Digital Product Opportunity Radar — Etsy + Pinterest

Find evidence-backed digital product opportunities using live Etsy market signals and Pinterest trend validation.

This Apify Actor is a focused product opportunity finder for creators deciding which digital-product niche to test next. It is not a generic scraper or an AI idea generator. It turns normalized marketplace evidence into transparent rankings, confidence scores, and TEST / WATCH / SKIP decisions.

1. What this Actor does

Give the Actor up to five seed niches, such as ADHD planner. It discovers related Etsy keyword opportunities, shortlists candidates using Etsy commercial evidence, validates those candidates against Pinterest trends, and returns one Dataset row per ranked opportunity.

Example result:

ADHD Morning Routine Cards

Opportunity: 82/100
Confidence: 89/100
Decision: TEST

Why:
- strong Etsy demand
- manageable entry headroom
- positive Pinterest validation

Numbers above are illustrative. Production scores are calculated only from normalized upstream evidence; missing values remain null.

Use it for Etsy product research, Etsy keyword research, printable product research, Etsy niche research, market validation, and prioritizing digital downloads. It can surface stronger and weaker candidates related to a seed; it does not promise “low competition Etsy niches” or guaranteed sales.

2. Who it is for

• Etsy digital-product and printable sellers
• Designers researching editable templates, planners, worksheets, trackers, and bundles
• Product researchers comparing digital product ideas with current evidence
• Agencies or automation builders that need structured niche-research output through the Apify API

3. How it works

Seed niche
  → Etsy keyword discovery
  → Etsy adapter and normalization
  → evidence-based candidate shortlist
  → Pinterest trend validation
  → Pinterest adapter and normalization
  → transparent opportunity + confidence scoring
  → ranked Dataset rows and full reports

Etsy is the primary commercial evidence source. Pinterest trends are secondary validation and cannot overpower Etsy in the score.

The default upstream Actors are configurable without changing business logic:

• Etsy: yumitori/etsy-keyword-tool
• Pinterest: yumitori/pinterest-trends-scraper in keyword-research mode

4. Input

{
  "seeds": [
    "ADHD planner",
    "kids screen free activities"
  ],
  "country": "US",
  "maxOpportunities": 10,
  "candidateLimitPerSeed": 20,
  "etsyExpansionDepth": 1,
  "debug": false
}

Field	Required	Default	Limits
seeds	Yes	—	1–5 strings, each 2–80 characters
country	No	US	US, GB, CA, DE, FR, IT, ES, BR, MX, AR, IN
maxOpportunities	No	10	1–20
candidateLimitPerSeed	No	20	1–40
etsyExpansionDepth	No	1	1 or 2
debug	No	false	Includes safe normalization/scoring metadata; never secrets

5. Output

The default Dataset receives one item per opportunity. Each record contains:

• the original seed, final rank, normalized keyword, suggested product, and conservative product format
• Opportunity Score, Confidence Score, and decision
• all normalized score components
• Etsy sample size, listings, average price, carts, recent-sales/listing shares, discount density, and digital-product share
• qualified Pinterest term, match quality, search volumes, multi-week momentum windows, trend evidence, and FULL / PARTIAL / NONE evidence quality
• available Etsy and Pinterest evidence; missing or low-quality evidence is null
• deterministic reasons and signal-supported risks
• real source URLs when upstream data supplies them

The default Key-Value Store also contains:

• OUTPUT.json: the full machine-readable report
• REPORT.md: a concise human-readable report

6. Opportunity Score

The 0–100 Opportunity Score uses these components:

Component	Weight
Etsy demand	30%
Entry headroom (100 - competition)	25%
Digital fit (digital_pct)	15%
Pinterest validation	15%
Margin potential	10%
Freshness (recent_listings_pct)	5%

Missing components are ignored and available weights are re-normalized. Missing Pinterest data is not converted to zero. A normal score requires Etsy demand plus additional Etsy evidence; otherwise the result is INSUFFICIENT_EVIDENCE.

7. Confidence Score

Confidence is separate from opportunity quality. A promising niche can have a high Opportunity Score and low Confidence Score when evidence coverage is thin.

Confidence component	Weight
Etsy core-evidence completeness	60%
Etsy sample credibility	25%
Qualified cross-market confirmation	15%

Rich Etsy evidence can establish meaningful baseline confidence on its own. A qualified Pinterest match increases confidence; Pinterest remains optional and does not automatically lower the Etsy-based Opportunity Score when unavailable.

Pinterest evidence is FULL when a qualified match includes enough weekly history for stable multi-week comparison, PARTIAL when a qualified match has current-interest/trend evidence but no usable history, and NONE when no sufficiently related validation is available. Partial validation is deliberately discounted. Separately, matchType reports semantic specificity as EXACT, CLOSE, BROAD, or NONE; broad matches retain their raw trend evidence but receive a capped validation contribution because an important niche token was dropped.

8. TEST / WATCH / SKIP

• TEST: Opportunity ≥ 75 and Confidence ≥ 60
• WATCH: Opportunity ≥ 60 but the TEST rule is not met
• SKIP: Opportunity < 60
• INSUFFICIENT_EVIDENCE: minimum Etsy evidence is unavailable

These decisions prioritize small, inexpensive product tests. They are not predictions or guarantees.

9. Example output

{
  "recordType": "opportunity",
  "seed": "ADHD planner",
  "rank": 1,
  "keyword": "adhd morning routine cards",
  "suggestedProduct": "ADHD Morning Routine Cards",
  "suggestedFormat": "Printable cards",
  "opportunityScore": 82,
  "confidenceScore": 87,
  "decision": "TEST",
  "scores": {
    "etsyDemand": 88,
    "entryHeadroom": 72,
    "digitalFit": 100,
    "pinterestValidation": 81,
    "marginPotential": 70,
    "freshness": 78
  }
}

This example is illustrative, not hardcoded production data.

10. Data sources

The Actor orchestrates existing Apify Store Actors rather than maintaining its own Etsy or Pinterest crawlers. Adapters isolate upstream schemas from the scoring engine. Override providers with ETSY_ACTOR_ID and PINTEREST_ACTOR_ID when a compatible adapter mapping is available.

Cost protection defaults to $1.00 total across Etsy seed calls and $0.25 for the Pinterest call. Configure:

ETSY_MAX_TOTAL_CHARGE_USD=1.00
PINTEREST_MAX_TOTAL_CHARGE_USD=0.25
ETSY_TIMEOUT_SECONDS=300
PINTEREST_TIMEOUT_SECONDS=300

The SDK passes these limits to child Actor runs. Etsy's configured budget is divided across the 1–5 seed calls so the run-level cap remains conservative.

11. Limitations

• Scores are research signals, not revenue guarantees.
• Etsy is the primary commercial evidence source.
• Pinterest is used as secondary trend validation.
• Pinterest attention does not necessarily equal purchasing demand.
• Missing Pinterest data is not treated as zero demand.
• Marketplace conditions change over time.
• Upstream Actor schemas and field coverage can change; unknown fields are not guessed.
• Results should prioritize small product tests, not justify large upfront investment.
• Upstream Actors can have their own pricing, availability, geographic coverage, and usage limits.

12. API / automation usage

Run locally after providing Apify credentials:

npm install
npm run build
apify run

Deploy from this directory:

npm install -g apify-cli
apify login
apify validate-schema
apify push

Use the Apify API after deployment:

curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_USERNAME~digital-product-opportunity-radar/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"seeds":["meal planner"],"country":"US","maxOpportunities":3,"candidateLimitPerSeed":5,"etsyExpansionDepth":1}'

Development and verification

Tests use sanitized fixtures and never call paid Actors:

npm run typecheck
npm test
npm run build

Report charging is scaffolded but disabled by default. Enable it only after configuring Pay-Per-Event pricing in Apify Console:

ENABLE_REPORT_CHARGING=true
ACTOR_TEST_PAY_PER_EVENT=true

The only future charge event in code is report_generated, issued after output is written and only when the effective pricing model is Pay-Per-Event.