feat: add SparkToro as audience research tool
Add SparkToro integration guide, registry entry, and references in customer-research skill. SparkToro reveals where your ICP spends time using clickstream, search, and social data — essential for finding podcasts, YouTube channels, subreddits, and websites your audience engages with. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -282,6 +282,61 @@ Comments on review videos are especially valuable — these are people actively
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---
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## SparkToro (Audience Intelligence)
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SparkToro is a behavioral audience research tool. Instead of mining individual posts and comments, it aggregates clickstream, search, and social data to show what your audience does at scale — what they read, watch, listen to, follow, and search for.
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### When to Use SparkToro vs. Manual Research
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- **SparkToro first** when you need to understand where your ICP spends time, what content they consume, and which influencers they follow — it answers these questions in seconds with aggregated data
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- **Manual research first** (Reddit, G2, communities) when you need raw language, exact quotes, emotional context, and the "why" behind behavior
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- **Best together**: Use SparkToro to identify which podcasts, subreddits, and websites matter, then go mine those sources manually for voice-of-customer language
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### Key Queries to Run
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**By competitor:**
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- "People who follow @competitor" — reveals shared audience affinities
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- "People who visit competitor.com" — shows what else they consume
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**By audience description:**
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- "People who frequently talk about [topic]" — finds audience behaviors
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- "People whose bio contains [job title]" — profiles a role-based segment
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**By your own audience:**
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- "People who visit yourdomain.com" — understand your actual audience
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- Compare against competitor audience profiles to find gaps
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### What to Extract
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| Data Type | What It Tells You | Use It For |
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|-----------|------------------|------------|
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| Top websites visited | Where your audience reads | Content partnerships, guest posting targets |
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| Top podcasts | What they listen to | Podcast guesting, sponsorship decisions |
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| Top YouTube channels | What they watch | Video content strategy, ad placements |
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| Top subreddits | Where they discuss | Community participation, Reddit ad targeting |
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| Search keywords | What they Google | SEO and content topic planning |
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| AI prompt topics | What they ask AI tools | Emerging content opportunities |
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| Social accounts followed | Who influences them | Influencer partnerships, co-marketing |
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| Demographics | Who they are | Persona building, ad targeting |
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### Source Weighting
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SparkToro data is aggregated and anonymized — it shows patterns, not individual opinions. Treat it as:
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- **High confidence** for behavioral data (what they visit, follow, search for)
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- **Medium confidence** for demographic data (self-reported, may be incomplete)
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- **Not a substitute** for qualitative research (doesn't capture language, emotions, or the "why")
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### Limitations
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- Free tier: 5 reports/month, shallow results (top 5–10)
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- No public API — all research done through web interface
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- Skews English-language, US-centric
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- Shows what audiences do, not why — pair with qualitative sources
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See [tools/integrations/sparktoro.md](../../../tools/integrations/sparktoro.md) for full tool details and pricing.
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---
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## Organizing Your Research
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Use a simple tagging system across all sources:
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@@ -319,6 +374,7 @@ Not all sources carry equal weight. Use this guide when assigning confidence lab
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| Survey (multiple choice) | Low-medium | Artifacts of the options you provided |
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| NPS verbatims | Medium | Correlates with score; prompted by the survey moment |
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| YouTube/TikTok comments | Medium | Skews toward engaged viewers; social performance |
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| SparkToro audience data | Medium-high | Aggregated behavioral data; strong for "what" but not "why" |
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| Job postings | Low-medium | Aspirational, not necessarily reflective of current pain |
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### Confidence Labels in Practice
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