Turn AI Search
into measurable KPIs
Measure brand visibility across AI search platforms and execute optimization strategies in one unified system.
Trusted by major companies
No.1 AI Search Optimization Solution
Own your brand visibility in AI answers with Chainshift.
We analyzes visibility across 7 LLMs and helps you optimize content and validate results—all in one platform.
User feedback
The AI search solution Chainshift selected by enterprises and marketing experts.
Frequently Asked Questions
Who needs Chainshift?
It is necessary for all companies interested in brand exposure and reputation on AI search engines.
In particular, it is effective for B2C companies, services where online recognition is important, and brands in fiercely competitive industries.
How is it different from existing SEO tools?
Existing SEO tools focus on the technical aspects of websites, but Chainshift analyzes the 'answers' generated by AI itself.
It provides insights from the perspective of AEO (Answer Engine Optimization) by tracking how brands are perceived by AI and in what contexts they are mentioned.
What are the introduction costs?
Chainshift is a subscription-based SaaS model.
We offer various pricing plans according to the number of keywords and questions tracked and the scope of analysis.
For more details, please inquire together when applying for the 'Brand Diagnosis'.
How often is the data updated?
The core data is collected and analyzed in real-time, and you can check the latest information on the dashboard.
Long-term trend analysis is also possible through weekly/monthly reports.
Can AI search exposure be defined by KPI?
Yes. Chainshift is defined not as mere exposure but as a manageable index.
AI search performance is structured into measurable KPIs such as ▲Visibility % ▲Citation % ▲ROI. This is a brand influence index, not just simple traffic, which can be set and tracked as a quarterly KPI.
Does that indicator relate to actual sales?
AI search is not simply a channel to increase top visibility.
It operates at the stage where users with a purchasing intent are asking specific questions.
Therefore, Chainshift analyzes not just simple exposure metrics, but how much brands are chosen at the point where actual demand occurs.
The key indicators are as follows:
When AI exposure increases, how does the actual brand search volume change?
When citations increase in AI, does the flow to the conversion page increase?
How does the share compare to competitors for the same question group?
In other words, it’s not just about “being visible,”
but rather a structure that looks at “whether our brand is being chosen for questions with purchasing intent.”
Additionally, when our own homepage or content (Owned Media) is optimized for AI search, it supports the analysis of the flow linking AI exposure → website influx → conversions, enabling us to confirm correlations with actual sales.
Chainshift is not a solution that merely views exposure, but rather a solution that assesses share and revenue connection potential at the point of capturing demand.
Can it be operated along with the existing marketing campaign?
It is possible.
AI search reflects the results of existing SEO, content, and PR campaigns.
Chainshift analyzes AI visibility together with existing campaign data to clarify the role of AI within the marketing MIX.
AI search is not a new channel, but a point where the results of existing channels are aggregated.
Can we measure whether the existing marketing performance affects AI search?
Yes. We compare and analyze how AI citations and exposure structures change after content publication, PR dissemination, and brand campaigns.
Through this, we can quantitatively verify whether "our existing activities are reflected in AI responses."
How is AI search structurally measured?
Chainshift independently develops an engine that structurally measures AI search data in an environment where actual users interact with LLM chatbots, rather than through simple API calls.
Fanout-based Question Expansion Analysis
AI collects expanded sets of questions that are actually utilizedPlatform-specific Source Analysis
Comparison by platform such as ChatGPT, Gemini, Perplexity, etc.Emotion and Risk Scoring
Quantifying the context of brand mentions
Through this process, AI search is measured not as qualitative but as quantitative data.
Is it a simple report, or is it linked to execution?
It will be connected until execution.
ChainShift suggests specific action items for each analysis result.
For example:
Low citation channel → Content distribution proposal
Increased emotional risk → Supplementary content design
Competitor SOV surge → Recommended response campaign
It provides not just a simple report but a variety of actions related to operational guidance and AI search optimization within the solution.
Can the results be re-evaluated after execution?
Yes, we compare the changes in visibility and citation before and after execution.
With the Chainshift solution, you can track performance by question set and conduct repeated experiments,
and with AI search, instead of a one-time campaign, if you use the Chainshift solution for continuous management, you can measure daily performance in real-time.
Diagnose your AI search results.
We will examine the visibility of our brand, citation structure, and market share compared to competitors in AI search, and suggest actionable improvement directions.
Email Us
daniel@chainshift.co
Call Us
+82 10-4155-9264
Contact Us
2nd Floor, 217 Teheran-ro, Gangnam-gu, Seoul