Intelligence
Creative work without measurement is opinion. Everything we ship comes with the reporting to judge it — this page shows the systems we build and the frameworks we run. All figures below are illustrative scenarios.
One screen a CEO reviews monthly: where demand comes from, whether it converts, and what changed. Illustrative 12-month scenario.
Qualified pipeline
$1.84M
+38% YoY
Organic demand
42.6K
+61% YoY
Conversion rate
3.4%
+0.8 pt
AI search visibility
27%
+11 pt
Jul — Site rebuild ships — July dip is seasonal, recovery is structural
Qualified demand rises from 100 in January to 186 in December — an 86-point gain — with a single seasonal dip in July.
| Period | index |
|---|---|
| Jan | 100 |
| Feb | 104 |
| Mar | 111 |
| Apr | 118 |
| May | 124 |
| Jun | 133 |
| Jul | 129 |
| Aug | 141 |
| Sep | 152 |
| Oct | 160 |
| Nov | 171 |
| Dec | 186 |
Organic search and AI answers together contribute 57% of pipeline; email 17%, paid 19%, referral and direct 7%.
| Channel | Share % |
|---|---|
| Organic search | 44 |
| AI answers / GEO | 13 |
| Email lifecycle | 17 |
| Paid campaigns | 19 |
| Referral & direct | 7 |
Executive insight — Qualified demand up 86 points on the year. Organic and AI answers now carry 57% of pipeline — paid spend can shift from prospecting to retargeting without losing volume.
Is the product earning its users — activation, retention, task completion, support friction? Illustrative 12-week product scenario.
Activation rate
38%
+6 pt
Week-4 retention
44%
+9 pt
Core-task completion
71%
+12 pt
Support tickets per 100 users
4.2
−31%
W5 — Onboarding redesign ships — brief dip as returning users adjust, then the lift resumes
Weekly active users rise from 100 in W1 to 155 in W12 — a net move of 55 points over the period. Marked point: W5 — Onboarding redesign ships — brief dip as returning users adjust, then the lift resumes.
| Period | index |
|---|---|
| W1 | 100 |
| W2 | 104 |
| W3 | 109 |
| W4 | 115 |
| W5 | 112 |
| W6 | 119 |
| W7 | 125 |
| W8 | 131 |
| W9 | 137 |
| W10 | 143 |
| W11 | 149 |
| W12 | 155 |
Bars show funnel reach, not a partition of 100%: Completed onboarding reaches 68% of users, narrowing to 33% at Weekly habit — the drop between stages is where activation work pays back.
| Channel | Share % |
|---|---|
| Completed onboarding | 68 |
| First core action | 51 |
| Returned in week 2 | 44 |
| Weekly habit | 33 |
Product insight — The onboarding redesign cut the biggest drop-off in the funnel and week-4 retention followed; the next leverage is the week-2 return, where a third of activated users still slip away.
Where does revenue come from — and what does it cost to earn? Illustrative 12-month commerce scenario.
Revenue
$412K
+24% YoY
Average order value
$86
+9%
Conversion rate
2.9%
+0.6 pt
Returning customers
31%
+5 pt
Jul — Checkout rebuild ships — conversion steadies and returning-customer share starts climbing
Revenue rises from 100 in Jan to 165 in Dec — a net move of 65 points over the period. Marked point: Jul — Checkout rebuild ships — conversion steadies and returning-customer share starts climbing.
| Period | index |
|---|---|
| Jan | 100 |
| Feb | 102 |
| Mar | 106 |
| Apr | 110 |
| May | 115 |
| Jun | 120 |
| Jul | 124 |
| Aug | 128 |
| Sep | 133 |
| Oct | 140 |
| Nov | 152 |
| Dec | 165 |
Organic search leads at 31%, followed by Paid campaigns at 27%; channel shares sum to 100% of the total.
| Channel | Share % |
|---|---|
| Organic search | 31 |
| Paid campaigns | 27 |
| Email-attributed | 22 |
| Direct & referral | 20 |
Commerce insight — Email lifecycle now carries nearly a quarter of revenue, so paid spend can prospect less and retarget more without losing volume.
Which campaigns create qualified demand — not just reach? Illustrative two-quarter campaign scenario.
Qualified traffic
28.4K
+19%
Visitor→lead progression
6.1%
+1.4 pt
Email-attributed pipeline
24%
+7 pt
Assisted conversions
1,180
+33%
Apr — Video series launches — qualified traffic inflects, and email starts compounding it
Qualified demand rises from 100 in Jan to 156 in Jun — a net move of 56 points over the period. Marked point: Apr — Video series launches — qualified traffic inflects, and email starts compounding it.
| Period | index |
|---|---|
| Jan | 100 |
| Feb | 108 |
| Mar | 119 |
| Apr | 127 |
| May | 141 |
| Jun | 156 |
Organic & content leads at 34%, followed by Email lifecycle at 24%; channel shares sum to 100% of the total.
| Channel | Share % |
|---|---|
| Organic & content | 34 |
| Email lifecycle | 24 |
| Paid social | 18 |
| Paid search | 14 |
| Video & referral | 10 |
Campaign insight — Reach and impressions are deliberately absent here: qualified progression is the measure, and organic plus email now create 58% of it.
The model behind every engagement: each stage hands measurable value to the next. Weakness anywhere in the chain shows up as cost everywhere after it.
The framework we run during discovery — illustrative scores shown. Each dimension is scored 0–5; the gap between bars is the roadmap.
In this scenario, AI discoverability and automation maturity score lowest at 1 of 5 — the two highest-leverage improvements. Brand consistency and search visibility are strongest at 4 of 5.
| Dimension | Score (of 5) |
|---|---|
| Brand consistency | 4 |
| UX clarity | 3 |
| Accessibility | 2 |
| Mobile performance | 2 |
| Conversion readiness | 3 |
| Search visibility | 4 |
| AI discoverability | 1 |
| Analytics maturity | 3 |
| Automation maturity | 1 |
Each stage of a customer journey is carried by a different part of the practice — and measured at the handoff.
Discovery
Brand, content, SEO & GEO
Evaluation
UX, product design, proof
Conversion
Performance, CRO, forms
Onboarding
Automation, internal tools
Retention
Lifecycle email, reporting
The architecture we build for retrieval-augmented generation — the same structure behind the AI knowledge workspace concept.
Data sources
Docs, CRM, tickets, wikis
Ingestion
Sync, clean, dedupe
Processing
Chunking & metadata
Embeddings
Versioned models
Vector database
Filtered retrieval
Retrieval
Hybrid + rerank
LLM orchestration
Prompts, tools, guards
Application layer
Cited answers, APIs
Evaluation
Quality & drift monitoring
Before
After
"I always know what you're working on" isn't an accident — it's this document, every week. A sample:
Website rebuild & search program
Build — week 6 of 10
When buyers ask ChatGPT or Google AI about your category, do you appear?
Request an assessment →Where does your site lose people who intended to buy?
Request an assessment →Which manual processes cost you the most hours — and which are safely automatable?
Request an assessment →Across brand, product, search, and analytics — where are you strong, and what is the one highest-leverage fix?
Request an assessment →How does your brand, product, search, and analytics maturity compare to your category?
Request an assessment →Is your brand clarity actually converting into pipeline — or leaking between stages?
Request an assessment →Where does your product lose users between sign-up and habit?
Request an assessment →Which of acquisition, conversion, AOV, and retention is actually capping your revenue?
Request an assessment →