Study Guide: Alex for Visual Storytellers
Your reference for using Alex to design, interpret, and communicate data visuals. Ready-to-run prompts for Power BI, Copilot, customer charts, and leadership narratives.
What This Guide Is Not
This is not a habit formation guide (see Self-Study Guide for that). This is a visual storytelling toolkit — the specific ways Alex can sharpen your charts, narratives, and leadership presentations before you open Power BI or build a single slide.
Core Principle for Visual Storytellers
The art of persuasion through visuals is centuries old. From Nightingale’s polar area diagrams to Minard’s Napoleon map, the greatest data visualizations were not the most technically complex — they were the most clearly reasoned. The chart was always secondary to the argument it made.
That principle holds today. Power BI is a tool. Copilot is a tool. The logic, the structure, the story — those are yours to design. Alex helps you design them.
The key pattern: bring the question your leadership needs answered, not just the data you have. The gap between “here’s a chart” and “here’s what you should do about it” is where Alex adds the most value.
The Seven Use Cases
1. Visual Design Principles and Chart Selection
When to use: Deciding which chart type to use, diagnosing why a chart isn’t working, or designing a visual from scratch.
Prompt pattern:
Help me select the right visualization:
What I'm trying to show: [comparison / distribution / trend / relationship / part-to-whole / geographic]
Audience: [executives / analysts / customers / board]
Data shape: [what variables, how many categories, time dimension?]
Risk I'm sensing: [too busy / too simple / misleading / unclear]
Help me:
1. Identify the right chart type for this message
2. Diagnose what's wrong with my current visual
3. Apply the principle of "one chart = one message"
4. Remove chart junk that isn't earning its visual weight
5. Rank the visual hierarchy so eyes land on what matters
Follow-up prompts:
I have 6 KPIs I want to show on one page. How do I prioritize them visually?
My stakeholder says this chart is "confusing." What are the 5 most common reasons a chart confuses people?
Should this be a bar chart, a line chart, or a scatter plot? Here's what I'm trying to argue: [paste argument]
2. Building the Leadership Narrative
When to use: Turning analysis into an executive recommendation. Moving from “what happened” to “what you should do.”
Prompt pattern:
Help me structure a leadership narrative around this data:
Situation: [what's happening in the business]
Metrics: [the key numbers — paste or describe]
Audience: [C-suite / VP / board / customer leadership]
Decision: [what we need them to decide or approve]
Time available: [how long to present]
Structure my narrative using:
1. The SCR framework (Situation → Complication → Resolution)
2. The single "so what" they must remember
3. The 3 supporting visuals that prove the point
4. The preemptive answer to "why should I believe this?"
5. The explicit recommendation and its tradeoffs
Follow-up prompts:
The data tells a mixed story. How do I present it honestly without losing the room?
I have 40 slides. Help me cut to 8 without losing credibility.
Write the opening 60 seconds of this presentation.
3. Power BI Design and Layout Strategy
When to use: Planning a Power BI report — page layout, visual selection, interaction design, color strategy.
Prompt pattern:
Help me design this Power BI report:
Report purpose: [operational monitoring / executive summary / customer-facing / deep-dive analysis]
Audience: [who will use it and how often]
Key questions: [the 3-5 questions this report must answer]
Data available: [tables and measures I have access to]
Interaction needed: [drill-through / cross-filter / slicers / bookmarks]
Help me:
1. Define the page hierarchy (overview → detail)
2. Select which visuals belong on which page
3. Design the color and typography system
4. Plan the slicer and filter strategy
5. Identify what NOT to put on the dashboard
Follow-up prompts:
My report has too many visuals. Apply the "ruthless edit" — what should go?
What's the right way to show target vs. actual in Power BI?
Design the executive summary page for a sales performance report.
4. Copilot-Assisted Analysis and Annotation
When to use: Using Microsoft Copilot inside Power BI, Excel, or Teams to accelerate analysis and generate narrative summaries.
Prompt pattern:
Help me write effective Copilot prompts for this analysis:
Tool: [Power BI Copilot / Excel Copilot / Copilot in Teams]
Data context: [what dataset or report you're working with]
What I need: [summarize / find anomalies / compare / forecast / draft narrative]
Output format: [chart annotation / executive summary / slide bullets / email]
Write Copilot prompts that:
1. Are specific enough to get useful output
2. Include the frame ("for an executive audience")
3. Ask for confidence-qualified language where uncertainty exists
4. Produce output I can verify before using
5. Chain into a narrative flow
Follow-up prompts:
How do I prompt Copilot to write a data story summary, not just a stat dump?
Write a Copilot prompt that finds outliers and explains them in plain language.
I got a Copilot summary but it's generic. How do I prompt for more specific insight?
5. Customer-Facing Visualizations
When to use: Designing charts and visual reports that go directly to customers — QBRs, account reviews, ROI reports, dashboards.
Prompt pattern:
Help me design a customer-facing visualization:
Customer type: [enterprise / SMB / consumer / partner]
Purpose: [QBR / ROI demonstration / health dashboard / account review]
What the customer cares about: [their KPIs and success metrics]
What I want them to feel: [confidence / urgency / gratitude / partnership]
Sensitive context: [any metrics that might look bad or need framing]
Help me:
1. Lead with their metrics, not mine
2. Frame the "red" numbers without losing trust
3. Design visuals that build relationship, not just report performance
4. Balance transparency with optimism
5. Structure the narrative so it ends with forward momentum
Follow-up prompts:
The customer's numbers are down. How do I present this honestly while keeping the relationship?
Design the QBR data story structure for a strategic account.
Write the annotation text for a customer health scorecard.
6. Persuasion Design and Rhetorical Strategy
When to use: High-stakes presentations where you need to move people — budget approvals, strategy pivots, executive alignment.
Prompt pattern:
Help me design a persuasion strategy for this presentation:
What I need them to do: [approve / fund / change / prioritize]
Their likely objections: [what will push back]
Their decision-making style: [data-driven / instinct-driven / risk-averse / skeptical]
What data I have that's compelling: [your strongest evidence]
What I don't have: [gaps in the evidence]
Design a persuasion architecture that:
1. Leads with what they already believe (agreement before challenge)
2. Uses the strongest visual as the anchor
3. Names the objection before they do
4. Quantifies the cost of inaction
5. Ends with a clear, easy-to-say-yes-to ask
Follow-up prompts:
My CFO is a skeptic. How do I design this for the "show me the math" audience?
What's the visual equivalent of a thesis statement?
I have one chart that proves my point. How do I build the entire narrative around it?
7. Presentation Audit and Visual Critique
When to use: Reviewing a deck or dashboard before it goes to leadership. Stress-testing the visual logic.
Prompt pattern:
Audit this presentation for visual storytelling effectiveness:
Presentation type: [executive deck / dashboard / customer report]
Context: [what decision or outcome this is meant to drive]
Current state: [describe the charts, their sequence, and the narrative if any]
Audit against:
1. One message per visual — does each chart earn its place?
2. Visual hierarchy — where does the eye go first on each page?
3. Data-ink ratio — what can be removed without losing meaning?
4. Narrative coherence — does the sequence tell a story or just display data?
5. The "so what" test — after every chart, can a viewer state the implication?
Return a prioritized list of changes.
Follow-up prompts:
Apply Tufte's data-ink ratio principle to this chart layout: [describe it]
Which of these 8 slides is doing the least work? How do I fix or cut it?
Pretend you're a skeptical CFO seeing this for the first time. What questions do you have?
Design Principles Worth Memorizing
Gestalt principles at work in every chart:
- Proximity — group related data
- Similarity — use consistent encoding (same color = same category, always)
- Continuity — the eye follows paths; design where it travels
- Figure/ground — your insight is the figure; everything else is ground
The data-ink ratio (Tufte): Every drop of ink must earn its place. If removing it makes the chart clearer, remove it.
The preattentive principle: Color, size, and position are processed before conscious thought. Use this intentionally — not decoratively.
One chart = one argument. If you can’t state the argument in 10 words, the chart isn’t done yet.
Practice Progression
Week 1: Describe your current most-used chart to Alex and ask it to critique it against visual design principles.
Week 2: Take an existing presentation and ask Alex to restructure it using the SCR framework.
Week 3: Build a Copilot prompt library for your most common reporting scenarios.
Week 4: Run a full audit on a dashboard you own — apply the “so what” test to every visual.
What Great Looks Like
After consistent use, you should notice:
- Every chart has a single, statable argument
- Leadership narratives lead with the decision, not the data
- Customer reports feel like conversations, not scorecards
- You kill charts that don’t earn their place
The goal isn’t for Alex to make your visuals — it’s for Alex to make your thinking sharp enough that your visuals make arguments, not just pictures.