From Data Chaos to Transparency: How We Built Analytics for Rostelecom

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ROMI

600%

Case data
Promotion features
From hypothesis to LP creation
PROFIT and key indicators

Tracking Key Metrics – DataLens Dashboard Visualisations

Screenshot: Statistical graphs and charts

Website

The platform is no longer active

Industry

Business solutions (ERP, CRM, automation)

Location

…

Region

Russia

Budget

The project was delivered in 2 phases. Total cost: 300,000 RUB

Project start

2022

Outcome

Reduced team workload for routine reporting

Outcome

Real-time tracking of key metrics

Outcome

KPI performance monitoring

Outcome

Lower operational costs

End-to-End Analytics for "Business Drive Academy" Project

Automate reporting

Ensure accurate data collection

Reduce data breach risks

Cut unnecessary service costs

Build a scalable data system

Challenges Faced During the Project

Client doubts

Previous team failed to set up analytics, which caused distrust of new solutions.

Rejection of foreign services

Client avoided foreign solutions due to risks of sanctions and possible blockages.

Rejection of paid services

Reluctance to use additional paid tools in the data transmission chain.

Yandex.Metrica limitations

Raw data transfer from Yandex.Metrica and AppMetrica to ClickHouse was not supported.

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Key Project Stages

Stage 1: Preparation Phase
- Platform identification (Yandex Cloud)
- Customer requirements analysis
- Selection of tools (Yandex.Metrica, AppMetrica, ClickHouse, DataLens)
Stage 2. Setting up data collection
2.1. Implementing web analytics
- Installed Yandex.Metrica on 2 websites:
  - Welcome landing page
  - Main platform with courses
2.2. Setting up mobile analytics
- Integrated AppMetrica tracking into iOS and Android apps
2.3. Configuring conversion tracking in Yandex.Metrica
- Transitions to introductory lessons
- Transitions to registration
- Platform registration
- Lesson views on the platform
Stage 3. Data integration and processing
3.1. Setting up user event parameter transmission
- Each user registered on the platform is assigned a unique user ID (UserID) ➡ We pass these to Yandex.Metrica as visit parameters ➡ Link them with Yandex.Metrica's ClientID
3.2. Organising data storage
- Created a database using Managed Service for ClickHouse within Yandex Cloud
3.3. Automating data transfer
- Developed Python scripts for:
  - Advertising costs (Yandex.Direct, VK)
  - Data from Yandex.Metrica
  - Data from AppMetrica
Stage 4. Infrastructure setup
- Creating a virtual machine via Compute Cloud
- Uploading data transfer scripts and configuring their regular execution
Stage 5. Data visualisation
- Configured data visualisation in DataLens so the client receives the final analysis results in the form of a dashboard.
- During the project, we created:
  - Datasets and data merging at the dataset level
  - Connection to ClickHouse
  - Charts
  - Dashboards

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Key results

The team implemented a secure analytics solution for the client on Yandex Cloud. A unified dashboard was created, reports were automated, and control over KPIs and advertising costs was established — all without the use of foreign services. Key results:

Information security compliant with Federal Law 152 (highest protection level — SU-1)
Data retention ensured through automatic backups and replication
Consolidation of all company data for analysis of any complexity and depth
Hosting of websites and web services in the cloud for maximum scalability and performance speed
Maximum visualisation speed thanks to built-in integration with Yandex's BI system, DataLens

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