Newcomer Path Builder
A personalized 3-step next-step path for every guest from a 1-minute intake — drafted by AI, sent by staff.
A personalized 3-step next-step path for every guest, generated from a 1-minute intake — drafted by AI, reviewed and sent by staff.
| Category | Operations |
| Church-health domain | Open the Front Door |
| Data-privacy tier | High — "where you're hurting" is a sensitive pastoral disclosure |
| Mastery-ladder target | Level 3 · Skills |
| Build stack | A short form + Make.com + Gmail + Claude API; logged to Planning Center |
The problem
A generic welcome card collects a name and triggers a one-size-fits-all form letter — exactly the assimilation gap Nieuwhof flags (about 70% of leaders lack an effective process). The research on retention points the other way: connection that is relevant and relational is what holds people. A small staff can't hand-craft a tailored next-step path for every guest, every week — so everyone gets the generic email, and the generic email is the leak.
What good looks like
The welcome card becomes a 1-minute form: life stage, what brought you, and (optionally) where you're hurting. On submit, an AI reads the answers against the church's real ministry catalog and drafts a warm, specific three-step path — e.g., DivorceCare group → coffee with a deacon → a low-pressure newcomer dinner — as a Gmail draft. Staff review, personalize, and send. The chosen path type is logged, and the church reports 90-day return rate by path type.
Honest framing: no published study proves AI-personalized paths beat human follow-up. The bet rests on the well-sourced finding that early, specific connection predicts retention (McIntosh & Arn; Gallup), applied at a scale a small staff cannot sustain manually. The AI scales the drafting; the human keeps the pastoral judgment.
Market scan
| Tool | Fit | Pricing (verify) |
|---|---|---|
| Text In Church | Templated, rules-based follow-up | $31–81/mo |
| Clearstream | Guest texting sequences | Credit-based |
| Mailchimp / CRM automations | Segment-based sequences | Varies |
| Subsplash | App + sequences | ~$300–600/mo loaded |
| Gloo | AI-assisted engagement | Unverified |
The gap: templated tools branch on checkboxes; none publicly reads a free-text pastoral disclosure ("going through a divorce, new to town") and composes a bespoke path. That generative, staff-reviewed draft is the open lane — and the human-in-the-loop design is the whole safety model.
Data privacy & security
This is a high-risk front-door build, because "where you're hurting" can be health, grief, marital, or financial disclosure. Treat it like confidential pastoral care:
- Explicit, plain-language consent on the form stating how the response is used and who sees it.
- Store responses in Planning Center with restricted field-level permissions — never a public sheet.
- Human-in-the-loop is mandatory: the AI only ever produces a Gmail draft. No automated sends, ever.
- Don't feed raw PII to consumer AI — use the Claude API under Commercial Terms and minimize what you send (you can omit the full legal name).
- Avoid logging the rawest disclosures in Make.com execution logs; provide an opt-out and a deletion path.
How to build it
- Build the intake form (Google Forms, Typeform, or Planning Center Forms) with a consent checkbox.
- Make.com watches for submissions.
- Make calls the Claude API with a tightly scoped prompt: "Given this life stage / motivation / need, propose a warm, pastoral 3-step path using only our real ministries [list]; do not promise counseling; flag anything needing urgent pastoral attention."
- Make creates a Gmail draft from the connections pastor — never auto-send.
- Staff reviews, edits, sends; Make logs the chosen path type to a Planning Center custom field.
- Weekly, compute 90-day return rate by path type (reuse the Guest-to-Member Funnel pipeline).
Rollout plan
- Q1: Replace the welcome card with the consented intake form. Draft paths manually for a month to learn the patterns.
- Q2: Turn on the AI-draft step with staff review; track path types.
- Q3: Compare 90-day return rates across path types; double down on what works.
Effort & cost
- Build: ~15–25 hours (prompt-tuning and the Gmail-draft step are the fiddly parts); ~5–15 min staff review per guest.
- Run: ~$20–30/mo (form tool + Make.com $12–21 + a few dollars of API) plus review time.
Sources
- Carey Nieuwhof — https://careynieuwhof.com/how-to-a-lose-first-time-guest-in-10-minutes-or-less/
- Friendship factor (McIntosh & Arn) — https://www.apostolic.edu/the-friendship-factor-2/
- Gallup — https://news.gallup.com/poll/16006/friendship-feeds-flock.aspx
- Make.com pricing — https://www.make.com/en/pricing
- Claude API data retention — https://platform.claude.com/docs/en/manage-claude/api-and-data-retention
Honesty flag: no study shows AI-personalized paths outperform human follow-up; the value case rests on scaling early, specific connection.