Market Intelligence
at Scale
From 189 investor websites to company-specific sales intelligence — in six weeks.
- MY ROLE
- Project initiator & lead
- SCOPE
- Nasdaq Helsinki
- METHOD
- AI-assisted research
- OUTPUT
- Sales tools & pipeline
What can we say to this company tomorrow?
IDX sells investor-relations websites and digital IR tools. Its sales team needed a reliable view of which providers companies used, where their investor websites fell short, and which concrete improvement to discuss with each prospect.
Manual reviews could answer these questions one company at a time. They could not efficiently provide a consistent picture of the entire Helsinki market.
Map the market. Find the gaps. Equip sales.
Map: identify IR-tool providers and capture supporting evidence across 189 websites.
Assess: screen sites and conduct deeper checks of AI readability, accessibility, search basics and machine-readable data.
Activate: build a searchable lookup, 19 fair handouts and a 16-prospect outreach pilot.
Synthesise: identify common patterns and prepare an IR Iceberg narrative and baseline study.
Research that a salesperson can actually use.
The IR Tools Lookup turned the research into a searchable interface. Select a company to generate a concise client-facing report, or switch to an internal view with competitive intelligence, sales notes and evidence. Reports can be printed as PDFs.
The lookup changed the sales-preparation workflow from manually reviewing a site to retrieving prepared, company-specific findings in roughly a minute. That is a workflow estimate, not a controlled time study.
Having the pages isn't the same as being readable.
Across the market, the research found that most IR sites had the expected content sections, but machine-readable access was much less consistent. About one-third of sites had release pages that were difficult for AI crawlers to read; around four in five lacked structured company data.
The analysis also found little relationship between the number of IR page types and technical quality (correlation 0.16). The resulting sales proposition shifted from visual redesign to specific, measurable problems in digital investor communications.
These findings describe the project's October–November 2026 automated assessment, not an independently verified industry benchmark.
AI did the processing. I owned the decisions.
I initiated and led the project, defined the commercial questions, secured compliance approval for read-only automated crawling, challenged classifications, incorporated sales-team knowledge and shaped the customer-facing language.
Claude supported crawling, measurement, workbook production, interface development and draft copy. I directed the work, corrected results and decided which findings were reliable enough to use.
One important correction involved reclassifying 72 sites after provider widgets were initially over-counted. That human review improved the defensibility of the market picture.
From research to conversations.
The project delivered a shared competitive view, a ranked prospect list, existing-client upgrade opportunities and repeatable, company-specific meeting material. Conversion results from outreach and fair activity were still pending at this November 2026 snapshot.