How Much Does It Cost To Build A Recommendation System

Updated on Jan 8th, 2024

Have you ever wondered how Spotify can know your favorite playlist, or how Amazon perfectly suggests you the most attractive products based on your interests? Well, the answer is simple – a recommendation system. Recommendation engines have already proved their significance in many leading businesses of the world like Google, Amazon, Facebook, Netflix, and so on. 

Irrespective of your company size and niche, a custom recommendation system carefully analyzes the user information and turns it into an effective suggestion for the users. Moreover, in today’s competitive era, a recommendation system, even helps your brand to stay ahead of the competitors by enabling you to offer the most personalized suggestions to your users in no time. But, how does a recommendation system work, what are its types, and what is the cost to develop a custom recommendation engine software

Well, if you are looking for answers to all such questions, then we are here to help you! From a development approach, to cost, in today’s article, we will be discussing everything you need to know about custom recommendation software development. But, first things first

What is a Recommendation System and how does it work?

To simply put, a recommendation system is an excellent software solution that works on a particular technology and suggests products or content lure specific users. It is often witnessed that users access innumerable content online but they fail to find that particular thing they are looking for. That’s where recommendation software comes to play!

With a custom recommendation software, you can seamlessly bring all the users and the content to one place, so as to enhance your customer experience. Whether shoes, clothes, music, or even your movies and plugins, nearly anything can be suggested to the users using an online recommendation system.


A recommendation system simply uses machine learning algorithms to learn more about user preferences. Let’s say you visited an e-commerce website, and you searched for headphones. You even searched for some good music systems. Now, next time when you will visit that online store, the recommendation system will automatically suggest to you some good electronics related to music accessories. All in all, a recommendation engine is like a salesperson that learns about your interests and preferences, and then suggest the best products based on it!

So, what are the types of recommendation systems?

There are majorly 6 types of recommendation systems that prevail in the media and entertainment industry. To name them, we have

  • Collaborative Recommendation System

In this type, the recommendation engine analyzes the past ratings and considers the recommendations of the users in the past. In short, they work in a manner that if users have liked a certain thing, they will like the same thing again in the future. 

  • Content-based Recommendation System

Under the content-based approach, the machine analyzes the profile of the users and then offers them suggestions based on their interests and the thing they are currently searching for. 

  • Demographic-based Recommendation Engine

As the name suggests, under this kind of approach, the recommendations are made on the basis of the interests of a particular area. No user-perspective is taken into consideration.

  • Utility-based Recommendation System

Under the utility-based recommendation engine, the system offers suggestions based on the availability and utility of the product to the customer. Different businesses can have different approaches to offering the utility of the same product.

  • Hybrid Recommendation Engine

The hybrid recommendation engine is nothing but combining any two types of recommendation systems to get an efficient and result-oriented solution.

  • Knowledge-based Recommender System

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.


How to Develop a Custom Recommendation System With Matellio?

Although developing a custom recommendation system is quite a complex task, it can be simplified by partnering with an experienced software engineering firm like Matellio. Below, we have mentioned the 5 easy steps in which you can develop your custom recommendation software in no time with our experts.

1. Fill Out the Consultation Form

The first step in developing a custom recommendation software is to fill out the consultation form. You need to mention your basic details like name, email, contact number, and a short message giving a brief about your requirements. After that, our experts will shortly contact you on either skype, mail or phone, whatever will be best suitable for both. 

2. Discuss Your Ideas and Requirements

Once the form has been filled, you can seamlessly discuss your business ideas and requirements with our experts. Although, you could have all the ideas related to product development, having an expert consultation is foremost necessary. Why? 

That’s because an expert could provide you with all the details and trends of the market that could potentially make your product a hit. Moreover, they would also have more knowledge in the development field, so they can tell you more about the feasibility of your business ideas. In short, getting an expert consultation could potentially make your product better than your competitors. What else does one need? 

3. Finalize the Design and Features

In the third step, our expert UI/UX designers could help you choose the most aesthetic design for your custom recommendation software. Additionally, the features you select for your recommendation system could also impact the overall success of your project. Remember, you need to have at least two to three advanced features in your recommendation system so as to outreach your competitors. 

Moreover, you also need to pay heed to UI/UX, as features that are not accessible are of no use. So, invest heavily in making your software more simple, yet useful and a bit more advanced than others. 

Now, here you also need to select a suitable type of recommender system that would work best for your business and your users. We have already mentioned the six major types of recommender systems, you could choose anyone or can even contact our experts to know more!

4. Hire Dedicated Developers

Once you have finalized the designs and the features for your recommendation system, it is now time to build your perfect development team. Now here you have two options, either outsource your project or hire developers and testers specifically for your project, also known as staff augmentation. With the staff augmentation, you can have your own development team that will completely work on your project until it is deployed successfully.

Moreover, working with an experienced software engineering firm like Matellio also has some of the perks. You can choose any suitable hiring models based on your project requirements, and can even upgrade the functionality of the recommendation system accordingly. We provide full flexibility and convenience to all our customers under all circumstances.

5. Test and Deploy

Last but not least, you need to test the project, so as to eliminate all the bugs that were left unnoticed during the development phase. Now, here again, you have two options – either go for manual testing or opt automated testing method. 

Although both the testing procedures are efficient, automated testing has been a growing trend in the market for quite some time now. It eliminates the involvement of the human aspect and automatically detects even the minutest of the bugs in your software solution. Hence, you can choose any of the following, and we ensure to provide the best services in your suitable method. 

Additional Read: Why Does Your Enterprise Need Test Automation? 

How Much Does it Cost to Build a Recommendation Engine?

So, we are at the most awaited section of the blog – the cost of building a recommendation system. Like any other custom software solution, the cost of developing a recommendation engine also depends on some critical factors. To name a few, we have

  • 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.

  • Upgradation 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.

Besides all those factors mentioned above, there are many more that contribute to the overall cost of developing a recommender engine. You can always contact us to get an accurate estimate of your project. 


Key Takeaway!

So, that was all about a custom recommendation system along with its cost and development plan. To conclude, we can say that, in today’s digital era, having a software solution/mobile application is not a big deal. That’s where something exceptional and out-of-the-box comes in! Having a custom recommendation system with your brand name will not only offer an increased brand value but will even ensure that you get more valuable customers for your business in a short time.

Additionally, it is still not a common aspect of the global market. Hence, why wait for your competitors to develop it first? Reach us today and kickstart your recommendation engine development process in no time. Plus, you will get an expert consultation on your business idea absolutely free by filling out our consultation form. So, hurry up!

Till then, Happy Reading!

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