LinkedIn Content Strategy & Writing Style
Co-founder @ Snippet Digital // Search Journey Optimization
1 person tracking this creator on Viral Brain
Suganthan Mohanadasan positions himself as a high-level technical architect at the intersection of SEO and AI engineering, moving far beyond traditional search marketing into the realm of Search Journey Optimization. His content strategy centers on "building in public" by releasing sophisticated, open-source tools like MCP servers that bridge the gap between LLMs and raw search data. He is notable for his rigorous, experiment-driven transparency, often debunking AI hype with hard statistical comparisons between LLMs and classical models like Prophet or ARIMA. By blending deep technical execution with strategic consulting, he provides a unique value proposition: he doesn't just predict the future of AI search; he builds the infrastructure for others to navigate it.
10.0K
7.0K
140
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4.3
190
4
Every SEO I know has the same routine. Open Google Search Console. Click Performance. Add a filter. Add another filter. Compare date ranges. Export to a spreadsheet. Pivot. Squint. Thirty minutes la…
Nobody has cracked AI SEO yet. Anyone telling you otherwise is selling something. But here is what we do know after months of experimentation at Snippet Digital We were stuck at position 6 on Googl…
Whenever someone asks, “What’s your favourite SEO tool?” and you answer “Google Search Console” you’re not as cool or elite as you think you are. Thank you for your attention to this matter.
I spent 6 hours last month turning a Screaming Frog CSV into a client deliverable. Not crawling. Not strategising. Just... wrangling rows in a spreadsheet. Categorising issues. Scoring severity. Wri…
Every AI tool I've used has the same problem. You open a chat. You explain your situation. It helps you. Then you close it and next time? It's forgotten everything. It's like hiring an assistant who…
I tore down my old personal WordPress site and rebuilt it from scratch. Nothing was broken. It just didn’t feel like me anymore. It had turned into a lead gen machine wearing my name. I’d outgrown…
4.3 posts/week
Posts / Week
1.8 days
Days Between Posts
4
Total Posts Analyzed
HIGH
Posting Frequency
140.375%
Avg Engagement Rate
STABLE
Performance Trend
170
Avg Length (Words)
HIGH
Depth Level
ADVANCED
Expertise Level
0.86/10
Uniqueness Score
YES
Question Usage
0.7%
Response Rate
Writing style breakdown
<start of post>
I spent 48 hours stress testing the new Claude Analysis Tool to see if it could replace my Python scripts for SEO forecasting.
The results were not what I expected.
I gave it 2 years of raw click data from a declining e-commerce site. No cleaning. No formatting. Just a messy CSV.
Find the point of failure and forecast the recovery.
Claude didn't just plot a line. It identified a specific cannibalisation issue between the category pages and the new blog subfolder that started exactly 14 weeks ago.
It wrote the Python code, ran the regression, and visualized the overlap in a scatter plot.
→ 14% traffic loss attributed to internal competition.
→ 3 specific URL clusters identified as the culprits.
→ A 90-day recovery model based on de-optimising the blog posts.
The scary part? It took 45 seconds. My manual script takes 20 minutes to configure and another 10 to debug the data types.
But there is a catch.
If you don't prompt it to check for seasonal outliers, it ignores them entirely. It saw a "growth trend" in November that was actually just Black Friday noise. It’s a calculator, not a consultant.
We are moving into an era where the "how" of data analysis is becoming free. The value is now entirely in the "what" and the "why."
If you aren't using LLMs to crunch your GSC exports yet, you are working 10x harder for the same insight.
I wrote a breakdown of the 5 prompts I used to get these visualisations.
Link in the comments 👇
<end of post>
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