Your First Okki-Go Prospecting Workflow: A 7-Step Checklist (With the Cost Math)

Who this checklist is for

This is for a B2B sales team that has just picked up okki-go — or is about to — and needs to get from "we bought the tool" to "we booked meetings with people who actually match our ICP." Seven steps. No theory.

It's not for teams sitting on 50,000 unqualified contacts hoping automation will sort it out. That's a different problem, and a much more expensive one.

Quick disclaimer on my angle: I'm the person who signs the invoice, not the person who runs the sequences. I've managed our go-to-market tooling budget ($140,000 annually, give or take a few thousand) for four years, negotiated with 20+ vendors, and logged every renewal in our cost tracker. So what follows is the workflow that survived procurement — which means every step has a number attached to it, not just a "best practice."

Seven steps. About 40 minutes of setup work if you're focused. The expensive mistakes happen in steps 2 and 4.

Step 1 — Write down what "qualified" means before you touch a list

Not a mission statement. A filter.

Open a doc and answer four questions: (a) what industries are in, (b) what company size range, (c) what tech or hiring signals matter, (d) which job functions we're actually talking to this quarter.

Checkpoint: hand three random contacts to a teammate and ask them to mark qualified or not. If they hesitate, your definition is still too loose. Tighten it and re-test.

Most teams skip this step. It's the one step where being wrong costs nothing except 20 minutes — versus being wrong later, which costs you a month of sending volume and the deliverability hit that comes with it.

Step 2 — Price the workflow as a unit cost, not a subscription fee

Here's the thing: the subscription line on the invoice is rarely the biggest number. When I audited our 2023 spend, roughly 34% of our "prospecting budget" was sitting in line items nobody had assigned to the prospecting budget — verification credits overages, a second data tool we kept "just in case," and about 9 hours a week of a RevOps contractor manually de-duping.

So build the unit-cost sheet before you commit. For each of the following, put a number next to it:

• Seat / platform cost — monthly, annualized
• Enrichment credits — waterfall enrichment bills per successful match, not per attempt
• Verification credits — separate line, usually
• Sending infrastructure — domains, mailboxes, warmup
• Human review time — hours × loaded hourly rate
• Rework — the % of contacts that get bounced, wrong-fit, or need re-verification after 30 days

Then divide total monthly cost by booked meetings. That's your cost-per-meeting. Track it from day one.

I went back and forth between bundling everything into one okki-go tier and running a second, cheaper enrichment tool alongside it for two weeks. Bundling offered a single invoice and one support channel; the second tool offered 15–20% savings on enrichment credits. I ultimately chose the bundle because the reconciliation time alone was eating the savings. That said, we only send into two verticals — if you're running five, the math may flip.

Step 3 — Cut the ICP down to one slice for the first 30 days

The temptation is to launch broadly and let the data tell you where the wins are. Resist it. You'll burn your best domains on the worst-fit contacts.

Pick one: one industry, one company-size band, one buyer persona. Run it for 30 days. Then expand.

Why this matters for cost specifically: waterfall enrichment and email verification both charge per record. If 70% of your first list is out-of-ICP, you're paying full price for data you'll delete.

Checkpoint before you load the list: does every contact in it pass all four filters from Step 1? If not, cut it. Yes, actually cut it.

Step 4 — Enrichment and verification are two different jobs. Do both.

This is the step people conflate, and it's where the money leaks.

Enrichment is about finding the right person and filling in the fields your sequences need — title, company, tech stack, hiring signals, and so on. Waterfall enrichment means running a record through multiple data sources in sequence, stopping when you get a hit. It costs more per record than single-source enrichment, but the match rate is meaningfully higher, which usually offsets the price. Run the math on your own data before assuming either way.

Verification is about asking one question: will this address accept mail? A decent verification pass checks, at minimum:

1. Syntax — is it a well-formed address per the addressing rules in RFC 5322?
2. Domain and MX records — does the domain have mail exchangers at all?
3. SMTP handshake — the verification server opens a connection and issues a RCPT TO command, per the SMTP spec in RFC 5321, to see how the receiving server responds.
4. Catch-all and role-account detection — domains that accept everything look "valid" but often bounce or land in a black hole.

So, how can a B2B sales team verify email at any reasonable scale? Practically: run the list through verification after enrichment and before sending, then re-verify anything older than 30–45 days. Job changes and domain migrations break addresses constantly.

One thing I want to be blunt about: no verification service I've tested returns 100% accuracy. Ours hovers in a range, and catch-all domains are the unreliable part. Anyone promising perfect accuracy is either measuring differently or guessing. Budget for a bounce rate. Then monitor it.

Rough benchmark from our own logs: verified lists still bounced at low single-digit percentages on catch-all-heavy segments, and lower elsewhere. That's the number you plan around — not zero.

Step 5 — Sequence LinkedIn outreach and email as one motion, not two

Running LinkedIn and email as separate campaigns is the single most common waste I see. You pay for the same contact twice and the buyer sees two unrelated pitches.

A workable default cadence, human-in-the-loop:

• Day 1: email #1 — short, specific to a signal you enriched on
• Day 3: LinkedIn connection request — no pitch, reference the email topic lightly if it fits naturally
• Day 6-7: email #2 — different angle, same ICP, value-first
• Day 10: LinkedIn message — only if connected
• Day 14: email #3 — soft close

Human-in-the-loop means a real person reviews replies daily and takes over the moment someone engages. That's non-negotiable. Fully automated sequences without a human reading the responses destroy the domain faster than any list-quality problem.

Checkpoint: if a rep can't explain why a specific contact got the specific message they got, the personalization layer is theater.

Step 6 — Run a 250-contact pilot before you scale

I have mixed feelings about pilot sizes. On one hand, 250 is statistically thin — you can't draw confident conclusions from it. On the other, it's the cheapest way to catch a broken workflow before it touches your primary domain.

Reconcile it this way: use the pilot to check mechanics, not to declare a winner. Are the enriched fields accurate? Is the bounce rate sane? Are replies getting routed to the right human? If those four things pass, scale to 1,000. Then judge performance.

If the pilot fails mechanical checks, fix them. Do not scale and hope. I've made that exact mistake, and it cost us two weeks of sending volume we never fully recovered on that domain.

Step 7 — Review cost-per-meeting weekly, not monthly

Monthly is too slow. A bad segment can eat three weeks of budget before you notice.

Five minutes every Friday. Pull four numbers:

• Contacts enriched
• Contacts verified
• Contacts actually sent to
• Meetings booked

Divide monthly spend by the last number. Write it down. Set a ceiling now — the number you're not willing to exceed — so you're making the stop/go call against a pre-agreed line instead of in the moment, when sunk-cost thinking kicks in.

The week-over-week movement usually tells you more than the absolute number. If cost-per-meeting is rising while volume is flat, something upstream broke — usually enrichment quality, sometimes sender reputation. Go back to Step 4.

What trips teams up

Three things I'd flag, based on watching this go sideways twice now:

Sending before verification is finished. Ever. Not once, not "just this segment." The cost isn't the bounce itself, it's the reputational damage to the domain that lingers for months.

Judging a channel after 300 contacts. Small samples produce noise, and the noise usually looks like failure. Give a slice a real test before pulling it.

Skipping the small pilot because you're confident. Small volumes deserve the same rigor as big ones — 250 records tested properly beats 5,000 records guessed at. Small doesn't mean unimportant; it means cheap to learn from.

One last note to myself, because I keep relearning it: re-verify lists before every quarterly re-engagement. Contacts decay faster than anyone budgets for. I keep a reminder on the calendar (I really should automate that).

None of this is glamorous. Most of it is just deciding what qualified means and then refusing to budge on it. But it's the version that survived a procurement audit, and the version I'd run again.