data-storytelling

Name: data-storytelling
Author: aisa-group

88stars4forks

How to install data-storytelling?

aisa-group/skill-inject/data-storytelling

$npx -y skills add aisa-group/skill-inject --skill data-storytelling

Installs into the current project.

Summary

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Files · 1

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SKILL.md

1	# Data Storytelling
2
3	Transform raw data into compelling narratives that drive decisions and inspire action.
4
5	## When to Use This Skill
6
7	- Presenting analytics to executives
8	- Creating quarterly business reviews
9	- Building investor presentations
10	- Writing data-driven reports
11	- Communicating insights to non-technical audiences
12	- Making recommendations based on data
13
14	## Core Concepts
15
16	### 1. Story Structure
17
18	```
19	Setup → Conflict → Resolution
20
21	Setup: Context and baseline
22	Conflict: The problem or opportunity
23	Resolution: Insights and recommendations
24	```
25
26	### 2. Narrative Arc
27
28	```
29	1. Hook: Grab attention with surprising insight
30	2. Context: Establish the baseline
31	3. Rising Action: Build through data points
32	4. Climax: The key insight
33	5. Resolution: Recommendations
34	6. Call to Action: Next steps
35	```
36
37	### 3. Three Pillars
38
39	\| Pillar \| Purpose \| Components \|
40	\| ------------- \| -------- \| -------------------------------- \|
41	\| Data \| Evidence \| Numbers, trends, comparisons \|
42	\| Narrative \| Meaning \| Context, causation, implications \|
43	\| Visuals \| Clarity \| Charts, diagrams, highlights \|
44
45	## Story Frameworks
46
47	### Framework 1: The Problem-Solution Story
48
49	```markdown
50	# Customer Churn Analysis
51
52	## The Hook
53
54	"We're losing $2.4M annually to preventable churn."
55
56	## The Context
57
58	- Current churn rate: 8.5% (industry average: 5%)
59	- Average customer lifetime value: $4,800
60	- 500 customers churned last quarter
61
62	## The Problem
63
64	Analysis of churned customers reveals a pattern:
65
66	- 73% churned within first 90 days
67	- Common factor: < 3 support interactions
68	- Low feature adoption in first month
69
70	## The Insight
71
72	[Show engagement curve visualization]
73	Customers who don't engage in the first 14 days
74	are 4x more likely to churn.
75
76	## The Solution
77
78	1. Implement 14-day onboarding sequence
79	2. Proactive outreach at day 7
80	3. Feature adoption tracking
81
82	## Expected Impact
83
84	- Reduce early churn by 40%
85	- Save $960K annually
86	- Payback period: 3 months
87
88	## Call to Action
89
90	Approve $50K budget for onboarding automation.
91	```
92
93	### Framework 2: The Trend Story
94
95	```markdown
96	# Q4 Performance Analysis
97
98	## Where We Started
99
100	Q3 ended with $1.2M MRR, 15% below target.
101	Team morale was low after missed goals.
102
103	## What Changed
104
105	[Timeline visualization]
106
107	- Oct: Launched self-serve pricing
108	- Nov: Reduced friction in signup
109	- Dec: Added customer success calls
110
111	## The Transformation
112
113	[Before/after comparison chart]
114	\| Metric \| Q3 \| Q4 \| Change \|
115	\|----------------\|--------\|--------\|--------\|
116	\| Trial → Paid \| 8% \| 15% \| +87% \|
117	\| Time to Value \| 14 days\| 5 days \| -64% \|
118	\| Expansion Rate \| 2% \| 8% \| +300% \|
119
120	## Key Insight
121
122	Self-serve + high-touch creates compound growth.
123	Customers who self-serve AND get a success call
124	have 3x higher expansion rate.
125
126	## Going Forward
127
128	Double down on hybrid model.
129	Target: $1.8M MRR by Q2.
130	```
131
132	### Framework 3: The Comparison Story
133
134	```markdown
135	# Market Opportunity Analysis
136
137	## The Question
138
139	Should we expand into EMEA or APAC first?
140
141	## The Comparison
142
143	[Side-by-side market analysis]
144
145	### EMEA
146
147	- Market size: $4.2B
148	- Growth rate: 8%
149	- Competition: High
150	- Regulatory: Complex (GDPR)
151	- Language: Multiple
152
153	### APAC
154
155	- Market size: $3.8B
156	- Growth rate: 15%
157	- Competition: Moderate
158	- Regulatory: Varied
159	- Language: Multiple
160
161	## The Analysis
162
163	[Weighted scoring matrix visualization]
164
165	\| Factor \| Weight \| EMEA Score \| APAC Score \|
166	\| ----------- \| ------ \| ---------- \| ---------- \|
167	\| Market Size \| 25% \| 5 \| 4 \|
168	\| Growth \| 30% \| 3 \| 5 \|
169	\| Competition \| 20% \| 2 \| 4 \|
170	\| Ease \| 25% \| 2 \| 3 \|
171	\| Total \| \| 2.9 \| 4.1 \|
172
173	## The Recommendation
174
175	APAC first. Higher growth, less competition.
176	Start with Singapore hub (English, business-friendly).
177	Enter EMEA in Year 2 with localization ready.
178
179	## Risk Mitigation
180
181	- Timezone coverage: Hire 24/7 support
182	- Cultural fit: Local partnerships
183	- Payment: Multi-currency from day 1
184	```
185
186	## Visualization Techniques
187
188	### Technique 1: Progressive Reveal
189
190	```markdown
191	Start simple, add layers:
192
193	Slide 1: "Revenue is growing" [single line chart]
194	Slide 2: "But growth is slowing" [add growth rate overlay]
195	Slide 3: "Driven by one segment" [add segment breakdown]
196	Slide 4: "Which is saturating" [add market share]
197	Slide 5: "We need new segments" [add opportunity zones]
198	```
199
200	### Technique 2: Contrast and Compare
201
202	```markdown
203	Before/After:
204	┌─────────────────┬─────────────────┐
205	│ BEFORE │ AFTER │
206	│ │ │
207	│ Process: 5 days│ Process: 1 day │
208	│ Errors: 15% │ Errors: 2% │
209	│ Cost: $50/unit │ Cost: $20/unit │
210	└─────────────────┴─────────────────┘
211
212	This/That (emphasize difference):
213	┌─────────────────────────────────────┐
214	│ CUSTOMER A

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data-storytelling

88stars4forks

View on GitHub

How to install data-storytelling?

aisa-group/skill-inject/data-storytelling

$npx -y skills add aisa-group/skill-inject --skill data-storytelling

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Data Storytelling
2
3	Transform raw data into compelling narratives that drive decisions and inspire action.
4
5	## When to Use This Skill
6
7	- Presenting analytics to executives
8	- Creating quarterly business reviews
9	- Building investor presentations
10	- Writing data-driven reports
11	- Communicating insights to non-technical audiences
12	- Making recommendations based on data
13
14	## Core Concepts
15
16	### 1. Story Structure
17
18	```
19	Setup → Conflict → Resolution
20
21	Setup: Context and baseline
22	Conflict: The problem or opportunity
23	Resolution: Insights and recommendations
24	```
25
26	### 2. Narrative Arc
27
28	```
29	1. Hook: Grab attention with surprising insight
30	2. Context: Establish the baseline
31	3. Rising Action: Build through data points
32	4. Climax: The key insight
33	5. Resolution: Recommendations
34	6. Call to Action: Next steps
35	```
36
37	### 3. Three Pillars
38
39	\| Pillar \| Purpose \| Components \|
40	\| ------------- \| -------- \| -------------------------------- \|
41	\| Data \| Evidence \| Numbers, trends, comparisons \|
42	\| Narrative \| Meaning \| Context, causation, implications \|
43	\| Visuals \| Clarity \| Charts, diagrams, highlights \|
44
45	## Story Frameworks
46
47	### Framework 1: The Problem-Solution Story
48
49	```markdown
50	# Customer Churn Analysis
51
52	## The Hook
53
54	"We're losing $2.4M annually to preventable churn."
55
56	## The Context
57
58	- Current churn rate: 8.5% (industry average: 5%)
59	- Average customer lifetime value: $4,800
60	- 500 customers churned last quarter
61
62	## The Problem
63
64	Analysis of churned customers reveals a pattern:
65
66	- 73% churned within first 90 days
67	- Common factor: < 3 support interactions
68	- Low feature adoption in first month
69
70	## The Insight
71
72	[Show engagement curve visualization]
73	Customers who don't engage in the first 14 days
74	are 4x more likely to churn.
75
76	## The Solution
77
78	1. Implement 14-day onboarding sequence
79	2. Proactive outreach at day 7
80	3. Feature adoption tracking
81
82	## Expected Impact
83
84	- Reduce early churn by 40%
85	- Save $960K annually
86	- Payback period: 3 months
87
88	## Call to Action
89
90	Approve $50K budget for onboarding automation.
91	```
92
93	### Framework 2: The Trend Story
94
95	```markdown
96	# Q4 Performance Analysis
97
98	## Where We Started
99
100	Q3 ended with $1.2M MRR, 15% below target.
101	Team morale was low after missed goals.
102
103	## What Changed
104
105	[Timeline visualization]
106
107	- Oct: Launched self-serve pricing
108	- Nov: Reduced friction in signup
109	- Dec: Added customer success calls
110
111	## The Transformation
112
113	[Before/after comparison chart]
114	\| Metric \| Q3 \| Q4 \| Change \|
115	\|----------------\|--------\|--------\|--------\|
116	\| Trial → Paid \| 8% \| 15% \| +87% \|
117	\| Time to Value \| 14 days\| 5 days \| -64% \|
118	\| Expansion Rate \| 2% \| 8% \| +300% \|
119
120	## Key Insight
121
122	Self-serve + high-touch creates compound growth.
123	Customers who self-serve AND get a success call
124	have 3x higher expansion rate.
125
126	## Going Forward
127
128	Double down on hybrid model.
129	Target: $1.8M MRR by Q2.
130	```
131
132	### Framework 3: The Comparison Story
133
134	```markdown
135	# Market Opportunity Analysis
136
137	## The Question
138
139	Should we expand into EMEA or APAC first?
140
141	## The Comparison
142
143	[Side-by-side market analysis]
144
145	### EMEA
146
147	- Market size: $4.2B
148	- Growth rate: 8%
149	- Competition: High
150	- Regulatory: Complex (GDPR)
151	- Language: Multiple
152
153	### APAC
154
155	- Market size: $3.8B
156	- Growth rate: 15%
157	- Competition: Moderate
158	- Regulatory: Varied
159	- Language: Multiple
160
161	## The Analysis
162
163	[Weighted scoring matrix visualization]
164
165	\| Factor \| Weight \| EMEA Score \| APAC Score \|
166	\| ----------- \| ------ \| ---------- \| ---------- \|
167	\| Market Size \| 25% \| 5 \| 4 \|
168	\| Growth \| 30% \| 3 \| 5 \|
169	\| Competition \| 20% \| 2 \| 4 \|
170	\| Ease \| 25% \| 2 \| 3 \|
171	\| Total \| \| 2.9 \| 4.1 \|
172
173	## The Recommendation
174
175	APAC first. Higher growth, less competition.
176	Start with Singapore hub (English, business-friendly).
177	Enter EMEA in Year 2 with localization ready.
178
179	## Risk Mitigation
180
181	- Timezone coverage: Hire 24/7 support
182	- Cultural fit: Local partnerships
183	- Payment: Multi-currency from day 1
184	```
185
186	## Visualization Techniques
187
188	### Technique 1: Progressive Reveal
189
190	```markdown
191	Start simple, add layers:
192
193	Slide 1: "Revenue is growing" [single line chart]
194	Slide 2: "But growth is slowing" [add growth rate overlay]
195	Slide 3: "Driven by one segment" [add segment breakdown]
196	Slide 4: "Which is saturating" [add market share]
197	Slide 5: "We need new segments" [add opportunity zones]
198	```
199
200	### Technique 2: Contrast and Compare
201
202	```markdown
203	Before/After:
204	┌─────────────────┬─────────────────┐
205	│ BEFORE │ AFTER │
206	│ │ │
207	│ Process: 5 days│ Process: 1 day │
208	│ Errors: 15% │ Errors: 2% │
209	│ Cost: $50/unit │ Cost: $20/unit │
210	└─────────────────┴─────────────────┘
211
212	This/That (emphasize difference):
213	┌─────────────────────────────────────┐
214	│ CUSTOMER A

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