy a Yoga Mat, but due to its high price, did not purchase it.

The next time customer visits the store, the same Yoga Mat is available at a 50% discount. Not only this, in the product recommendation section he finds Yoga equipment as well and buys them all in bulk.

This is the power of Mobile App Related Products!

Moving on, let us discuss the befitting factors of Product Recommendations in the Mobikul Mobile App.

• Customers need not go here and there and visit several product pages.
• Personalized recommendations are even more effective as it is based on customers’ previous purchase history data such as most viewed, visited, or bought product items and the product that customer is viewing or buying currently.
• Instigates the customers to purchase in bulk and this way business merchants can make more money.
• Most of all, customers can save a huge amount of time browsing products in a store.
• One of the finest strategies to initiate more purchases and increase sales for the stores.

Mobile App Builder product recommendations prove to be a boon for online businesses. It adds on to enhance the sales and conversion rates for the stores.

That’s all for Related Products: Product Recommendations in Mobile Apps. If you still face any issues, feel free to add a ticket and let us know your views to make the module better at webkul.uvdesk.com.