Case study

Data-driven measurement and performance analytics Data-driven measurement and performance analytics

Data-driven measurement and performance analytics

We are building a comprehensive measurement and analytics framework that provides a clearer view of website traffic, user journeys and the performance of individual marketing channels.

Data-driven measurement and performance analytics – Data-driven measurement and performance analytics

About the project

For CVonline.hu, we are building a comprehensive measurement and analytics framework that provides a clearer view of website traffic, user journeys and the performance of individual marketing channels. Alongside reviewing and improving the GA4 measurement setup, we standardise conversion tracking, analyse campaign-driven traffic and create reporting that connects marketing activity with measurable business outcomes.

The objective is not simply to collect more data, but to understand which channels, campaigns and user journeys actually contribute to applications and business performance. The resulting analytics framework supports ROI calculation, more efficient allocation of marketing budgets and continuous performance optimisation.

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FAQ

Frequently Asked Questions

What does Krankovics Béla do at ComLab?
Krankovics Béla works across ComLab’s digital and technology practice, focusing on digital business development, AI-powered solutions and measurement systems. A key part of his work is turning strategic business and communication objectives into practical digital products, automated processes and measurable solutions.
What are Krankovics Béla’s main areas of expertise?
His main areas of expertise include digital strategy, digital product development, marketing technology, data-driven solutions, automation and the business application of artificial intelligence. More recently, his work has focused particularly on AI visibility, generative search and understanding how brands appear in the answers and recommendations generated by AI systems.
What is AI visibility?
AI visibility describes how prominently and accurately a brand, company, product or expert appears in generative AI systems such as ChatGPT, Gemini or Perplexity. It is not only about whether a brand is mentioned, but also about the context in which it appears, the topics it is associated with, the sources AI systems rely on and how the brand is positioned compared with its competitors.
How is AI visibility different from traditional SEO?
SEO primarily focuses on how websites appear and rank in search engine results. AI visibility addresses a broader question: how generative AI systems understand a brand, what information they associate with it and when they include it in generated answers or recommendations. The two disciplines are closely connected, but they are not the same.
How can a brand’s AI visibility be measured?
Measuring AI visibility starts with identifying relevant user questions, topics and decision-making scenarios, then analysing responses across multiple AI platforms on a recurring basis. Metrics can include brand mention rate, relative position, competitor visibility, recommendation context, cited sources and topic coverage. The objective is not to analyse a single prompt, but to identify recurring patterns, differences and changes over time.
What is the ANSWER Framework?
The ANSWER Framework is a methodology for systematically improving AI visibility. Its purpose is to move AI visibility beyond one-off optimisation and turn it into an ongoing process built around research, measurement, content, technical improvements and continuous validation.
What types of projects can Krankovics Béla support?
He works on projects where communication, digital technology, data and artificial intelligence intersect. These can include AI visibility strategy and measurement, digital product and service development, web platform design, marketing technology and CRM solutions, automation, and the development of AI-powered business and communication tools.