# Pipeline Creation Analyst > Pipeline-Creation Analyst - Skill: `heath-gtm/pipeline-creation-analyst-2` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add heath-gtm/pipeline-creation-analyst-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/heath-gtm/pipeline-creation-analyst-2/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: heath-gtm (https://skillmd.com/u/heath-gtm) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/heath-gtm/pipeline-creation-analyst-2 --- # Pipeline-Creation Analyst ## What this does This skill answers the top-of-funnel coverage question: do you have enough at-bats to hit next quarter's number, and where are the gaps? It reads your CRM and a product-analytics tool, runs forward-looking coverage math per channel and per rep, ranks the hottest accounts to work, builds a daily prioritized account drop with a named owner per account, and surfaces the segments you are under-prospecting. It is built for the person who runs the pipeline review, not the person who works a single lead. ## What you'll need You do not need to connect anything to start. Bring your pipeline and the skill runs today. Connect the tools below and it pulls the data automatically and adds signals you cannot paste by hand. - Works today with: your open pipeline by channel and owner, plus the period target. Paste it or upload a CSV. - More powerful connected to a CRM: accounts, owners, channel attribution, and forecasted value, live. - More powerful connected to a product-analytics tool: powers the product channel and the new-user signal. - Sharper with an account-fit score and a hiring or firmographic signal source: better ranking and the "why now" line. ## How this runs at your connection level This skill is never reliant on a connector. It runs on the data you give it today and gets more powerful as you connect tools. It never invents a number it cannot see. A gap is a prompt, not a guess. - **Bring your data**: paste or upload your list (a deal export, a stage CSV). The skill runs the full analysis today on your real numbers. No connection required. - **Connect your tools**: the same skill pulls the data automatically and adds signals you cannot paste by hand (live activity, product usage, history). Same output, less effort, sharper. - **Just exploring**: no data yet? Get the framework, the exact fields it reads, and a worked example on sample data, so you can see the shape before you feed it. Every run ends with the one thing that would make the next run sharper, a field to add or a tool to connect. ## Customize this for yourself | Set this | What it is | Default / Example | |---|---|---| | CRM connector | System of record for accounts, owners, pipeline | A CRM | | Product-analytics connector | Source of product usage and active-user counts | A product-analytics tool | | Channel field | The account field that classifies channel | A "channel source" field; never the opportunity-level channel field | | Fit-score field | Account-level ICP fit score | An "account fit score" field, 0-100 | | Forecast / target field | Account-level forecasted value used in coverage math | A "forecasted value" field | | Channels | Your acquisition channels | Inbound, Outbound, Product | | Coverage targets | Per-channel pipeline target for the period | Set from your quota plan | | Activity sources | The signals that count as "engaged" | Calls, emails, tasks, product events, weighted by recency | | Daily drop size | Accounts surfaced per day | 10 | To use your own channels, replace the channel list with whatever your business runs. To use your own targets, set a per-channel pipeline number and the coverage math re-bases against it. ## The method 1. Classify every account by channel. Read the channel field and group accounts into your channels. 2. Run forward-looking coverage math per channel. Project the pipeline needed to hit the period target using win rate and cycle time, then compare projected against needed. Output a covered-percentage and a health flag (healthy, under, over) per channel. 3. Score account engagement velocity per rep. Count accounts engaged in a trailing window using your activity sources, weighted by recency, against book size. 4. Rank hot accounts. A composite of recent signal, account-fit score, and product engagement. 5. Detect the new-user signal. Flag accounts showing fresh active users as a distinct work item. 6. Surface under-prospected segments. Cross fit score against coverage. Name the gap as segment plus channel, with target and current percentages. 7. Build the daily drop. Top N prioritized accounts, each with a recommended owner and a one-line "why now." 8. Compute the coverage gap. Target, current projection, dollar gap, and the math to close it. End with the single point of leverage. ## Quality gates - Coverage math is forward-looking. It projects pipeline needed for the next period, not just open opps. - The daily drop names a recommended owner, with the account fact that justifies the routing. - Under-prospected surfacing is segment plus channel, with target and current percentages. - Fail loud on missing fields. Never invent a field name or definition. ## Output (example) ``` TEAM PIPELINE COVERAGE · Period target: 1.8M new revenue Per-channel coverage: INBOUND: 890K projected vs 900K needed · 99% covered · HEALTHY OUTBOUND: 310K projected vs 720K needed · 43% covered · UNDER PRODUCT: 202K projected vs 180K needed · 112% covered · OVER THE DAILY DROP, Monday 1. Account One Recent funding + sales hiring spike Owner: Rep A Fit 87 2. Account Two Cost-consolidation trigger Owner: Rep C Fit 73 3. Trial Account 3 active users, 1 power user Owner: Rep B Fit 68 Under-prospected segments: - Mid-market, Outbound: 22% of target, 8% current coverage - Existing accounts with new-user signups in last 30d: 12 ignored Coverage gap math: Needs 1.8M. Current projection 1.4M (gap 400K). To close: 18 more opps at avg 22K + 60% win rate = 30 more meetings. Leverage point: Rep C plus the outbound segment. ``` ## Where the numbers come from The coverage targets, win rate, cycle time, average deal size, and the daily-drop size are defaults. Re-tune them to your plan. The thresholds that drive healthy, under, over are defaults too. Set them where your team draws the line. The activity-source weighting is a starting point; adjust which signals count and how recency decays. ## Example chat **You:** Run coverage for the team against this quarter's $1.8M target. **Claude:** Here's where the gap actually is. ``` INBOUND: 890K projected vs 900K needed · 99% covered · HEALTHY OUTBOUND: 310K projected vs 720K needed · 43% covered · UNDER PRODUCT: 202K projected vs 180K needed · 112% covered · OVER ``` Outbound is the whole story here. Inbound and product are fine on their own, but averaged together they'd have hidden a 43% channel until it was too late to fix this quarter. **You:** Give me the daily drop for Rep C since they own outbound. **Claude:** ``` 1. Account One Recent funding + sales hiring spike Fit 87 2. Account Two Cost-consolidation trigger Fit 73 ``` Both carry a named reason, so Rep C isn't guessing why these two are first. Sharpener: connect a hiring or firmographic signal source so "why now" lines like these generate automatically instead of getting written by hand each morning. ## Go further The coverage math and the daily drop prove the gap and the priority. Here's the version that runs before the rep's first coffee. - **Push the drop into the inbox automatically.** A scheduled Claude task pulls the CRM and product-analytics data every morning and delivers each rep's top-10 by 7am. - **Reroute the moment a channel goes under.** Connect Slack so a channel crossing below its coverage threshold posts straight to the manager, instead of surfacing at the weekly review. - **Score the "why now" from real signal.** Connect a hiring or funding signal source so the daily drop's reason line writes itself from live data, not a rep's memory. Coverage math answers "do we have enough." The daily drop is what actually closes the gap. ## Make it yours Map your connectors and fields, set your channels and targets, and this becomes your coverage companion. Built by an operator. Customize it, break it, make it better.