About the service
In large products, SEO issues rarely look like “one single bug.” More often, they are a combination of factors and a consequence of how the system is built: URLs, routing, indexation rules, templates, and the way they scale.
We perform a system-level analysis and model how signals are passed within your product, where conflicts arise, what creates crawl waste, and which constraints are holding back growth.
The result is a roadmap: a list of tasks, implementation instructions/technical specifications, and execution priorities.
What’s included
- Analysis of URL architecture and routing logic
- Indexation model: canonical, robots, parameters, sitemap
- Page- and template-level SEO signals
- Detection of duplicates and signal conflicts
- JS rendering and indexation risks (at the architecture level)
- Core Web Vitals / Web Performance as ranking and behavioral signal factors
- Crawl-path logic and discoverability
- Impact/Effort prioritization of technical changes
What Exactly Is Analyzed
This service helps identify technical reasons that prevent organic traffic growth and pinpoint growth opportunities.
We view the product from both the user and search engine perspectives — and find where it fails to meet Google requirements and where bottlenecks limit scaling.
- URL architecture and page generation rules (templates / sections)
- Routing logic (dynamic segments, parameters, facets) and its impact on indexation
- Indexation signals: canonical / noindex / robots / sitemap and how they interact
- Template SEO patterns (meta, headings, schema, linking) and their scalable impact
- Duplicates and signal conflicts (canonical vs noindex vs redirects)
- Discoverability: crawl paths, depth, orphan pages, internal “dead ends”
- JS rendering risks (content and links that appear only after render)
- Core Web Vitals and their impact on rankings and behavioral signals
How to Prepare for More Accurate Analysis
We can start even without “perfect” data. But if you have the opportunity, these steps improve accuracy and reduce the time needed to identify root causes.
- Access to Google Search Console (read-only is enough)
- A list of main page types/templates (home/category/product/article, etc.)
- A brief description of routing logic: which parameters exist, which sections are data-generated
- If available — server logs
- A list of major releases/migrations from the last 3–6 months (if any)
What Is Important to Understand Honestly
We do not “promise top-1 positions” and do not provide tips and tricks. We systematically improve the product so it meets the requirements and expectations of search engines and users.
If the product is actively evolving, it is important not only to “fix what needs changes now,” but to build governance so that future changes and growth do not create chaos.
Risks & Limitations (So Expectations Stay Realistic)
- The speed at which results appear depends on crawl frequency and site scale: sometimes the first signals are visible within 2–6 weeks after implementation.
- Results are affected not only by on-site changes, but also by competitors’ actions in search results and algorithmic factors.
- Architectural changes have a large blast radius. That is why we almost always recommend staged rollout + control metrics, rather than “implement everything at once.”
What the Team Receives
Not a template SEO audit, but a structured engineering document with technical constraints, their impact, and ways to fix them.
- If server logs are available, the audit is supplemented with log-based analysis of crawl behavior and indexation anomalies.
- For SPA / SSR projects, rendering, hydration, and JavaScript execution bottlenecks are analyzed separately.
How the Work Is Done
The analysis is built around data, system context, and real technical constraints of the project — without template “checklist audits”.
We gather available data about the site, indexation, rendering, templates, internal structure, and search engine behavior. In parallel, we build context: how the system is built and which constraints affect SEO.
- Collected dataset for analysis
- Initial findings and potential risk areas
We conduct a deep analysis of technical constraints, system conflicts, bottlenecks, and factors that may affect crawlability, rendering, indexation, internal linking, or scalability.
- List of technical findings
- Root cause analysis
- Examples and edge cases
Findings are turned into implementation-ready recommendations with impact explanations, fix examples, technical details, and prioritization.
- Implementation guidelines
- Prioritized backlog
- Impact / effort estimation
Handover of materials to the team, alignment with developers / PM / SEO stakeholders, answers to questions, and clarification of implementation details.
- Final audit package
- Q/A session if needed
The focus is not on checklists, but on finding technical constraints and systemic root causes. The analysis accounts for site architecture, rendering, indexation, templates, internal structure, JavaScript, and other factors that influence rankings, crawlability, and scalability.
The team receives a structured document with technical findings, risk explanations, problem examples, recommendations, and a prioritized backlog for implementation.
Yes. Recommendations are prepared in a format the dev team can use: with examples, context, impact descriptions, and implementation guidance. If needed, we can provide Jira-ready tickets.
Not required. But if server logs are available, they allow more accurate analysis of crawl behavior, discoverability, and search bot activity.
It depends on project scale, data availability, and architectural complexity. On average, the process takes from a few weeks to one month.