If a signal stays inside a report without an owner, the team learns about the issue later and spends more time finding the cause. At this scale the delay affects a demand area, not one keyword.
Operating daily
27,000 queries every day: from monitoring to owned SEO actions
At 27K queries and roughly 8K URLs, rankings are no longer something a team can simply “check”. Important declines disappear inside normal daily movement. I initiated an internal system that groups changes by demand area and turns a signal into owned investigation and work.
Case at a glanceInitiated the system, selected the stack and defined the data architecture, aggregation rules, alerts and ownership model.
The system runs daily across ~27K queries and ~8K URLs. A comparable recurring check costs more than 10× less than the selected SaaS scenario.
10×+Selected SaaS scenario
1×In-house system
Selected SaaS scenario versus the in-house setup at comparable daily monitoring volume.
The value is not rank collection but a shorter path from signal to action
At tens of thousands of queries, manual checking stops scaling. The important outcome is connecting visibility movement to a category, its context and an accountable specialist so the signal does not remain a row in a report. The system turns daily noise into an owned investigation and action flow.
Key decision07
What the team gets beyond lower operating cost
The system is designed around action.
Category-level view
Movement is visible at the level of a demand area.
Owned next step
A signal is connected to a task and category owner.
Prepared evidence
Collection and aggregation are automated so specialists can focus on interpretation.
Why a rank report was not enough
At this scale the team can have thousands of observations without knowing what deserves attention first. The requirement was to see demand areas, filter normal noise and route meaningful movement to the person who owns the category.
Why build an in-house layer
The decision came from monitoring scale and workflow requirements.
SaaS monitor
Faster to start and easier to maintain, but custom clustering and ownership must fit the product.
In-house layer
Requires engineering and maintenance but aligns to the catalog and team structure.
How a signal reaches an owner
A cluster is a group of queries representing one demand area.
A-Parser
Collect rank and SERP observations.
ClickHouse
Store and aggregate by queries, URLs and clusters.
Superset
Expose the analysis to specialists and leadership.
Telegram → Kaiten
Turn a meaningful deviation into an alert and assigned task.
Investigate
A specialist decides whether the signal requires SEO action.
How the system reduces daily noise
A weekly median reduces day-to-day noise. A deterioration of roughly 10% or more versus the previous week becomes a review trigger for the specialist.
Not every lost position has the same business value
The platform helps distinguish ordinary ranking movement from changes that deserve real priority.
High-sensitivity categories
In some categories, top positions have a stronger relationship with business performance, so deterioration deserves faster attention.
Lower-sensitivity categories
In others, ranking movement has a weaker commercial effect and should not automatically displace more important work.
Category-level prioritization
The signal is interpreted in category context rather than treating every keyword loss as equally important.
My responsibility vs the team
Product design and day-to-day investigation are separate responsibilities.
My responsibility
Problem definition, toolchain, data architecture, aggregation rules, alerts and ownership model.
Team
Technical build plus day-to-day investigation of signals.
Context & measurement
- Context
- Large e-commerce business · operating data product
- Scale / period
- ~27K queries · ~8K URLs · daily monitoring
How the cost was compared
The comparison covers recurring rank-monitoring costs at a comparable workload. Build cost and shared infrastructure are tracked separately.
Search analytics
Facing a similar challenge?
Tell me where SEO is blocked by product, engineering or data.