Keyword research taught without shortcuts
We started Meroladuk in 2017 because the instruction available at the time was shallow. The real mechanics of how people search — and why that matters for visibility — deserved a proper platform.
Keyword research sits at the intersection of language, intent, and data — and most courses only teach one of those three.
When someone types a query into a search engine, they're expressing a very specific need at a specific moment. Understanding that moment — not just the words — is what separates good keyword research from mechanical data collection. Volume and competition scores are easy to pull from any tool. Reading the intent behind a phrase takes practice and pattern recognition.
Our sessions work through real scenarios: choosing between closely related phrases, deciding when low-volume terms are worth targeting, and interpreting SERP layouts as evidence of what Google thinks a query means. Each walkthrough uses live tools and actual data, not simplified mock-ups.
Live tools, real data — no sanitised demos.
Fionnuala Driscoll
Lead Instructor, Keyword Strategy
How the instruction is structured
Fionnuala spent eight years doing keyword research for editorial teams, e-commerce operations, and independent publishers before moving into instruction. Her work spans verticals where intent signals are genuinely difficult to interpret — health, finance, legal — and she brings that specificity into every session.
Sessions at Meroladuk are not pre-recorded slides read aloud. The format is demonstration-first: you watch an expert work through a problem in a real tool, then work through a parallel problem yourself. Feedback is specific and tied to the decisions made, not general encouragement.
How sessions are actually run
Each session starts with a brief context-setting: what type of site or project we're researching for, what stage of the process we're at, and what decision we're trying to make. That framing matters because the same keyword can be the right answer or the wrong one depending on context.
- Define the decision — clarify what you're actually trying to figure out before opening any tool
- Collect raw data — use Ahrefs, Semrush, or Google Search Console depending on what's available
- Read the SERP — interpret the results page as evidence of intent, not just competition
- Map to content — connect keyword groups to specific pages, not keyword lists to vague categories
- Document the logic — write down why you included or excluded each cluster so decisions are repeatable
Tools change. The thinking behind them doesn't.
Platform features shift regularly — metric names change, data sources update, UI gets restructured. We teach the reasoning that sits underneath tool output rather than memorised click sequences. If you understand why a difficulty score is a proxy metric and not a hard fact, you can work with any tool that produces one.
See what the learning program covers in detail
View the program