sales-buzzabout

What this skill does

# Buzzabout Platform Help

Helps the user with Buzzabout platform questions — from research setup and credit optimization through AI analysis, narrative tracking, audience segmentation, and competitive intelligence.

## Step 1 — Gather context

If `references/learnings.md` exists, read it first for accumulated platform knowledge.

Ask the user:

1. **What area of Buzzabout do you need help with?**
   - A) Research setup — topics, keywords, language filters
   - B) Credit management — optimizing RH usage, understanding overage costs
   - C) AI analysis — interpreting sentiment, trends, pain points
   - D) Narrative tracking — setting up Slack alerts for topic shifts
   - E) Audience segmentation — creating and refining synthetic audiences
   - F) Competitive research — reverse-engineering competitor strategies
   - G) Integrations — Zapier webhook, Slack alerts, API (Enterprise)
   - H) Billing — Pro vs Business vs Enterprise plan differences
   - I) Something else — describe it

2. **What's your goal?** (describe your specific question or problem)

**If the user's request already provides most of this context, skip directly to Step 2.** Lead with your best-effort answer using reasonable assumptions (stated explicitly), then ask only the most critical 1-2 clarifying questions at the end.

## Step 2 — Route or answer directly

If the request maps to a specialized skill, route:
- Social listening strategy or tool comparison → `/sales-social-listening [question]`
- Audience intelligence (where audiences spend attention) → `/sales-sparktoro [question]`
- Content intelligence and trending content → `/sales-buzzsumo [question]`
- Reddit-specific monitoring or lead gen → `/sales-social-listening [question]`
- Buyer intent signals and prioritization → `/sales-intent [question]`

Otherwise, answer directly from the platform reference below.

## Step 3 — Buzzabout platform reference

**Read `references/platform-guide.md`** for the full platform reference — capabilities, pricing, credit system, integration recipes, and comparison with alternatives.

Answer the user's question using only the relevant section. Don't dump the full reference.

## Step 4 — Actionable guidance

You no longer need the platform guide — focus on the user's specific situation.

1. **Research setup** — start with narrow topics, expand after reviewing initial results; use language filters to reduce noise
2. **Credit optimization** — batch related queries; use custom date ranges to avoid scanning irrelevant timeframes; credit rollovers help if usage is uneven month-to-month
3. **Narrative tracking** — set up Slack alerts for emerging narratives so you catch trend shifts early
4. **Audience segmentation** — refine synthetic audiences by cross-referencing with actual customer profiles; segments are starting points, not final targeting
5. **Competitive research** — analyze competitor brand mentions alongside your own; focus on sentiment differences and unmet needs

If you discover a gotcha, workaround, or tip not covered in `references/learnings.md`, append it there.

## Gotchas

*Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.*

- **Credit-based pricing is unpredictable.** Research Hours (RH) consumption varies by query complexity and data volume. A broad topic scan burns more credits than a narrow one. Monitor usage in the dashboard and set overage alerts ($0.25/RH overage adds up fast).
- **API is Enterprise-only.** Pro and Business plans have no programmatic access except via the Zapier webhook digest workaround. If you need API access, you must contact sales for Enterprise pricing.
- **Zapier webhook is the only automation path on Pro/Business.** Insert Zapier's webhook URL as a digest destination to route topic alerts to Slack, email, or other tools. There is no native REST API endpoint.
- **Synthetic audiences are AI-generated, not tracked cohorts.** They're derived from conversation patterns, not actual user profiles. Useful for messaging direction, not for targeting.
- **Data sources are broad but depth varies.** Reddit and TikTok analysis is strongest. Instagram, LinkedIn, and X coverage depends on public data access, which platforms restrict periodically.
- **Free trial is limited.** Evaluate whether the credit allocation covers your research scope before committing to a paid plan.

## Related skills

- `/sales-social-listening` — Social listening strategy — monitoring setup, tool comparison, sentiment analysis, competitive intelligence, crisis detection
- `/sales-sparktoro` — SparkToro — audience intelligence revealing where audiences spend attention (websites, podcasts, YouTube, subreddits)
- `/sales-buzzsumo` — BuzzSumo — content intelligence, trending topics, journalist database, backlinks API
- `/sales-reddinbox` — Reddinbox — AI audience intelligence across Reddit, X, HN with intent scoring and market briefs
- `/sales-do` — Not sure which skill to use? The router matches any sales objective to the right skill. Install: `npx skills add sales-skills/sales --skill sales-do`

## Examples

### Example 1: Optimize credit usage for market research
**User says**: "I'm burning through my 200 RH in the first week doing competitor research — how do I make credits last?"
**Skill does**:
1. Reviews how RH consumption works — broader queries and longer date ranges consume more
2. Recommends narrowing date ranges to last 30 days instead of all-time
3. Suggests batching related competitor queries into single research sessions
4. Notes credit rollovers mean unused credits carry over — consider spreading research across weeks
**Result**: Practical credit optimization strategy to stretch 200 RH across a full month

### Example 2: Set up automated content ideas via Zapier
**User says**: "How do I get Buzzabout to send me trending topic ideas in Slack every morning?"
**Skill does**:
1. Explains the Zapier webhook integration — insert webhook URL as digest destination
2. Walks through setting up a Zapier workflow: Buzzabout digest → Zapier webhook trigger → OpenAI action (generate content ideas) → Slack message
3. Notes this is the only automation path on Pro/Business — no native API
4. Suggests daily digest frequency to avoid credit overconsumption
**Result**: Working Zapier automation pipeline from Buzzabout to Slack with AI content generation

### Example 3: Compare Buzzabout vs SparkToro for audience research
**User says**: "Should I use Buzzabout or SparkToro to understand my target audience?"
**Skill does**:
1. Explains the fundamental difference: Buzzabout analyzes what audiences say (conversations, sentiment, pain points); SparkToro reveals where audiences spend attention (websites, podcasts, channels)
2. Notes Buzzabout is better for understanding motivations and trending narratives; SparkToro is better for channel discovery and ad placement
3. Suggests using both if budget allows — SparkToro for finding channels, Buzzabout for understanding what resonates
4. Compares pricing: Buzzabout Pro $49/mo vs SparkToro Personal $50/mo
**Result**: Clear comparison based on user's specific research goals

## Troubleshooting

### AI analysis results feel generic or shallow
**Symptom**: Buzzabout returns insights that seem obvious or don't match what you see in actual conversations
**Cause**: Topic query is too broad, covering millions of conversations without specificity
**Solution**: Narrow the research topic with specific keywords, competitor names, or product categories. Use language filters if your market is non-English. Try the AI Chat interface to ask follow-up questions that drill into specific themes. Reduce the date range to focus on recent conversations where trends are clearer.

### Research credits depleting too fast
**Symptom**: Running out of 200 RH (Pro) or 600 RH (Business) well before month end
**Cause**: Running broad queries, long date ranges, or too many parallel research sessions
**Solution**: Che