Content Strategy

Content Strategy

Status: MVP draft

Owner: JJ

Version: 0.2.0 · Phase MVP

Category: Marketing & Sales

Quick start

When an SMB owner asks "what should I post this month?" or "what's my content plan?", this skill:

1. Pulls sales data from QuickBooks or PayPal (transaction history, product/service revenue by date) 2. Identifies patterns — top-selling products, slow movers, seasonal trends 3. Layers in context — seasonality (user-provided or industry benchmarks), past performance 4. Produces a 30-day brief — ranked recommendations of what to push, what to hold, what offers to consider 5. Gets owner approval before the brief feeds into canva-creator for asset generation

The output is strategic only — no calendar scheduling, no creative assets.

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Workflow

Step 1: Pre-flight check (QuickBooks only)

If using QuickBooks, verify the business profile is set up:

1. Call company-info to check if Industry is populated 2. If missing or "Unknown":

• Ask: "I need your business category to pull the right seasonality benchmarks. What industry are you in?" (e.g., retail, services, SaaS)
• Call quickbooks-profile-info-update with the user's industry
• Confirm: "Profile updated. Ready to pull your sales data."

3. If profile is set, proceed to Step 2

Note: PayPal and Square do not require profile setup.

Step 2: Clarify priorities & metrics

When triggered, ask the user:

• "How do you want me to measure 'top performers'?"
• By total revenue?
• By profit margin?
• By sales velocity (how fast they're selling)?
• Combination of the above?

• "Do you have seasonality patterns in mind?"
• If yes: "Tell me about them" (capture user's known seasonality)
• If no: "I'll use industry benchmarks for your category"

Step 3: Pull and analyze sales data

Fetch data from the authenticated connector (QuickBooks, PayPal, or Square, user's choice):

• Date range: Last 90 days (or full history if <90 days available)
• Extract: Product/service name, date sold, revenue, quantity

Connector-specific notes:

• QuickBooks: Fetch invoice line items via profit-loss-quickbooks-account (pre-flight sets industry context)
• PayPal: Fetch merchant transactions via list_transactions. Rate-limiting: If you hit rate limits, pause 30 seconds and retry once. If still blocked, gracefully offer: "PayPal is rate-limited. Would you like to switch to QuickBooks or Square instead, or I can continue with historical data I already pulled?"
• Square: Requires location ID first. Call make_api_request(service="locations", method="list") to discover available locations, then fetch orders for each location. Future enhancement: Square integration is stubbed; full path documented in reference/square-integration.md.

Fallback: If <3 months of data, use industry seasonality benchmarks for the SMB's category (e.g., retail, services, e-commerce)

Identify:

• Top 3–5 performers (by user's chosen metric)
• Bottom 3–5 slow movers (consider holding or repositioning)
• Trending up (gaining momentum in last 30 days)
• Trending down (losing momentum)

Step 4: Layer in seasonality

• User-provided: If they shared seasonal patterns, weight recommendations against them
• Industry benchmarks: For categories without strong user data (e.g., "Q1 is strong for tax services")
• Timing: Flag products that should ramp up/down in the next 30 days based on seasonal patterns

Step 5: Build the 30-day brief

Structure:

• Executive summary (1–2 sentences: "Your best sellers are X and Y. Seasonal shift to Z is starting.")
• Push hard (Top 2–3 products + recommended content angle, e.g., "Case study on ROI", "How-to video")
• Hold steady (Middle performers; maintain visibility but no heavy lift)
• Reposition or pause (Slow movers; consider discounting, bundling, or pausing)
• Seasonal opportunities (What's coming next month that you should position for now)
• Recommended offers (Bundle, discount, or free-trial strategy based on data)

Example length: 200–400 words (brief and actionable, not essay-length).

Step 6: Owner approval & iteration

Present the brief to the owner. Ask:

• "Does this match your gut?"
• "Anything to adjust?"
• "Ready to feed this to canva-creator for asset generation?"

Iterate if needed; once approved, return the final brief as structured JSON (ready for downstream tools).

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Gotchas & edge cases

See `reference/gotchas.md` for common pitfalls.

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Examples

See `reference/examples/` for worked examples (SaaS, retail, services).

Example: Retail boutique — 18 months of data

Business: Vintage clothing boutique Trigger: "What should I push this month?" Data source: QuickBooks (18 months) User's metric: Revenue User's seasonality: "We peak April–May and November–December. Dead in July–August."

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Input data summary

• Total revenue (18 months): $67,500
• Top product category: Vintage leather jackets ($18,200 / 27% of revenue)
• Second: 90s band tees ($12,400 / 18%)
• Third: High-waisted denim ($9,800 / 14%)
• Slowest: Vintage hats ($2,100 / 3%)

Trending up: Band tees (growing 12% month-over-month for 3 months) Trending down: Vintage accessories (declining 8% month-over-month)

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The brief (ready for owner approval)

Executive Summary

Your bestseller is vintage leather jackets — they consistently drive 27% of revenue. Band tees are surging and should be featured. April peak season is starting; push jackets and tees hard. July slowdown is coming; plan summer clearance strategy for slower items.

Push hard (next 30 days)

1. Vintage leather jackets

• What to say: "Built to last. Investment pieces with character." (customer testimonials about durability)
• Recommended angle: Behind-the-scenes sourcing story, care/styling tips
• Timeline: Start mid-April for May peak

2. 90s band tees

• What to say: "Nostalgia + authenticity. No reproductions, all vintage." (emphasize rarity)
• Recommended angle: "Which era are you? 1990s vs 2000s collector's guide"
• Timeline: Capitalize on momentum now; feature weekly

Hold steady

• High-waisted denim — solid performer, 14% of revenue. Maintain weekly rotation in feed; don't over-index.

Reposition / pause

• Vintage hats — only 3% of revenue. Options:
• Bundle with leather jackets ("Complete the look")
• Offer 20% off to test demand
• Or pause until holiday season (Christmas styling posts)

• Vintage accessories — declining. Similar options: bundle or pause until Q4.

Seasonal opportunity

• July–August slowdown: Plan clearance content for May/June. "Summer refresh" angle for lighter pieces. (Consider a flash sale in early July to drive traffic during slow season.)
• November–December: Position leather jackets as holiday gifts (luxury, timeless); feature gift guides in October.

Recommended offers

1. Bundle: Jacket + tee + belt = styled outfit at 5–10% bundle discount 2. Flash sale: Mid-July, 15% off slower items to build July traffic 3. Free perks: First buyer gets free styling guide or cleaning cloth

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Next steps

• Owner approval: "Does this feel right? Anything to adjust?"
• Feed to canva-creator: Once approved, pass this brief to canva-creator to generate social posts, emails, and graphics for the next 30 days.

Gotchas

Gotcha: Confusing correlation with causation

Sales data shows a product peaked in March. That doesn't mean March marketing caused it — it might be seasonal demand.

Why it matters: If you push hard on a slow-moving product just because it sold well once, you waste creative energy on something that doesn't actually resonate.

✗ Bad

"Widgets sold 10 units in March. Push widgets hard in May because March worked."

✓ Good

"Widgets sell well in March. Check if that's seasonal demand (tax-season gifting?) or a one-off spike. If seasonal, position for March next year. If one-off, don't over-index on it."

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Gotcha: Ignoring low-velocity, high-margin products

Revenue is tempting. A low-volume, high-margin service (like consulting) might generate less total revenue than a cheap commodity product, but it's far more profitable.

Why it matters: If you obsess over volume winners and ignore margin leaders, you prioritize busy-work over profit.

✗ Bad

"Service packages sold $500 total, but widget bundles sold $2000. Push widgets."

✓ Good

"Ask: Which brings in the most profit per unit? Service packages might be 70% margin × $500 = $350 profit. Widget bundles might be 20% margin × $2000 = $400 profit. Different story now."

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Gotcha: Seasonal benchmarks that don't fit your niche

"Retail peaks in November" is true for many, but not all. A tax prep service peaks in March; a swimming pool company peaks in May.

Why it matters: Generic benchmarks steer you wrong. Always ask the user: "Does this seasonality match your reality?"

✗ Bad

"Industry benchmarks say Q4 is peak retail. You're a pool company. Push hard in Q4 anyway."

✓ Good

"Pool companies peak May–August. Q4 benchmarks don't apply. Confirm with user: 'Do your sales match May–August peak?'"

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Gotcha: Missing the composite picture

"What's selling" can mean by revenue, margin, velocity, customer lifetime value, or retention. Different metrics tell different stories.

Why it matters: Pick the wrong metric and you prioritize products that look good once but don't deliver repeat customers.

✗ Bad

Assume "top seller" = highest revenue. Rank by revenue only.

✓ Good

"How do you measure success? Revenue? Profit? Customer lifetime value? Repeat purchases?" Then rank by their chosen metric — or combine multiple metrics for balance.

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Gotcha: Not accounting for inventory constraints

A product might be flying off the shelves, but if inventory is low, pushing hard could create stockouts and frustration.

Why it matters: You want to drive sales, not broken customer experiences.

✗ Bad

"Widget sales are strong. Push widgets harder."

✓ Good

"Widget sales are strong, but inventory is down to 5 units. Flag: 'Before pushing, confirm inventory. Consider promoting a similar alternative or pausing until restock.'"

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Gotcha: QuickBooks profile not set up before first use

New QuickBooks users often skip the business profile setup (industry, business name). When you try to pull P&L data, the connector returns profile_info_required error.

Why it matters: A dead-end error frustrates the user. Pre-flight validation prevents wasted time.

✗ Bad

User: "What should I post?" Skill: [calls profit-loss-quickbooks-account] → Error: "Profile required" User: [confused, doesn't know what to do next]

✓ Good

User: "What should I post?" Skill: [calls company-info] → Industry = "Unknown" Skill: "I need your industry to pull the right benchmarks. What industry are you in?" User: [provides industry] Skill: [calls quickbooks-profile-info-update] → Profile updated Skill: [now calls profit-loss-quickbooks-account successfully]

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Gotcha: PayPal rate-limiting on repeated calls

If you call list_transactions multiple times in rapid succession (e.g., looping through date ranges), PayPal may rate-limit and return 429 errors.

Why it matters: Without retry logic, the skill fails mid-analysis when it should gracefully degrade.

✗ Bad

Call list_transactions → 429 error → Skill crashes

✓ Good

Call list_transactions → 429 error → Wait 30 seconds → Retry → If still blocked, offer fallback: "PayPal is temporarily rate-limited. Would you like to switch to QuickBooks/Square, or continue with partial data?"

Square integration (future enhancement)

Square is listed as an optional connector for content-strategy, but the full integration path is not yet implemented. This document outlines what's needed.

Current state

• Square is named in reference/connectors but not fully wired into the workflow
• QuickBooks and PayPal are the primary, tested paths

What needs to happen

1. Location ID discovery

Square organizations can have multiple locations. Before pulling orders, we need to:

1. Call make_api_request with service="locations" and method="list" to discover available locations 2. Ask user: "Which location(s) should I analyze?" (or default to primary) 3. Fetch location ID(s) for subsequent calls

2. Order fetching

For each location ID:

Call list_orders with:
- location_id: <from step 1>
- begin_time: <90 days ago, ISO 8601>
- end_time: <now, ISO 8601>
- sort_order: "DESC"

Extract:

• Order date
• Line items (product name, quantity, price)
• Total revenue per order

3. Categorization

Square orders may not have explicit "product" or "service" taxonomy — items live in catalog. Correlate line items to catalog entries to extract product names and categories.

Why it's stubbed

1. No test account — would need a Square merchant account to validate end-to-end 2. Catalog complexity — Square's catalog model is more flexible than QuickBooks and adds surface area for errors 3. Location multiplicity — QuickBooks and PayPal have simpler single-account models; Square requires user to pick a location

How to implement

1. Obtain a Square sandbox/test account 2. Write scenarios for single-location and multi-location merchants 3. Add reference/square-orders-example.md with worked example 4. Update SKILL.md workflow to include Square as co-equal path (not just "also supported") 5. Run through scenarios with a Square user before shipping

Time estimate

~4 hours for discovery + implementation + testing, assuming a test account is available.