Polish and Central & Eastern European market. Professional development courses: data science, programming, project management, digital marketing. Over 200 courses, strong instructors, genuine learner outcomes.
Organic traffic accounted for 4% of total sessions. Paid channels carried the weight. The team had tried content marketing, had a blog, ran webinars — but organic share stayed flat.
The problem wasn't effort. It was the conceptual model the entire presence was built on.
The platform described courses the way a course catalog works: course name, format, duration, price, syllabus. Precise, structured, complete.
But a person who doesn't yet know which course they need doesn't search 'Python course Warsaw.' They search 'how to automate reports in Excel' or 'what skills does a data scientist need.' The platform was visible only to the first group. For the second — it didn't exist.
This wasn't a keyword problem. It was an architectural problem: the entire content structure was organized around what the company sells, not around the questions people bring to search.
We mapped search demand across every topical vertical the platform covers — not from the product outward, but from the user's problem inward.
The volume of search demand in topics the platform's courses address was substantial. But it was phrased around the problem the person wants to solve — not around the format of a learning product.
The query 'kurs Python' is searched by someone who already knows what they want. That's a minority. Most people search 'jak automatyzować raporty w Excelu' or 'jakie umiejętności potrzebuje data scientist.' The platform was visible only for the first group. For the second — it didn't exist.
Second finding: the site structure mirrored the course catalog. No entry point oriented toward someone who doesn't yet know which course they need.
Rethought the architecture from problem to product. Added a navigation layer between the search query and the specific course — pages in the format 'How to become X' and 'Where to start in Y,' answering questions that precede the product choice.
Rewrote the language of key pages. Product catalog language gave way to search query language — without simplification and without losing the precision of course descriptions.
Built a content layer for research demand. Materials that close the 'still thinking' stage: career path comparisons, profession overviews, specialization guides in Polish and English.
Introduced end-to-end measurement. For the first time, it became visible which content drives registrations and purchases — and which only drives reads.
| Before | After | |
|---|---|---|
| Organic traffic / month | 94,000 | 430,000 |
| Organic share of total traffic | 4% | 31% |
| Registrations from organics / month | 1,240 | 8,700 |
| Revenue from organic channel / month | €112,000 | €487,000 |
| Top-10 coverage for target queries | 180 | 2,400+ |
The product was described in the company's language. Search works in the language of a person who has a problem.
Between them lies a gap that goes unnoticed until you look at the data from the right angle. This isn't a copywriting question. It's a question of conceptual model: from what do you build your search presence — from the product or from the person?
The answer to that question determines everything else.
Organic underperforming despite a strong product and clear demand?
We'll check what question your search presence is built on.