Recommendation System Made-to-Order

Incorporate our referral systems to achieve remarkable commercial gains.
Recommendation

Recommendation System: What Are They?

Companies can provide individualized offers and experiences to their customers through AI-based recommendation system algorithms. Customer engagement and lifetime value are influenced by quality recommendations.
SITKA creates solutions that are customized and tailored to each company’s KPIs.
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Why Customize?

Customer engagement is becoming increasingly difficult for both online and offline organizations. Digital era customers are increasingly managing the purchasing process and deciding WHAT they want, WHERE they want it, and WHEN they want it, thanks to their social networks and smartphones.

We create solutions that will benefit your company

AI-based recommendation system for content

A personalized content AI-based recommendation system can boost engagement and lower bounce rates. This smart feature selects the appropriate information for each visitor automatically. Real-time behavior, visitor profiles, and similar journeys are used to make recommendations.

25% faster

Users can find requested material much quicker.
Recommendations-for-Products

Recommendations for Products

Personalized product recommendation system metrics can boost online sales and average order values. This sophisticated feature makes a product recommendation system based on real-time behavior, order history, and comparable journeys. Increase upsells and cross-sells by including it on product and checkout pages.

Up to 5 times faster

Users can find preferred products for the system design recommendation system.

The Advantages of Customized Recommendation System

Realtime

Data for recommendation system in Real-Time.

Personalize

Several Personalization Strategies Depending on Your Business Goals.

Customize

System design recommendation system specifically for your project.

Problem Definition: How Do We Create a Recommendation System?

Data Exploration and Analysis
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Extraction of information
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Improved Customer Service
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A/B Evaluation
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Modeling Data
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Optimized Customer Experience

Problem Definition: How Do We Create a Recommendation System?

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Data Exploration and Analysis

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A/B Evaluation

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Extraction of information

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Modeling Data

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Improved Customer Service

We combine innovative technologies with a client-oriented approach. Let us create easy-to-use and reliable custom automated document processing software for your business. You can integrate it with your existing ERP/CRM system, application, or platform.

Why Should You Work with Us?

We make it simple to create fantastic data for recommendation system metrics.
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Models that are up to date

We're continuously on the lookout for innovative ways to enhance our predictions and achieve the greatest potential outcomes for a system design recommendation system.

Customizable-Solutions

Customizable Solutions NLP-benefits-1

We don't settle for second best. Our solutions are customized to meet the needs of our customers and the nature of their data for the recommendation system.

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Scalable Outcomes

We make preparations for the future. Our suggestion systems and solutions will evolve in tandem with your company, enhancing your skills.

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Team of Professionals

We are motivated to achieve greatness in all we do for our clients.

Successful stories of our customers

  • Smart TV App Movie Recommendation system metrics

    The client is in the digital home entertainment industry for Smart TVs. It's a popular premium video-on-demand service that lets users watch newly released films in high definition or choose from a library of over 7000 titles. They have 1.5 million monthly active users on their SmartTV app. As a consequence, each customer receives fresh individualized recommendations, and customers may find their favorite movies faster.

  • Building Predictive Analytics Module for E-Commerce Platform
    The Client is an e-commerce provider who cooperates with more than 50 brands. The Client was interested in a solution for generating cross-brand and single-brand recommendations. The business goal was to use machine learning (ML) to increase sales, revamp customer experience, and attract new clients and retain loyal users of the online platform. Eventually, the Client acquired a first-class e-commerce ML-led system.

Contact Us

Drop us a line about your project or describe a challenge your company needs help solving. We’d love to discuss how SITKA can work with you.

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