Sales & CRM

How to qualify inbound leads as Educators, Coaches, and Course Creators

Sales & CRMFor Educators, Coaches, and Course Creators2 apps12 steps~24 min to set up

You spend 20 minutes per inquiry copy-pasting details from a ConvertKit form submission into a Notion doc, cross-checking whether they're already in your Stripe customer list, then manually scheduling a discovery call via Calendly. You have no single place that says: 'This person signed up for your free workshop, opened three emails, but hasn't bought.' Your 'qualification' process is a Gmail label called 'maybe' and a Google Sheet with columns like 'hot?' that you update inconsistently. You're missing real buyers because your follow-up is manual and slow, and you're spending time on tire-kickers who never planned to pay.

Build this on Starch → See the apps used

Sales & CRMFor Educators, Coaches, and Course Creators2 apps12 steps~24 min to set up

Outcome

What you'll set up

A CRM pre-loaded with your inbound leads from ConvertKit and Calendly, enriched with LinkedIn profile data and email engagement history, so you know who's worth a 30-minute call before you ever open a conversation.

An automated triage workflow that scores every new lead by behavior — workshop attendance, email opens, prior purchases — and surfaces the top five to follow up with each week.

A qualification checklist and email draft queue so you can respond to the right people within 24 hours without writing the same 'tell me about your situation' email from scratch every time.

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

CRM Email Agent

Data sources & config

Starch connects directly to Gmail (scheduled sync — messages, labels, thread history), Google Calendar (scheduled sync — events 12 months back), Calendly (scheduled sync — bookings and events), and Stripe (scheduled sync — charges, customers, subscriptions). ConvertKit is connected from Starch's integration catalog and queried live when the lead-scoring automation runs. LinkedIn enrichment runs through browser automation — no LinkedIn API needed.

Prompts to copy

Build me a CRM for qualifying inbound coaching leads. I need pipeline stages: New Inquiry, Attended Free Workshop, Discovery Call Scheduled, Proposal Sent, Enrolled, Not a Fit. Fields I care about: name, email, which program they're interested in (1:1 coaching / group cohort / self-paced course), how they found me, Stripe purchase history, last ConvertKit email open date, and a notes field for call prep. Pull in their LinkedIn profile where available.

Set up a weekly triage automation: every Monday at 8am, review leads in 'New Inquiry' and 'Attended Free Workshop' stages who haven't had a discovery call scheduled. Score them by engagement signals from my Gmail thread history and ConvertKit open data. Surface the top five I should contact this week, draft a personalized outreach email for each, and add a follow-up reminder if I don't reply within 48 hours.

Every time a new Calendly booking comes in tagged as a discovery call, automatically create a CRM record for that person if they don't already exist, pull their last three email interactions from Gmail, and generate a one-paragraph call prep summary I can read in 60 seconds.

Run these in Starch → or paste them into your favorite agent

Walkthrough

Step-by-step

1 Connect Gmail, Google Calendar, Calendly, and Stripe — Starch syncs each on a schedule so your lead and purchase data is always current without manual exports.

2 Connect ConvertKit from Starch's integration catalog; the agent queries it live when your qualification app needs open-rate and list-segment data for a specific contact.

3 Start from Starch's CRM app template, then describe your actual pipeline stages and fields in plain language — program interest, cohort vs. 1:1, referral source. Starch reshapes the schema to match how you actually sell, not how a generic B2B CRM thinks you should.

4 Tell Starch: 'Import leads who've registered for any of my free workshops in the last 90 days from ConvertKit, match them against Stripe customers, and flag anyone who's attended a workshop but never purchased.' This becomes your cold-start list.

5 Set up LinkedIn enrichment by browser automation: for any lead without a LinkedIn URL, Starch searches and attaches the profile automatically — no manual lookup.

6 Configure the weekly scoring automation using the prompt above. Each Monday it reads Calendly (has a discovery call been booked?), Gmail (have you exchanged at least two emails?), ConvertKit (did they open your last three campaign emails?), and Stripe (any prior purchase?) to rank your unconverted leads by warmth.

7 Wire the Email Agent to your Gmail; tell it: 'For any lead the scoring automation flags as top five this week, draft an outreach email referencing what program they showed interest in and the last thing we discussed.' Review and send in one click.

8 Set a follow-up trigger: if the outreach email gets no reply within 48 hours, Email Agent drafts a one-line nudge and reminds you to send it — so no warm lead quietly goes cold because you got busy recording a lesson.

9 When a discovery call is completed, update the CRM stage to 'Proposal Sent' and tell Starch: 'Draft a follow-up email summarizing what we discussed on the call and the next step.' The agent pulls the Calendly event notes and your Gmail thread to build the summary.

10 Set a monthly cleanup automation: 'Move anyone who's been in New Inquiry for 45 days with no email opens to Not a Fit and send them a low-pressure nurture sequence instead.' This keeps your active pipeline honest and small.

11 Build a simple dashboard showing: total new inquiries this month, conversion rate from workshop attendee to discovery call, conversion rate from discovery call to enrolled, and average days to close. Pull from the CRM stages directly.

12 Once the system is running, fork the CRM app to add a cohort field so you can qualify leads against specific launch windows — 'Is this person a fit for the April cohort or the July cohort?' — without rebuilding anything.

See this running on Starch

Connect your tools, describe what you want, and the agent builds it. Closed beta is free.

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Worked example

April 2026 cohort launch — 6-week qualification window

Sample numbers from a real run

Free workshop registrants (ConvertKit list segment)	184
Leads auto-imported into CRM with purchase history checked	184
Leads flagged as high-engagement (3+ email opens, attended workshop)	47
Discovery calls scheduled from top-five weekly batches	19
Enrolled in April cohort (avg. $1,800 per seat)	11
Revenue from qualified-lead workflow	19,800

Before Starch, you ran this qualification process across three browser tabs and a color-coded spreadsheet. This launch, Starch imported all 184 workshop registrants from ConvertKit, cross-referenced them against your Stripe history (22 were prior customers — flagged immediately as warm), and enriched 61 profiles with LinkedIn data through browser automation. The Monday scoring automation surfaced five leads each week across the six-week window. You sent 28 outreach emails — almost all drafted by Email Agent pulling context from Gmail threads and Calendly notes. You had 19 discovery calls, enrolled 11 people at $1,800 each, and spent roughly 40 minutes a week on the entire pipeline instead of the usual two hours of manual digging. Three people who would have fallen through the cracks — they'd attended the workshop but never replied to a broadcast email — were caught by the 45-day cleanup automation and converted during the second follow-up sequence.

Measurement

How you'll know it's working

Workshop-to-discovery-call conversion rate (benchmark: 10–15% for a warm audience)

Discovery-call-to-enrollment rate (benchmark: 40–60% if your call-screening is working)

Average days from first inquiry to enrollment decision

Percentage of enrolled students who had at least two email touchpoints before the call

Leads that went stale (in pipeline 45+ days with no activity) — should trend toward zero with automated cleanup

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

HubSpot Free CRM

Covers contacts and deals but requires significant manual setup to mirror your course-business pipeline stages; ConvertKit and Calendly integrations need Zapier glue, and there's no AI that reads your Gmail threads to prep you for a call.

Google Sheets + Zapier

Cheap and familiar, but you're maintaining the automation logic yourself; scoring leads by engagement signals across ConvertKit, Calendly, and Stripe requires zaps that break when any platform updates its schema.

Notion CRM template

Great for notes and pipeline visualization, but Notion doesn't query ConvertKit or draft follow-up emails — you're still doing the data-gathering and writing manually.

ConvertKit automations alone

Handles email sequences well but has no concept of a deal pipeline, no discovery-call scheduling context, and no way to flag a lead as 'attended workshop + no purchase' without building a complex tag logic that breaks on edge cases.

On Starch RECOMMENDED

One platform — crm, email agent all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

My course platform is Kajabi or Teachable — can Starch pull student data from there?

Kajabi and Teachable are reachable through Starch's integration catalog (queried live when your app needs the data) or via browser automation for platforms where a direct connector isn't available. You'd describe what you want — 'show me everyone who completed module 1 but hasn't booked a call' — and Starch works out how to get the data. If your platform has an API in the catalog, it queries that; if not, browser automation can pull it from your dashboard directly.

I use ConvertKit for email marketing — does Starch sync that, or is it live-query only?

ConvertKit connects from Starch's integration catalog and is queried live when your qualification automation runs — so open rates, tags, and list segments are always current, not a stale snapshot. If you need to cross-reference ConvertKit data against Stripe purchase history in the same query, Starch handles that in one step.

Will Starch actually understand my business — 1:1 coaching vs. group cohort vs. self-paced course are very different qualification criteria.

Yes — the CRM is schema-flexible by design. You describe your qualification criteria in plain language: 'For 1:1 coaching leads, I care about their budget and timeline. For group cohort leads, I care about which cohort date fits them. For self-paced, I mostly just need to confirm they have credit-card intent.' Starch builds separate fields, stage logic, and scoring rules for each program type. You're not adapting to a fixed template.

Is Starch SOC 2 certified? I have student payment data flowing through here.

Starch is not SOC 2 Type II certified today. If your organization requires SOC 2 certification before connecting a payments or student data source, that's a real constraint worth knowing upfront. For most solo coaches and small course businesses, this isn't a blocker, but it's worth factoring in if you're working with enterprise clients or handling sensitive protected data.

I'm worried about Gmail access — what does the OAuth screen look like to me?

Currently, the Gmail OAuth consent screen shows the name of the underlying verified connector rather than 'Starch.' It's a cosmetic issue — the connection is real and secure — but it can look unexpected on first setup. Starch is working on getting its own verified client name on the consent screen; that's on the roadmap.

I don't want to rebuild this every time I launch a new cohort. Can I reuse the qualification setup?

Yes. Once your CRM, scoring automation, and email drafts are configured, launching for a new cohort means updating the target dates and program name — not rebuilding from scratch. You can fork the app and tell Starch: 'This is now the July cohort version; update all the date references and the program name.' The underlying logic stays intact.