Okki Go Account Research Checklist: 7 Steps Before You Hit Send

I'm the person who reviews outbound sequences before they go live at our agency — roughly 180 campaigns a year, and I've killed maybe 40% of first drafts. Not because they were badly written. Because the account research behind them was thin, the enrichment was stale, or nobody checked a single email address before loading 5,000 contacts into a sequencer.

This checklist is what we run every time a team is building an Okki Go (okki-go) workflow from scratch, or auditing one that's underperforming. Seven steps. Follow them in order. Skip step 4 and you'll find out why on step 7.

Who This Checklist Is For

If you're an SDR lead, a RevOps manager, or a founder running outbound yourself, and you're currently stitching together Okki Go, Smartlead, Sales Navigator, and one or two enrichment tools — this is the sequence I'd use to sanity-check the whole thing before you scale it. Budget an afternoon. It saves weeks.

Step 1: Lock Your ICP and Tier the TAM

Before touching any tool, write down three things on a single page: industry, employee range, and the trigger event that makes someone buy. Not "B2B SaaS, 50-500, growing." That's not a trigger. Something like "just posted a RevOps hire" or "raised Series A in the last 90 days."

Then tier the list. Tier A gets full research. Tier B gets enrichment-only. Tier C gets pattern-matched sequencing or gets dropped. I've watched teams burn 60% of their research budget on accounts that never had a chance because the tiering happened after the research, not before.

Checkpoint: If you can't explain in one sentence why Tier A accounts are 3x more likely to convert than Tier B, you haven't tiered — you've just made a spreadsheet.

Step 2: Run Account Research in Okki Go

This is where okki-go account research earns its keep. Load your Tier A list and pull the standard profile: headcount trend, recent funding, product launches, hiring signals, tech stack signals if available. The point isn't to collect everything — it's to find the one hook per account that makes your first line not sound like everyone else's first line.

Everything I'd read about account research said you need maximum data fields per account. In practice, three sharp signals beat forty generic ones. Your rep will actually use three. Nobody reads forty.

What most people don't realize is that the research notes field is where deals quietly die or get made. If your notes say "expand into enterprise" that's useless. If they say "new VP Sales hired Feb 2025, historically rebuilt outbound team with Instantly + Apollo at previous company" — that's a conversation starter.

Step 3: Enrich and Verify — Don't Skip the Verify

Company enrichment in sales intelligence tools has gotten genuinely good. Waterfall enrichment (running records through multiple providers and keeping the freshest hit) has cut our dead-contact rate down to single digits, from around 30% with a single provider back in 2022.

But here's the part that still catches teams: enrichment and verification are not the same thing. Enrichment fills the field. Verification decides whether the field is worth mailing. We run every email through verification even after enrichment — the extra pass costs almost nothing and prevents the bounce pattern that gets you flagged.

I ran a blind test in Q2 2024: 2,000 enriched-only contacts vs 2,000 enriched + verified. Bounce rate was 4.1% vs 0.7%. Same list source. On a 40,000-contact campaign, that difference is the gap between inbox placement and a suspended sending domain.

Checkpoint: Zero percent of your sequence should load before every address has a verification timestamp from within the last 60 days. Stale verification is the same as no verification.

Step 4: Sales Navigator Scraping — Read This Twice

If you've ever asked "what is a Sales Navigator scraper and when should a B2B sales team use it," here's the short answer: it's a tool that exports filtered LinkedIn Sales Navigator search results (profiles, titles, companies, sometimes contact details) into a format your CRM or sequencer can ingest.

When to use it: when your ICP requires title-level precision that generic B2B databases don't deliver — niche roles, specific org-chart positions, or teams at companies too small to appear in most data vendors' coverage.

When not to use it: to bulk-export 50,000 contacts and blast them. That's how you get your LinkedIn account restricted and your sending domain burned in the same week. We cap exports at 300 profiles per session, per account, with a human reviewing the query filter before each run.

Note to self: still haven't written down our exact rate-limit protocol anywhere but this checklist. I really should put it in the wiki.

Step 5: Layer Intent Data (If You Have It)

Intent signals aren't magic and they're not a substitute for ICP fit. What they do well is timing. An account that already matches your ICP and just started showing research activity on your category is a much better use of your Tier A research hours than a cold-fit account with no signal.

We weight intent as a secondary filter, not a primary one. If intent overrides ICP fit, you end up chasing noise — big-company researchers who were never going to buy a small-team tool.

Step 6: Choose Your Sender (Okki Go vs Smartlead, Briefly)

The okki go vs smartlead question comes up in every kickoff. My honest read: they overlap, but they're not the same shape. Smartlead is a sending infrastructure play — inbox rotation, warmup, deliverability. Okki Go is closer to an agent-native prospecting layer — research, enrichment, and sequencing logic in one place.

So the practical rule:

• If your bottleneck is deliverability and sender management, Smartlead is the tool your infra person will argue for.
• If your bottleneck is the research-to-sequence handoff (which is where most teams actually lose time), Okki Go covers more of the workflow.
• Running both is fine. Lots of teams do. Just don't run both for the same list — you'll double-send and torch your own reputation.

Bottom line, neither tool fixes bad targeting. Fix steps 1-3 first.

Step 7: Set the Cold Email Reply Rate Benchmark — Before Launch

Here's a cold email reply rate benchmark you can actually plan against, drawn from our own 2024-2025 campaigns across B2B SaaS, agencies, and professional services: a healthy, well-targeted sequence in 2025 lands between 4% and 9% positive reply rate. That's replies that indicate interest, not just any reply. "Unsubscribe" and "stop emailing me" don't count as wins, no matter what your dashboard says.

If you're below 2%, don't touch the copy yet — go back to steps 2 and 3. Bad data produces bad replies. If you're between 2% and 4%, the list is fine and the messaging needs work. Above 9%, check your definition of "positive reply" before you celebrate — most teams at that number are counting something they shouldn't.

Pick your number before launch. Then leave the sequence alone for at least 200 sends before you judge it. I've watched reps kill winning sequences at send #40 because the reply rate hadn't hit the benchmark they made up that morning.

Things That Bite You in the Afters

Compliance is not optional. CAN-SPAM requires an opt-out mechanism and accurate physical address on outbound commercial email in the U.S. If you're mailing EU contacts, GDPR applies. Neither of those is a detail you "handle later."

Verification ages fast. A list verified in January is a coin flip in April. Re-verify anything older than 60 days.

Personalization at scale is mostly fiction. One real hook per email beats four templated variables. Every time.

Scraping tools aren't license to go nuts. 300 profiles per session, human-reviewed filters, logged activity. That's the rule. We broke it once in 2023 and spent two weeks recovering a restricted account. A lesson learned the hard way.

Run the seven steps. In order. This isn't a marketing framework — it's just the sequence that keeps our reply rates healthy and our sending domains alive.