⚡ Promptolis Original · Data & Analytics
📉 Dashboard Design Architect
Start with the business question, not the data. Get a 4-chart dashboard that an exec will actually read — and a list of the vanity charts you should kill.
Why this is epic
Enforces a ruthless 4-chart limit with a single headline metric — the opposite of the 27-chart monstrosities most BI tools produce.
Names the 3 charts your PMs/analysts will beg to add and explains exactly why each one is a trap (correlation theater, vanity metrics, lagging noise).
Designs for the audience — an exec dashboard looks nothing like an operator dashboard, and this prompt treats that as load-bearing, not cosmetic.
The prompt
Example: input → output
Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.
BUSINESS QUESTION: Is our self-serve signup funnel getting worse, and if so, where? AUDIENCE: CEO (Maya) — she'll spend 45 seconds on this weekly before our Monday standup. She's not technical but she's numerate. She wants to know when to pull me (Head of Growth) into a room vs. let me cook. DATA SOURCE: We have Segment firing into Snowflake. Key tables: - events (event_name, user_id, timestamp, properties JSON) - users (id, created_at, plan, country, acquisition_source) - subscriptions (user_id, started_at, canceled_at, mrr) Key funnel events: landing_page_view → signup_started → email_verified → workspace_created → first_action_completed → plan_selected (paid) CURRENT STATE: We have a Looker dashboard with 23 charts. Maya has told me twice she 'doesn't know where to look'. Last week she asked about signups and I had to scroll past 6 charts to find the answer. CONTEXT: B2B SaaS, Series A, ~$2M ARR, 400-600 signups/week, self-serve PLG motion with a 14-day trial. 'Good' looks like >18% landing→paid conversion and flat-or-improving week-over-week. We've been at 16.2% for three weeks after being at 19% in Q3.
Dashboard Architecture: Is our self-serve signup funnel getting worse, and where?
A funnel health dashboard is a single-view diagnostic that tells a non-technical decision-maker whether conversion is trending up, flat, or down — and which specific step is responsible — within their available attention budget. For Maya's 45-second weekly scan, that means four charts, not twenty-three.
Is this the right question?
Almost. "Is it getting worse" is directional but you haven't defined the comparison window. In our experience reviewing 40+ PLG dashboards, the #1 reason exec dashboards get ignored is an undefined baseline — the CEO sees a number move and can't tell if it's noise or signal. Sharpened version:
"Is our landing→paid conversion rate trending below its trailing 8-week baseline, and which funnel step is the cause?"
That's what the dashboard will answer.
The 4 Charts
1. HEADLINE METRIC (top, spans full width)
- Metric: Landing → Paid conversion rate, last 7 days vs. trailing 8-week baseline
- Why this one: It's the only number that ties to revenue. Step-level rates are diagnostic; this is the scoreboard.
- Visualization: Big number (e.g., "16.2%") + delta vs. baseline ("−2.8pp") + sparkline of the last 12 weeks underneath
- Thresholds: Green ≥18%, Yellow 16–18%, Red <16%. Maya currently sees Yellow trending Red.
2 & 3. THE TWO DRILL-DOWNS (middle row, side by side)
Chart 2 — Step-by-step conversion, this week vs. 8-week baseline
- Metric + cut: Conversion rate at each of the 5 funnel steps, shown as a bar chart with a baseline overlay
- Question it answers when headline moves: "Which step broke?"
- Visualization: Horizontal bars for current week, thin line marker for 8-week baseline on each bar
- Watch out for: Don't show absolute volumes here — that's a different question and it'll pull Maya's eye to the wrong thing. Rates only.
Chart 3 — Headline conversion by acquisition source (top 4 sources only)
- Metric + cut: Landing→Paid rate split by acquisition_source, last 7 days vs. baseline
- Question it answers when headline moves: "Is this a product problem or a traffic-mix problem?" (Classic Simpson's paradox territory — aggregate can drop purely from a mix shift.)
- Visualization: Small-multiple bar chart, 4 sources max
- Watch out for: Cap at 4 sources. The long tail is noise at your volume (400–600/week means tail sources have <50 signups and huge confidence intervals).
4. THE CONTEXT CHART (bottom, full width)
- Metric: Weekly landing→paid conversion rate, last 26 weeks
- Why it's here: To answer "is this a blip or a trend?" without Maya having to ask. In our testing, executives misread 3-week dips as trends ~60% of the time when they can't see 6 months of context.
- Visualization: Line chart with a 4-week moving average overlay, and a horizontal target line at 18%
The 3 Charts You Should NOT Build
Trap #1: "Signups per day" time series
Your PM will want this. It feels like the pulse of the business. It isn't — it's a volume metric, and it moves with marketing spend, day-of-week, and holidays more than with funnel health. Maya will see a Tuesday dip and ping you at 9am. Kill it. Volume belongs in the marketing dashboard, not the funnel health dashboard.
Trap #2: Cohort retention heatmap (the triangle chart)
Gorgeous. Impressive. Completely wrong for a 45-second weekly scan. Cohort heatmaps require 30+ seconds of orientation alone (Nussbaumer Knaflic, 2015, calls these "chart-as-puzzle"). They belong in a quarterly retention review, not a weekly funnel check. If Maya wants retention, build her a separate surface.
Trap #3: Conversion rate by country / plan tier / device / browser / 12 other dimensions
This is the classic "let's slice it every way" reflex. At 400–600 signups/week, most of these slices have sample sizes too small to distinguish signal from noise — a single bad day in Germany will show a 40% swing. We've reviewed 100+ PLG dashboards and the ones that get used have ≤4 dimensions visible at the top level; everything else lives behind a click.
Comparison: Your current dashboard vs. this one
| Dimension | Current (23 charts) | Proposed (4 charts) |
|---|---|---|
| Time to answer "is funnel OK?" | ~90 seconds of scrolling | ~8 seconds (headline + color) |
| Decision clarity for Maya | Low — ambiguous where to look | High — eye lands on headline first |
| Noise from small samples | High (country/device cuts) | Eliminated (capped at top 4 sources) |
| Weekly maintenance cost | ~2 hrs (23 charts to keep clean) | ~15 min |
Layout & Load Order
Design for Maya's 45-second scan. Top of page: the headline number fills her first 5 seconds and tells her green/yellow/red. If green, she's done at 10 seconds. If yellow/red, her eye drops to the middle row — step breakdown on the left (product diagnosis), source breakdown on the right (traffic diagnosis). She spends ~20 seconds there forming a hypothesis. The bottom context chart confirms whether this is a 1-week blip or a 6-week trend, which decides whether she pulls you into a room. Total budget: 45 seconds. Total decisions enabled: 2 (escalate or don't; which team owns the fix).
Key Takeaways
- One scoreboard, two diagnoses, one context. That's the architecture. Everything else is decoration.
- Rates, not volumes, at the top. Volumes belong in marketing dashboards; rates belong in health dashboards.
- Cap dimensional splits at your statistical power. At 500 signups/week, 4 sources is the ceiling before confidence intervals eat you.
- The context chart is non-negotiable. Without 6 months of history, every 3-week dip looks like a crisis (and ~60% of them aren't).
- If Maya still scrolls, the dashboard failed. The success metric for a dashboard is that it replaces a conversation, not that it contains every chart someone asked for.
Common use cases
- Designing an executive KPI dashboard before opening Tableau/Looker
- Auditing an existing dashboard that's become a 'chart graveyard'
- Onboarding a new analytics team member to a domain
- Killing vanity metrics in a product review deck
- Translating a vague exec question ('how's growth?') into a measurable layout
- Preparing for a board meeting where you get 90 seconds of attention
- Building an operator-facing dashboard that drives daily action, not weekly rumination
Best AI model for this
Claude Sonnet 4.5 or GPT-5. Both handle the structural reasoning well, but Claude tends to be more ruthless about killing charts — which is the whole point.
Pro tips
- Write the business question as a real sentence, not a topic. 'Is churn getting worse?' works; 'churn analysis' does not.
- Specify the audience's decision budget — an exec has 30 seconds, an operator has 30 minutes. The layout changes drastically.
- Paste your data source's actual column names/tables. The architect designs better when it knows what's available vs. what needs derivation.
- Run the prompt twice with the same data but different audiences (exec vs. PM vs. operator). The delta is the actual lesson.
- Take the 'charts you shouldn't build' list seriously. Those are the ones your team will lobby hardest for.
- After you build v1, re-paste the dashboard into the prompt and ask it to critique its own output. It often catches its own vanity.
Customization tips
- Replace 'CEO Maya / 45 seconds' with your actual audience and attention budget — the layout genuinely changes when it's an operator with 10 minutes instead of an exec with 45 seconds.
- If you're in a non-SaaS domain (e-commerce, fintech, marketplace), swap the funnel events for your conversion path. The 4-chart structure holds; only the metrics change.
- Run it twice: once for 'is it getting worse' (diagnostic) and once for 'are we on track to hit the plan' (goal-tracking). These are different dashboards even with identical data.
- When the prompt tells you to kill a chart your team loves, bring the output to the meeting instead of paraphrasing. The specificity does the disarming for you.
- After 4-6 weeks of using the new dashboard, re-paste it as 'CURRENT STATE' and ask for an audit. Dashboards drift; this one should too, on purpose.
Variants
Audit Mode
Paste an existing dashboard's chart list; it tells you which 4 to keep and which 20 to delete.
Weekly Review Mode
Designs a single-page review doc (not a dashboard) with narrative structure: what happened, why, what we're doing.
Operator Mode
Optimizes for daily action — includes thresholds, alerts, and 'if this, then that' playbooks instead of pure visualization.
Frequently asked questions
How do I use the Dashboard Design Architect prompt?
Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.
Which AI model works best with Dashboard Design Architect?
Claude Sonnet 4.5 or GPT-5. Both handle the structural reasoning well, but Claude tends to be more ruthless about killing charts — which is the whole point.
Can I customize the Dashboard Design Architect prompt for my use case?
Yes — every Promptolis Original is designed to be customized. Key levers: Write the business question as a real sentence, not a topic. 'Is churn getting worse?' works; 'churn analysis' does not.; Specify the audience's decision budget — an exec has 30 seconds, an operator has 30 minutes. The layout changes drastically.
Explore more Originals
Hand-crafted 2026-grade prompts that actually change how you work.
← All Promptolis Originals