Web analytics forms the backbone of the data-driven approach in digital marketing.
Using a web analytics interface, we can set up data collection and basic reports and create end-to-end analytics solutions. Not only can we upload, merge, process, and visualize your data, but we can also identify growth points for your website and improve your conversion rate.
These days, people are no longer afraid to take risks in everyday life, and that's great! But when business revenue is at stake, even a minor mistake might be costly. Data-driven decisions are becoming a key component of business decisions, especially in digital marketing. More than anyone else, digital marketers understand the importance of collecting and analyzing data. But what if there are a dozen different data sources outside of standard reports? How do you deal with all this data?
That's why at Netpeak we have focused our expertise on the right things: we can set up automatic data collection, aggregate your data from all sources, and create easy-to-read reports of any complexity level. You can feel confident knowing that your solution is data-driven.
Alexander Konivnenko Head of Web Analytics
Solve problems with data analytics
Standard analytics tasks
Analytics systems can be set up to correctly monitor digital channels, track customer behavior, and acquire new customers.
Custom analytics solutions
Calculate the ROI of customer acquisition channels using a standard or custom attribution model, and track cross-platform, cross-domain, and online/offline user behavior.
Income growth and average order value increase
Use the CRO service to improve the performance of your customer acquisition channel and directly increase the profitability of your business. Get more out of the traffic you already have.
Use web analytics to setup standard tasks
Google Analytics setup
Configure the required settings, events, reports, and notifications in your Google Analytics account, and create a technical requirement document to integrate the website and analytics system.
Switch from Universal Analytics to Google Analytics 4
Enable data collection in Google Analytics 4, set up all the necessary events, and prepare technical requirements to import data from your website to the analytics system.
Enhance your e-commerce setup
Install an enhanced e-commerce module, configure Google Tag Manager, and develop a step-by-step technical requirement document to send purchase and user behavior data to the analytics system.
Measurement Protocol Implementation
Create a step-by-step technical requirement document to transfer purchase and user behavior data from your CRM and ERP systems, databases, and other external sources to Google Analytics.
Google Tag Manager Setup
Set up triggers, tags, and variables in Google Tag Manager, and create a technical requirement document for programmers to implement the necessary tracking codes.
Create custom analytics solutions and BI systems
We can help you decide which data sources to include in the final solution and identify the data, reports, or dashboards that are required. You will also get a diagram of the analytical solution.
Create special connectors — program codes that import API data and store it in a data warehouse.
When data is imported into separate tables in the data warehouse, our SQL code combines and aggregates the data into summary reports.
The last step is to visualize the data stored in the warehouse. We build custom dashboards in Google Data Studio, Power BI, and Tableau.
Types of data we can work with
We can obtain data on clicks, impressions, audiences, and other metrics from advertising systems such as Google Ads, Facebook Ads, and so on.
Web analytics systems
We can extract data from Google Analytics, AppsFlyer, and other web analytics platforms for an in-depth assessment of website or app performance and combine it with sales and profit data.
CRM and ERP systems
Process data on transactions and clients, and combine it with ad campaign data to get a full picture of the effectiveness of your marketing campaign.
Accounting and warehouse management systems
Process data from your 1C or other accounting systems for in-depth cash flow or product analysis.
Services and tools we use for analytics solutions
Processing and orchestration
Google BigQuery — A fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is an excellent and inexpensive solution for storing and processing data from different systems without having to bind it to a physical server.
MySQL—An open-source relational database management system. Most classic business software products for ordinary users are based on MySQL.
PostgresQL или Postgres — Also known as Postgres, this is a free and open-source relational database management system that emphasizes extensibility and SQL compliance.
Greenplum — A big data technology tool based on MPP architecture and the Postgres open-source database technology.
R — A programming language that's optimized for statistical analysis and data visualization. It is an open-source free software environment within the GNU package.
Python — A general-purpose programming language considered to be one of the best data science tools for big data jobs and machine learning.
SQL — A structured query language, which is a computer language for storing, manipulating, and retrieving data stored in a relational database.
DBT — An open-source command line tool that helps analysts and engineers transform data in their warehouse more effectively.
Apache Airflow — An open-source workflow management platform for data engineering pipelines.
Microsoft Power BI — One of the most popular platforms for visualizing data and creating interactive charts and reports.
Google Data Studio — An online tool for converting data into customizable informative reports and dashboards introduced by Google as part of the Google Analytics 360 Suite Enterprise.
An American company that develops software for interactive data visualization and business analytics of the same name.
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