The Two Signal Types
Field Sentiment
What practitioners are saying publicly about a category — captured from LinkedIn, Reddit, conference talks, newsletters, articles, and surveys on a rolling 90-day window.
Financial Signal
Where money is actually moving — sourced from analyst reports, financial disclosures, funding announcements, and procurement data, tiered by source reliability.
Field Sentiment
Field sentiment captures what practitioners — the people actually building, buying, and deploying AI products — are saying in public channels. The sources include:- LinkedIn posts and comment threads
- Reddit discussions (relevant subreddits and community forums)
- Conference talks and published session summaries
- Industry newsletters and practitioner-authored articles
- Surveys with disclosed methodology and sample sizes
Financial Signal
Financial signal tracks where capital and procurement spend are actually moving in a given AI category. Sources are organized into three tiers by reliability:Tier 1 — Primary financial disclosures
Tier 1 — Primary financial disclosures
The highest-reliability sources. These include SEC filings, publicly disclosed ARR figures, and announced funding rounds. Tier 1 sources reflect actual committed capital or disclosed revenue — not projections or estimates.
Tier 2 — Analyst reports and market research
Tier 2 — Analyst reports and market research
Institutional research from analysts including Grand View Research, Mordor Intelligence, MarketsandMarkets, Menlo Ventures, and comparable firms. Tier 2 sources involve estimation methodology, so they’re weighted below Tier 1 but still treated as defensible signal.
Tier 3 — Procurement surveys and secondary sources
Tier 3 — Procurement surveys and secondary sources
Survey-based procurement data and secondary financial sources. Tier 3 is used for context and directional support but doesn’t satisfy the minimum sourcing threshold on its own.
Sentiment Clusters
Field sentiment statements aren’t just counted — they’re categorized. Every practitioner statement collected for a frame is classified into one of three sentiment clusters:- Enthusiastic — The practitioner expresses clear positive signal: adoption, recommendation, observed ROI, active deployment
- Cautious — The practitioner engages with the category but hedges: conditional adoption, unresolved concerns, wait-and-see positioning
- Skeptical — The practitioner expresses doubt: failed deployments, overhype claims, reluctance to invest
The 90-Day Rolling Window
The 90-day window is intentional. It makes the map a current-conditions instrument, not a historical archive. This means a few things in practice:- A frame’s direction can shift between versions as new statements enter the window and older ones age out
- Sentiment that was enthusiastic six months ago doesn’t carry forward if practitioners have gone quiet or turned cautious
- Emerging categories can move from Insufficient Signal to a directional call quickly if practitioner conversation spikes
How Signal Becomes a Direction
The directional call for each frame — Concordant, Money Ahead, Mouth Ahead, or Insufficient Signal — is computed from the relationship between the two signal types. It isn’t generated by a model or written editorially. The directional call itself reflects whether financial investment and practitioner sentiment are aligned, diverging, or absent. The CosentriQ team performs a quality review before each version is published to ensure every frame that reaches you is defensible.1
Signals are collected and processed
Field sentiment statements are collected, filtered for relevance, and classified into sentiment clusters. Financial sources are identified, tiered, and verified against minimum thresholds.
2
Thresholds are checked
Each frame must meet minimum signal thresholds before a direction can be computed. Frames that don’t meet thresholds are flagged for Insufficient Signal status.
3
Direction is computed
The relationship between financial signal strength and field sentiment distribution determines the directional call. Aligned signals produce Concordant; diverging signals produce Money Ahead or Mouth Ahead depending on which type leads.
4
Frames pass a quality review before publishing
The CosentriQ team reviews all computed frames before a version is published to verify that each directional call is defensible and the signal is sound. No frame reaches the live map without passing this review.
Coverage: Subpatterns and Industries
The map currently covers five AI agent subpatterns across major industries. Subpatterns:
Industries currently in coverage:
Financial services, healthcare, legal, software and SaaS, retail and CPG, manufacturing, customer support and BPO, media and content, and government and education. Coverage expands with each map version as signal thresholds are met in new industry and subpattern combinations.
Frames with insufficient signal are excluded from the published map. If your target category and industry combination doesn’t appear as a frame, it means the CosentriQ team didn’t have enough defensible signal to publish a directional call — not that the market doesn’t exist. Check back after the next version refresh, or contact the CosentriQ team if you need intelligence on a specific combination.