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Recommendation Systems and Smart Feeds for Applications
We build recommendation systems and smart feeds that boost engagement, increase time spent in apps, and improve monetization. Our solutions use advanced algorithms and integrate seamlessly with your products.
WHO IS THIS FOR?
- Social Networks: Personalized feeds of posts, photos, and videos to increase engagement and time spent in the app.
- Marketplaces: Product recommendations and curated collections to boost conversions and order value.
- Streaming Services: Personalized movie, series, and music recommendations to improve user retention.
- Content Platforms: Smart feeds for articles, news, and videos to increase views and content consumption.
What We Offer
Development of Recommendation Systems
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What It Is
Personalized recommendations that suggest content (photos, videos, posts) based on user behavior, preferences, and context. -
Who It Is For
Social networks, marketplaces, streaming services looking to retain users and increase engagement. -
How we work
→ Analyze user data and business goals to create relevant recommendations.
→ Develop algorithms using collaborative filtering, deep learning, and hybrid approaches.
→ Implement systems that update in real time and adapt to individual users. -
Example
A recommendation system for a social network increased engagement by 25% and average time spent in the app by 15%.
Building Smart Feed
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What It Is
Feeds that personalize content for each user, sorting it by relevance, engagement, or business goals. These feeds help retain users and boost activity. -
Who It Is For
Social networks, news apps, video platforms, and content services. -
How We Work
→ Develop ranking algorithms based on user behavior, preferences, and context.
→ Set up real-time data processing for minimal latency.
→ Optimize feeds for specific goals: longer viewing time, higher CTR, or better engagement. -
Example
A smart feed for a video platform updated recommendations in real time, increasing average viewing time by 30% and user interactions by 20%.
Optimizing Business Metrics
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What It Is
Fine-tuning recommendations to meet business goals, such as increasing CTR, interaction time, or conversions. -
Who It Is For
Companies looking for recommendation systems that directly drive growth in key performance metrics. -
How We Work
→ Run A/B tests to determine the most effective algorithms.
→ Optimize ranking and algorithm parameters to improve KPIs.
→ Provide monitoring tools to track CTR, engagement, conversions, and more. -
Example
A recommendation system for a marketplace increased conversions by 18% with personalized product suggestions and optimized content display.
WHY CHOOSE US?
PERSONALIZATION
Our systems adapt to user behavior in real time, ensuring relevant and timely recommendations.
PERFORMANCE
We optimize algorithms for minimal latency—under 200ms, even with millions of users.
RESULTS
Our solutions increase CTR by up to 20%, engagement by up to 30%, and improve LTV through precise recommendations.
TECHNOLOGIES
We use TensorFlow and PyTorch for deep learning, ElasticSearch for scalable search, and Spark for big data processing.
our cases
technology blog
Do you want to increase user engagement and retention?
Contact us and we will offer a solution on how to embed smart recommendations and feeds into your product so that the content finds its audience!"
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