B2B Sales Prospecting Checklist: 7 Steps From Email Validation to ABM (and Where OKKI Go Fits)

Who this is for (and why 7 steps)

If you're about to add one more tool to your sales stack, stop for a minute. I review sales-tech purchases before they reach the client—roughly 200 items a year—and I've rejected around 28% of first deliveries in 2024 for the same reason: people buy tools before they've defined the process the tool is supposed to serve.

This checklist has 7 steps. Each one is a gate you should clear before you sign another contract. Nothing fancy. Just the questions I ask before approving a purchase.

Who it fits: RevOps leads owning an SDR team, outbound agency founders scaling past 5 seats, and marketing teams being asked to carry a sales quota on the side. Who it doesn't fit: teams already running a mature motion with plenty of internal data—you've probably internalized most of this. Skim it anyway. Some of the checkpoints are worth re-running once a quarter.

Step 1 — Define your ICP before you decide on ABM

What is account-based marketing and when should a B2B sales team use it? Short answer: ABM is picking a named list of accounts (50 to 500 is typical) and building outreach tailored to each one. It is not "send to everyone but pretend it's personalized." That's a different motion entirely.

ABM genuinely fits when:

• Your average contract value is high enough to justify 15+ minutes of research per account
• Your total addressable market is small enough that you can literally remember the names—say, a few hundred accounts
• Sales cycles run long (6+ months), so a touch point six weeks early doesn't read as spam

It does not fit when your ACV is $80 and your sales cycle is two weeks. That's overkill. Simple as that.

Before approving any tool, I want both numbers written down: target account count and average deal size. If nobody can say whether the list is 200 accounts or 20,000, no tool is going to fix that.

Step 2 — Nail down your data sources

Okay, this step is almost embarrassingly basic. But skipping it is what sank a $12,000 annual contract we signed in 2023.

Where do contacts actually come from? CRM exports, LinkedIn, scraping, intent data, a mix? Every source has its own failure mode:

• CRM data is stale and unverified—records untouched for six months rot like milk
• LinkedIn gives you titles but not always work emails
• Scraping gives you coverage but not validity

Checkpoint: Pull 50 random records from your primary source and hand-verify them. If more than 4 are wrong, that source needs cleaning before you plug anything into it.

Step 3 — Pick an email validation service (and accept it can't be 100% accurate)

This one matters. No email validation service is 100% accurate. Any vendor that puts that number in a contract either doesn't understand the problem or is betting you won't check.

As of 2025, mainstream validation services land around 92-97% accuracy depending on list quality. That's the reality. Plan around it.

What to check:

• How does it treat catch-all addresses? Some flag them all as "invalid," which is too aggressive—you'll throw away real leads
• Does it give reason codes, or just a yes/no? Reason codes let you spot which source is off before the rot spreads
• Does it re-validate? Emails decay at roughly 2-3% per month. One-time validation is a deliverability liability

In our stack, quarterly re-validation is a standing rule. No exceptions. Old data gets old—fast.

Step 4 — Identify website visitors, not just form fills

If you're still waiting for people to fill out forms, you're losing 98% of your site traffic. Identifying website visitors—matching anonymous sessions to companies (and sometimes people)—is where most serious lead generation now starts.

Three things to watch:

1. Match rate. Company-level match typically lands between 20-40% depending on traffic mix. Person-level is lower. Marketing decks love to cite 60%+, but I haven't seen that in practice.
2. Compliance. Visitor identification touches personal data. You need a legitimate-interest argument that holds up under GDPR/CCPA.
3. Workflow integration. Identifying a visitor and then not following up is just expensive analytics. Wire the trigger into an SDR queue, or don't bother.

Step 5 — Plan your enrichment stack as a waterfall, not a snapshot

Single-source enrichment was fine in 2021. Not anymore. Coverage data is brutal these days: no single vendor covers more than 65-70% of B2B contacts with everything you actually need—email, phone, title, headcount, tech stack.

A waterfall means querying multiple vendors in sequence, stopping once a field is filled, and spending budget only on gaps that remain. In practice this gets you 15-25% higher coverage than any one vendor alone. It's worth the extra plumbing.

Checkpoint: Compute single-source vs. waterfall coverage on your first 1,000 records. If the gap is under 10%, skip the complexity. If it's over 20%, the waterfall justifies itself quickly.

Step 6 — Is OKKI Go a sales prospecting skill?

This is the question I get most often, and honestly, the answer depends on how you define "skill."

OKKI Go isn't a skill. It's an agent-native platform—it orchestrates data, verification, and outreach rather than doing those jobs itself. The skill is stringing an email validation service, identify website visitors, and ABM workflows together into one motion. The tool is the carrier, not the skill. Get those backwards and no purchase order is going to save you.

The honest question when you evaluate okki go cost is: what is it actually replacing? Usually three or four point tools, plus the person-hours to run them. If okki-go replaces two tools in your stack, the monthly invoice may look higher but total cost of ownership (i.e., not just the license fee but every hour someone spends stitching things together) lands lower. But only if you actually retire the tools you replaced. I've watched half a dozen teams bolt on a new platform and cancel nothing. That's how stacks turn into landfill.

For context: we run OKKI Go for outbound and lead routing. It works for us because our ICP is fairly stable and our volume—around 40,000 unique contacts a year—is big enough that the tool-consolidation math works. This worked for us, but our situation was a mid-market B2B company with a stable, English-speaking ICP. If you're prospecting in a highly niche vertical where the list shifts weekly, the calculus might be different. Your mileage may vary.

Step 7 — Build human-in-the-loop outreach

AI can draft, sequence, and send. AI should not, and I'd argue cannot, fire campaigns into the wild without a human reviewing at least a sampled slice. Not at scale.

The math here is unforgiving. A damaged sending domain takes 4-6 weeks to recover reputation. That's a long time for your pipeline to wait on a mistake nobody caught. I watched a misconfigured automation in 2023 blow up a client's domain reputation in a single weekend—the mental note to myself was: never approve a sequence with no human in the loop, period.

Checkpoint: Every automated sequence has a named human owner and a daily 15-minute review window. That 15 minutes has saved our clients real money.

Notes and common mistakes

Things I look at hard before signing off:

• Don't buy a tool you won't use within 90 days. That's how shelfware starts
• Validation accuracy isn't the same as inbox placement. A 92%-clean list still lands in spam if domain warm-up was rushed
• ABM is not a tool feature. It's a motion. Tools amplify whatever motion you already have—including a bad one
• "Agent-native" doesn't mean "autopilot." Someone still needs to be sitting in the driver's seat

Bottom line: audit your stack every quarter. The compounding returns from process efficiency are real, but only if the architecture is right. Define the motion, then buy the tool. Otherwise, you're just adding one more thing to maintain (and yes, I've made that mistake more than once).