Accountability

How We'll Know It's Working

Every metric is measurable, time-bound, and directly traceable to the visibility deficit identified in this assessment.

Primary KPIs

LLM visibility metrics

These are the direct measures of how AI systems represent JE Dunn to buyers. Quarterly measurement via repeat simulation.

Metric Current Target (12mo) How We Measure
Confidentiality Friction Rate 57.6% <25% % of LLM responses citing "confidential client" language
Hedging Language Rate 37.3% <15% % of responses with equivocating qualifiers
Turner Unprompted Mention Rate 25.7% <15% % of JE Dunn queries that surface Turner first
Clean Positive Recommendation 3% >20% % of responses recommending JE Dunn without caveats
Third-Party Source Count 8 15+ Unique domains citing JE Dunn semiconductor work
First-Party Source Dependence 36.1% <20% % of LLM citations pointing to jedunn.com
How we measure: Re-run the 700-question simulation quarterly using the same personas and methodology. This creates a directly comparable dataset showing exactly how the AI information layer is shifting.
Leading Indicators

Market visibility metrics

These leading indicators predict LLM visibility improvements before they appear in AI training data refreshes.

Top 5
Google Search Position
For "semiconductor construction" and related terms
3+/qtr
Trade Media Features
Construction Dive, ENR, Cleanroom Technology
2+/yr
SEMI/iMasons Presence
Conference presentations or published content
Named
Client References
3–5 semiconductor clients with public permission

Content Pipeline Targets

Monthly: 4+ LinkedIn posts, 1 technical blog post, 1 project case study. Quarterly: 1 white paper on SEMI or Cleanroom Technology platform, 1 wire service distribution, 1 executive byline in trade media. These are the inputs that drive LLM training data improvements.

Digital Infrastructure Targets

Month 1: Schema markup implemented. Month 2: Wikipedia entry developed. Month 3: Semiconductor landing page restructured. Month 6: All project pages updated with technical specifications. These structural improvements make all content work harder.

Outcomes

Business impact metrics

The ultimate proof — these are the business outcomes that visibility improvements should drive within 12 months.

Pipeline

Inbound RFQ Increase

Measurable increase in unsolicited semiconductor RFQ volume — the clearest signal that JE Dunn is appearing in more buyer research processes. Baseline established from current 12-month trailing data.

Positioning

Reduced Turner Pushback

Fewer procurement conversations where Turner is presented as the benchmark by the buyer. Currently, 19.1% of LLM responses frame Turner as the standard. Qualitative tracking through BD team debriefs.

Win Rate

Higher Semiconductor Win Rate

When JE Dunn is shortlisted, improved AI visibility should translate to faster conviction and fewer "need more references" delays. Track semiconductor-specific win rate against company average.

The accountability model: Spotlight reports against all three metric tiers quarterly — LLM visibility (direct simulation), market visibility (leading indicators), and business impact (outcome tracking). Every dollar invested is traceable to measurable movement.

The Data Is Clear. The Plan Is Ready.

57.6% confidentiality friction. 3% clean recommendation rate. $1B+ in annual revenue at risk. The visibility deficit is measurable — and so is the fix. Let's find 90 minutes to walk through the full strategy.

Find 90 Minutes to Discuss

Rick Nash, CEO  ·  rick.nash@spotlightar.com

The Fix