Want to reduce sales costs? Use a recommender algorithm

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Filtering virtual information or data using recommender algorithms will provide the most relatable and relevant items to the user based on their choices and previous engagements. This is known as a recommendation system. The recommendation system is so popular with the industry giants. They have an established recommendation engine that helps them attract more customers to their platforms and increase sales using AI technology. The recommender engine is very vital for reducing costs in every segment in any business model. Reducing sales costs, marketing costs, analytics costs, etc can be done by a recommendation system easily.


Let see some data based on this -


  • Amazon’s recommendation system reduces 29.2% of the total sales cost and increases in growth annually.
  • Netflix cut costs by 10% of annual spendings that is approximately $156 million.
  • Facebook credited 40% of investment costs using a recommendation algorithm.
  • Linkedin saves 15.3% of costs in every segment they spend.
  • Overall YouTube’s regular sales costs reduced by 55% by its recommendation system.
  • Alibaba saved up to 30.7% of its costing through delivery purposes.
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    You can see the signs of progress of the giants using a recommendation engine. Now you can calculate the future for your goals. How can a recommender system help you reduce costs? The answer is reduced sales activity through recommendation algorithms.


    Recommendation engines have become important as companies use the information to grow their market share. By understanding consumer behavior, trends and needs, your organization will automatically raise revenue and help consumers more. This occurs without costly salespeople trying to annoy the masses.


    In an analog data management system, a company needs different employees for different work segments. Data analytics, data manager, data organizer, etc positions are fulfilled by people, and you have to pay them for their services every month/year. This is costly and not timely. We allow you to install a recommender system into your business without hiring. Let your business grow as fast as true demand rises.


    There are many benefits of using a system like this. Reducing costs is one of them. But the main thing is to utilize the recommendation system as your goals are set to retrieve scalable benefits. Additionally, your recommendation engine will provide historically and purchase behavior analysis which can be used in inferential data analysis. If this is something you’re interested in - please reach out to us and receive your implementation plan.


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    We at Superior Data Science can analyze the data of your organization to make an effective decision based on the forecasting done by using AI and machine learning techniques.


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