Product Recommendation System

recommendation-system

How likely are you to buy Candles when you buy a Cake? Very High Right?? We often buy shocks when we buy a new pair of Shoes. This is because shopkeeper recommend us to buy them and yes they are necessary. Is there any way I can implement same system in my E commerce Website and App? Yes you can and this is called a Product Recommendation System. This is Machine Learning System in which you are recommended product without explicitly hard coding.

Let’s assume, you have E commerce Shop. You want to recommend Toys when people buy dress for Kids. Until now you have to do it manually. When people buy this recommend this. And in large product, it is near to impossible. And as user behavior changes your hard coded system may not work. Hence, we introduced Product Recommendation Software in Nepal. You can implement this system and let machine automatically recommend product on the Basis of User Preferences and Product Type.

Note: You can use Recommendation System in any Website like News Recommendation, Video Recommendation, Food, Movie – not only E commerce.

Why Do My E-commerce Need A Recommendation System

Frankly speaking its a Growth Hacking Secret. 35% of revenue of Amazon is due to Recommendation System. E-commerce is quite big website, there are lots and lots of product. You see products which you will never buy. Just think of User Experience there. They will be bored scrolling. With Recommendation, you can show products they are likely to buy. It helps in increasing sales as a result of very personalized offers and an enhanced customer experience.

  • Provide Relevant Content
  • Increase Sales
  • Provide Amazing User Experience
  • Increase Average Order Value
  • Increase Up Sell and Cross Sell

Types of Recommendation System

Basically there are three types of Product Recommendation System:

  1. Content-Based
  2. Collaborative filtering
  3. Hybrid

Collaborative Filtering

In Collaborative Filtering Recommendation, our System will gather the Information of user, what products he have watched and purchased. Similarly, other data related to customer segments. Think of this like, lets say user A buys Milk with Bread and user B also buys Milk with Bread. Next time A buys Shoes with Shocks. Now you can recommend shocks to user B when he buys Shoes – as they resemble same buying preference.

A picture speaks thousand words:

Example of Collaborative Filtering

Content Based Recommendation

Unlike Collaborative Filtering, in Content Base Recommendation data is analyzed with the content itself than user. For example, if a person buys Milk and Bread, he is very likely to buy Jam right? Because these 3 products are quite related to each other. This also includes the historical data of the customer and recommend on the basis of past preferences.

Content Based Recommendation System

Hybrid is the combination of Both Content Based and Collaborative Filtering Recommendation.

Who can build Recommendation System in Nepal

With more than 3 years of Experience in the field of AI and RPA, Alphateds can providie amazing Data Science Solution to your business. You can build recommendation system for your system. Book You Quote Now. For more information call us at 9843613265!

How Much Does it Costs to Build A Recommendation System

Recommendation system is not like other system which is built once and done. It takes time to make the system perfect with regular updates and training. The cost of building a new recommend system starts from Rs.1,00,000. However more details can be discussed over meeting or telephone. The breakdown of cost looks like:

  • Project Management Cost

Knowledge-based systems create relations between the product and the user needs and thus help to suggest better products to the users as per their needs.

  • Design and Development Cost

The cost of UI/UX designers and hiring the perfect web developers would be covered under this category.

  • The Complexity of the Project

Any advanced features and the size of your company will also have an impact on the overall development of recommendation software.

  • Upgrade and Maintenance

To upgrade and maintain your software and to scale it with time by adding new features would also require some additional cost. All that would be included under this category.

  • Testing Cost

Lastly, to test the software in and out so that no bugs hamper the overall functioning of the software is also necessary. Hence, that cost would be incurred under this category.

49 thoughts on “Product Recommendation System”

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