Big Data SEO. One algorithm, every signal.
Every tool shows you data. Bubbles1 tells you what to do with it. Our own algorithm analyzes signals from SEO, GEO/LLM, SEA, social media, Google Search Console / Bing Webmaster Tools and your server log files — detects the gaps between them, and proactively tells your team which topics underperform and which content to build first.
Six signals, one truth
Single-channel tools see single-channel problems. The engine cross-references every source a topic lives in.
SEO / SERP
Rankings, SERP features, competitor positions — the classic organic layer, tracked daily.
GEO / LLM
Citations, share of answer and drift across ChatGPT, Gemini, Claude & Perplexity.
SEA
Paid search terms, costs and conversions — where you're paying for clicks organic should own.
Social Media
Topic demand and engagement signals — what audiences ask before search engines see it.
Search Console & Bing WMT
Real queries, impressions, clicks and index coverage — straight from both indexes that feed AI answers.
Server Log Files
How Googlebot and LLM crawlers actually behave on the site — crawl budget, errors, ignored sections. The ground truth.
Fix the pipes before the content
Content built on broken crawling is wasted budget — logs surface the issues no simulator sees.
Fix the pipes before the content
Content built on broken crawling is wasted budget. The engine analyzes your server logs and flags critical issues that must be fixed before any content work starts.
- Crawl budget waste — bots burning visits on parameters, filters and dead ends
- Blocked opportunities — key pages Googlebot and LLM crawlers rarely or never visit
- Error patterns — 4xx/5xx spikes and redirect loops seen by real bots, not simulations
- AI crawler visibility — GPTBot, PerplexityBot & friends: who reads what, how often
🗄️ Critical — fix before content work
From raw signals to build-this-first
Ingest
All six sources stream into one data model per client, per topic, per market.
Normalize
Keywords, prompts, ads and posts are clustered into comparable topics.
Detect gaps
The algorithm finds mismatches: demand without content, spend without rankings, citations lost to competitors.
Prioritize
Every gap is scored by impact and effort — a ranked list of what to build first.
Communicate
Pro-active alerts and briefs land with your team — before the client asks.
The engine speaks first
No dashboard archaeology — the algorithm delivers a ranked, cross-channel priority feed to your team.
The engine speaks first
No more dashboard archaeology. The engine tells you where topics underperform in SEO, GEO/LLM and/or SEA — and what to do about it.
- Gap alerts — "high SEA spend, no organic ranking" or "LLM demand, zero citations"
- Content priorities — a ranked build-first list per client, refreshed continuously
- Cross-channel context — every recommendation shows which sources triggered it
- Straight into workflows — one click from recommendation to brief to ticket
🛰️ This week's build-first list
Common questions
Which integrations does the engine need?
Why does log file analysis matter for SEO/GEO?
How is this different from a dashboard with all my data?
Can I adjust how the algorithm prioritizes?
Does it work without SEA or social data?
Stop guessing. Start prioritizing.
Connect your sources and get your first build-first list this week.