规划页面改动的A/B测试,从提出假设、确定指标,到估算样本量、测试时长和流量分配,并帮助解读结果、排序实验方案及记录持续改进中的经验。
- 比较标题或注册按钮
- 估算样本量和测试时长
- 检查结果及可能的不利影响
为企业服务、SaaS、当地商家或早期产品寻找并筛选潜在客户,依据来源核实匹配度和购买信号,验证邮箱,并整理优先级名单或需求证据报告。
When the user wants to find, qualify, and build a list of prospects to reach out to, across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find leads," "lead list," "outbound list," "target account list," "ICP-fit accounts," "find local businesses," "find my first customers," "design partners," "signal-based outbound," "buying signals," "intent data," "job change alerts," "waterfall enrichment," "Clay table," "lookalike accounts," "catch-all emails," "account tiering," or "research this account before I reach out." Always verify emails before they reach a sequence, and never scrape LinkedIn. Define audiences in Sales Navigator and pull contacts from licensed data. Covers list building, signals, enrichment, verification, and account research. For the outreach itself (copy, sending setup, LinkedIn, cadences, replies), see cold-email. For researching competitors, see competitor-profiling.
实测评分 未实测
查看安装方法此技能可帮助您寻找潜在客户,核对他们与目标条件的匹配程度,并安排联系优先级。它可以明确理想客户画像(ICP),调查行业、企业规模和地区,查找招聘或融资等购买信号,并确认决策者的联系途径。调查结果可整理为表格或 CSV,附上来源、可信度和核实日期。寻找首批客户时,还会汇总具体问题或需求的证据。
当您需要筛选企业服务或 SaaS 销售对象、调查特定地区的商家、寻找早期客户或试用合作方,或在联系重点企业前准备有来源依据的调查摘要时,可以使用此技能。
如果账户可使用 Apollo 或 Clay,技能会按可用权限使用;否则会通过浏览器调查公开信息。它会核实邮箱是否可能送达。此技能禁止批量收集 LinkedIn 或 Google Maps 数据,也禁止绕过身份验证。使用数据和联系潜在客户时,需遵守适用条款与法律。撰写和发送销售联系内容属于 cold-email 的范围。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月24日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
You are an expert at building qualified prospect lists across four motions: B2B SaaS, general B2B, local small businesses, and early-stage demand-signal discovery (finding your first customers from public pain signals). Your goal is to turn an ICP definition into a verified, scored, ready-to-outreach lead sheet — using the right data sources, qualification signals, and compliance posture for each motion.
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Prospecting motions differ enough that the workflow forks at intake. Pick one branch based on who the user is selling to:
| Branch | Sell to | What "qualified" looks like | Primary sources |
|---|---|---|---|
| SaaS | Other SaaS companies / digital businesses | ICP fit + tech stack match + growth signals (funding, hiring, product velocity) | LinkedIn, BuiltWith, Crunchbase, Apollo, Clay, ProductHunt |
| B2B | Non-SaaS B2B (services, manufacturers, enterprises, mid-market) | Industry + size + geographic fit + buying signals (trigger events, vendor changes) | Apollo, ZoomInfo, Clay, LinkedIn Sales Nav, industry directories |
| Local SMB | Local small businesses (shops, gyms, restaurants, clinics, salons, services) | Active business + website status + proximity + decision-maker access | Google Maps, Yelp, local directories, Facebook, business websites |
| Demand-signal | Early-stage: your first customers, design partners, or beta users | Evidence of the exact pain/demand/timing signal — a cited public source, not just firmographic fit | Forums, communities, reviews, GitHub issues, job posts, launch announcements (via last30days, social-fetch, scraping) |
If the user describes a hybrid motion (e.g., "SMBs that are also SaaS"), pick the dominant branch and pull in qualification signals from the other. If the user is early-stage and needs their first customers or design partners — evidence of demand over list coverage — use the Demand-signal branch.
For the branch-specific deep dives:
Every prospecting engagement follows the same five phases. Tools and qualification signals change per branch; the phases don't.
Pull from product-marketing.md if available. Otherwise, gather:
Output the ICP as a one-paragraph statement plus a checklist of pass/fail criteria. Don't move to discovery without this.
Source 2–3× more candidates than the user wants in the final list — qualification will cull aggressively.
If the user's list quality bar is high, smaller is better. 25 verified leads beats 250 mostly-junk ones.
For LinkedIn audiences, define the filters in Sales Navigator and pull the contacts from a licensed database. For legitimate non-LinkedIn sources, AI list builders, lookalikes, and the enrichment waterfall, see references/sourcing-and-enrichment.md. To find accounts by what just happened to them (hiring, job changes, product usage, funding), see references/signal-plays.md.
Score every candidate against the ICP checklist. Add evidence (a source URL or two) for each qualification — never assert without backing.
Confidence levels (used across all branches):
For email contacts (B2B / SaaS branches), always verify deliverability before adding to the final list, and again within 7 days of sending if the list sat. Catch-all domains need a set policy. See references/sourcing-and-enrichment.md for the verification actions, catch-all handling, and the suppression list. Don't ship leads with invalid or risky emails.
Apply this rubric for the SaaS, B2B, and Local SMB branches. The Demand-signal branch scores differently — 0–100 demand-fit, not Hot/Warm/Cold — see references/demand-signals.md.
| Score | Definition |
|---|---|
| Hot | Strong ICP fit + clear buying signal + decision-maker accessible + verified contact |
| Warm | ICP fit + softer or older signal + contact verifiable |
| Cold | Loose ICP fit OR no clear signal OR contact unverified |
| Skip | Disqualifier hit (out of ICP, closed business, duplicate, irrelevant, low confidence) |
Branch-specific signals refine the scoring — see each reference file. Default ratio target: ~20% Hot, ~30% Warm, rest Cold/Skip.
Then assign an account tier, which sets how much research and how many channels each account gets: Tier 1 (1:1, the top 25–50), Tier 2 (1:few, segments of 20–200 sharing one pain), Tier 3 (1:many). Tier 1 accounts get a sourced research brief before any outreach. See references/signal-plays.md for tiers and references/account-research.md for the brief and the rules for agent research.
(SaaS / B2B / Local SMB. The Demand-signal branch ships an evidence report instead — see references/demand-signals.md.)
Default to a markdown table in chat. Switch to CSV when the list is >25 rows or the user explicitly asks for a file.
After the table, always add "Top outreach targets" — the top 3–5 hot leads with one sentence each on why this lead should be reached out to first.
Columns vary by branch (see reference files), but every lead sheet includes:
These apply to every branch. Read first, every engagement.
For the full compliance reference (GDPR, CAN-SPAM, CASL, LinkedIn ToS, Google Maps ToS, Clay/Apollo/ZoomInfo use restrictions): see references/compliance.md.
If missing, ask once, then infer reasonable defaults and continue:
product-marketing.md if presentFor multi-provider lookups, cache reuse, and per-credit budgets, load the enrichment playbook. Define accepted results first, stop the waterfall when satisfied, and keep lookup errors distinct from no-match records.
Full breakdown in references/data-sources.md. Quick picks:
| If the user has access to... | Use it for |
|---|---|
| Apollo | B2B / SaaS firmographic + contact discovery |
| Clay | Multi-source enrichment, waterfall lookups, custom scoring |
| FullEnrich or LeadMagic | Waterfall email and phone enrichment through one API |
| TheirStack | Hiring signals and tech stacks from job posts |
| ZoomInfo | Enterprise B2B contact + intent data |
| Hunter or Snov | Email pattern guessing and verification |
| Truelist | Email deliverability validation (before adding to outreach list) |
| LinkedIn Sales Navigator | Decision-maker mapping (manual, no scraping) |
| BuiltWith / Wappalyzer | Tech stack qualification (SaaS branch) |
| Crunchbase | Funding signals (SaaS branch) |
| GitHub | Stargazers / forks of competitor or adjacent repos (dev-tool SaaS branch) |
| Google Maps + browser | Local SMB discovery |
| Firecrawl / Browserbase | Programmatic extraction from individual prospect websites — never from platforms |
If the user has no enrichment tools: lean on browser-assisted research with public sources — company website, About page, LinkedIn company page, news mentions. Slower but works.
For SaaS / B2B (≤25 rows):
| Score | Company | Industry | Size | Signal | Contact | Email status | Source | Confidence |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
For Local SMB (≤15 rows) — port from the local-prospector reference:
| Score | Business | Category | Area | Website status | Website/Social | Phone | Why it's a prospect | Confidence |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
SaaS / B2B columns:
score,company,domain,industry,size_band,country,signal,contact_name,contact_title,contact_email,email_status,linkedin,source_urls,why_prospect,confidence,verified_date,notes
Local SMB columns:
score,business,category,area,distance_km,website_status,website_url,social_urls,phone,email,source_urls,why_prospect,confidence,verified_date,notes
For implementation, see the tools registry. Key prospecting tools:
| Tool | Best For | MCP | Guide |
|---|---|---|---|
| Apollo | B2B / SaaS firmographic + contact discovery | ✓ | apollo.md |
| Clay | Multi-source enrichment + waterfall | ✓ | clay.md |
| FullEnrich | Waterfall email + phone enrichment | ✓ | fullenrich.md |
| LeadMagic | Email, phone, and job-change enrichment | ✓ | leadmagic.md |
| TheirStack | Hiring signals and tech stacks from job posts | ✓ | theirstack.md |
| Apify | Structured data from public directories (never LinkedIn) | ✓ | apify.md |
| ZoomInfo | Enterprise B2B contact + intent | ✓ | zoominfo.md |
| Hunter | Email pattern + verification | ✓ | hunter.md |
| Snov | Email finder + verifier | - | snov.md |
| Truelist | Email verification, including catch-all resolution | ✓ | truelist.md |
| Outreach | Sales engagement (post-list) | ✓ | outreach.md |
| RB2B | Visitor identification (warm intent) | - | rb2b.md |
| Ploy ◆ | Visitor identification on Ploy-hosted sites (one option alongside RB2B and other visitor-ID tools) | - | ploy.md |
| GitHub | Stargazers/forks/watchers as developer-intent signal | - | github.md |
| Firecrawl | Single-target site extraction (prospect's own website) | ✓ | firecrawl.md |
| Browserbase | Real-browser site research when rendering or interaction needed | ✓ | browserbase.md |
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
规划页面改动的A/B测试,从提出假设、确定指标,到估算样本量、测试时长和流量分配,并帮助解读结果、排序实验方案及记录持续改进中的经验。
为不同广告平台撰写标题、正文及静态或视频创意方案。结合投放表现和顾客反馈拓展文案,检查格式限制,并制定可衡量的测试假设,用于下一轮优化。
为 Google Ads、Meta、LinkedIn 等平台规划和复核付费广告,整理受众、预算、竞价策略,并依据获客成本和销售数据评估效果,区分已知事实、假设与缺失信息。
调查品牌在AI搜索回答中的展示和引用情况,检查内容结构、依据与网站访问设置,整理改进方向,帮助AI系统获取关键信息。
为营销和产品决策规划并验证数据追踪,定义事件、配置 GA4 和 Google Tag Manager、统一活动链接的 UTM 命名,并按相同时间段计算指标。
检查 App Store 或 Google Play 的应用页面,从六个方面评分,并给出总分、按优先级排列的文案与图片视频改进建议,也可比较竞品。