From salla-merchant-understanding
Map a Salla merchant's journey through a specific flow or pillar. Identifies emotions, pain points, platform gaps, and opportunity areas. Arabic market and mobile-first context built in. Slash command: /merchant-journey
How this skill is triggered — by the user, by Claude, or both
Slash command
/salla-merchant-understanding:merchant-journeyThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are mapping a Salla merchant's journey through a specific experience. Journey maps here are not abstract — they reflect real Salla merchants navigating real platform flows, with mobile-first context, Arabic UX, and Saudi e-commerce realities built in.
You are mapping a Salla merchant's journey through a specific experience. Journey maps here are not abstract — they reflect real Salla merchants navigating real platform flows, with mobile-first context, Arabic UX, and Saudi e-commerce realities built in.
knowledge/pm-context.md for pillar context and segment focus.knowledge/platform-pillars.md for the pillar's known pain points and touchpoints.knowledge/personas/ for relevant merchant personas.knowledge/research/ for any existing research to ground the journey in.knowledge/feedback/ for merchant feedback related to this journey.Ask:
"Which merchant journey do you want to map?" Examples:
"Which merchant persona or segment?" (Nano / SMB / Mid-Market / or reference a specific persona from knowledge/personas/)
"What's the research question this journey map should answer?" (e.g., "Where do merchants drop off in checkout setup?" or "What's causing low loyalty program activation?")
If knowledge/research/ contains relevant research, use it to populate the emotional states and pain points.
If Slack MCP is available, search for CS tickets or merchant feedback related to this flow.
If no data is available, use knowledge/platform-pillars.md pain points and ask the PM:
# Merchant Journey Map: [Journey Title]
**Merchant persona:** [Persona name / Segment]
**Journey scope:** [Start point → End point]
**Research question:** [What this map answers]
**Data sources:** [Research used to build this map]
**Created:** [Date]
---
## Journey Overview
> [One paragraph summary of this journey — what the merchant is trying to do, how it currently feels, and what Salla's biggest opportunity is]
---
## Journey Stages
[Adapt stage names to the specific journey. Example for onboarding: Discover → Sign Up → Configure → Launch → First Sale]
### Stage 1: [Stage Name]
**What the merchant is doing:**
[Concrete actions the merchant takes in this stage]
**Touchpoints with Salla:**
[Which Salla screens, emails, notifications, or CS contacts happen here]
**Device context:**
[Mobile app / Desktop / Both — note expected device split]
**Emotional state:**
[How the merchant feels: excited / confused / frustrated / confident]
Scale: 😊 Positive | 😐 Neutral | 😟 Frustrated | 😤 Blocked
**What's working well:**
- [Positive experience element]
- [Positive experience element]
**Pain points:**
- [Pain point] — *Severity:* [High/Med/Low] — *Evidence:* [Source]
- [Pain point] — *Severity:* [High/Med/Low] — *Evidence:* [Source]
**Arabic/Mobile considerations:**
[Any specific RTL, Arabic language, or mobile UX issues in this stage]
**Quote from merchant:**
> "[Representative quote — in Arabic if authentic, with translation. e.g., 'الصفحة ما تحمل عندي على الجوال' — 'The page doesn't load on my phone'"]"
**Opportunity:**
[Specific product opportunity emerging from this stage's pain points]
---
### Stage 2: [Stage Name]
[Repeat structure]
---
### Stage 3: [Stage Name]
[Repeat structure]
---
[Continue for all stages]
---
## Emotion Curve
[Represent the merchant's emotional journey across stages using text visualization]
Stage: | [Stage 1] | [Stage 2] | [Stage 3] | [Stage 4] | [Stage 5] Emotion: | 😊 | 😐 | 😟 | 😤 | 😊 Level: | +3 | +1 | -1 | -3 | +2
**Lowest point:** [Stage with worst experience and why]
**Highest point:** [Stage with best experience and why]
**Critical drop:** [Any stage where experience drops sharply — these are the most urgent opportunities]
---
## Key Findings
### Biggest Pain Point
**[Pain]** — [Why this is the #1 issue in this journey. Evidence. Which merchants are most affected.]
### Moment of Delight (if any)
**[What works well]** — [Why this creates a positive experience. What can be learned from it.]
### Biggest Drop-Off Risk
**[Stage / step where merchants are most likely to abandon]** — [Evidence, hypothesis for cause]
---
## Salla Platform Gaps Identified
| Gap | Stage | Affected Segment | Severity | Which Pillar Owns It |
|-----|-------|-----------------|----------|---------------------|
| [Specific missing feature or broken flow] | [Stage] | [Segment] | [High/Med/Low] | [Pillar] |
| | | | | |
---
## Arabic/Mobile-Specific Findings
[Issues unique to the Arabic or mobile experience in this journey:]
- **[Issue]:** [Description, where in the journey, impact, fix direction]
- **[Issue]:** [Description]
---
## Opportunities (Ranked by Impact)
| # | Opportunity | Stage | Effort | OKR Alignment | Recommendation |
|---|------------|-------|--------|--------------|---------------|
| 1 | [Specific opportunity in product terms] | [Stage] | [High/Med/Low] | [KR it supports] | Prioritize |
| 2 | | | | | Explore |
| 3 | | | | | Future |
---
## Competitor Reference
[How do Zid, Shopify, or other competitors handle the most painful stage of this journey? What can Salla learn or differentiate from?]
---
## Recommended Next Steps
1. [Most immediate action — e.g., "Run `/write-prd` for Opportunity 1"]
2. [Research needed — e.g., "Conduct 5 merchant interviews to validate the Stage 3 pain point hypothesis"]
3. [Cross-team coordination — e.g., "Share Stage 2 findings with the [other pillar] team"]
Write to: knowledge/research/journey-[journey-slug].md
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.
npx claudepluginhub bakrsabeeh/salla-super-pm --plugin salla-merchant-understanding