Ideas we realize. Problems we solve.
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Predictions
Foresight
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Forecasting
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Recommendations
Content personalization.
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Risk modeling
Algorithms. Statistic.
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Spam
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Clusterization.
Clustering. Segmentation.
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Model training
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Patterns recognition.
Trends and seasonality. Correlation.
Data science process and timeline
While the estimate depends on your project idea, we work in short, focused iterations — so you’ll see results asap. If you need help with project ideas, please read the section above.
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1
Start
Start of iteration 1
✔ Estimated time: 5 days.
✔ Start without the overhead of hiring in-house.
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2
Data Science
Work execution
✔ Estimated time: 2 weeks
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3
Finish
Finish of iteration 1
✔ Estimated time: up to 1 week.
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4
Start
Start of iteration 2
✔ We provide support with data science through ongoing maintenance and other options.
We are certified partners of
Our clients
We deliver results for brands across the USA, Australia, Canada, Europe, and Asia.
These include companies in E-commerce, Social Discovery, iGaming, Web3, Healthcare, iOT, OTT, EdTech, MarTech, and FinTech.
Client testimonials
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“They did a lot of work studying real user data – they built hypotheses and ran experiments that led to a significant increase in our conversions.”
Analytics director at Plarium
Anton Polischuk
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“Dot Analytics’ work was completed on time and met our expectations. We received a ready-made infrastructure for collecting and consolidating data, moving away from manual and fragmented work..”
CTO at DataRoot Labs
Ivan Didur
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“We had so-called raw business data and we wanted to centralize it for further analysis. The main thing for us is that we got high-quality and accurate data. We are convinced that they did a great job!
CEO, co-founder of Bookimed
Yevheniy Kozlov
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“Working with Dot Analytics to develop the AI capability of our new DataRoot Labs platform has been transformative for us and our customers.”
CEO, co-founder of DataRoot Labs
Max Frolov
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“We needed to combine, process and display a large amount of data. It was a complex job and I am 99% satisfied with the result.”
CEO, co-founder at Futurra Group
Vitaliy Shatalov
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“We were interested not only in working with user data and the site, but also in comprehensively improving marketing. We are very pleased with the result.”
CEO at Kismia
Vlad Amardi
“They did a lot of work studying real user data – they built hypotheses and ran experiments that led to a significant increase in our conversions.”
Analytics director at Plarium
Anton Polischuk
“Dot Analytics’ work was completed on time and met our expectations. We received a ready-made infrastructure for collecting and consolidating data, moving away from manual and fragmented work..”
CTO at DataRoot Labs
Ivan Didur
“We had so-called raw business data and we wanted to centralize it for further analysis. The main thing for us is that we got high-quality and accurate data. We are convinced that they did a great job!
CEO, co-founder of Bookimed
Yevheniy Kozlov
“Working with Dot Analytics to develop the AI capability of our new DataRoot Labs platform has been transformative for us and our customers.”
CEO, co-founder of DataRoot Labs
Max Frolov
“We needed to combine, process and display a large amount of data. It was a complex job and I am 99% satisfied with the result.”
CEO, co-founder at Futurra Group
Vitaliy Shatalov
“We were interested not only in working with user data and the site, but also in comprehensively improving marketing. We are very pleased with the result.”
CEO at Kismia
Vlad Amardi
why choose us as your data analytics agency
We don’t just deal with data, we understand your industry
Our expertise in a range of industries allows us to deliver solutions that align with industry standards and our clients’ expectations.
Explore our Industry-Specific Expertise
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E-commerce
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iGaming
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Web 3.0
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SaaS
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Crypto
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Social Discovery
FAQ
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What is the difference between trend prediction, forecasting, and foresight analysis?
Forecasting builds short-term expectations based on historical data. Predictions are forecasts of specific events or customer actions. Foresight is strategic modeling of future scenarios for making long-term decisions.
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What technologies and methods does Dot Analytics use for content personalization and customer recommendations?
We employ hybrid recommendation systems that combine content-based filtering, collaborative filtering, and deep learning techniques.
To enhance personalization quality, we apply natural language processing (NLP) methods, user behavior clustering, and model training on real-time customer journey data. -
How quickly can we expect to see the first results after implementing forecasting or recommendation models?
Initial results typically become visible within 1 to 3 months after deployment, with improvements in conversion rates, customer retention, and sales performance.
The exact speed depends on the volume and quality of available data as well as the chosen modeling approach. -
How do I get started?
Getting started is easy. Reach out to us with your needs, and our data engineering consultant will tailor data processing solutions to transform your data into a valuable asset.