A 7-Step Checklist for Buying Sales Prospecting Tools (okki-go, Sales Dialer, AI Email Writer, Email Search)

Who this checklist is for

If you're a B2B sales team evaluating prospecting tools—okki-go, a sales dialer, an AI email writer, or an email search tool—this is the checklist. Seven steps. Run them in order. Skipping to step three before you've done step one is how teams end up paying for twelve months of software nobody touches.

Quick context on who's writing this: I handle tool procurement for a 120-person B2B SaaS company. Roughly $400K in annual software spend across 11 vendors. I took over sales-ops purchasing in 2023 and have misjudged at least two prospecting tools since then. Here's what I'd do differently.

Step 1: Define what "prospecting" actually means for your team

Most people skip this. They jump straight to booking demos.

Figure out where your bottleneck is. Because prospecting in B2B sales breaks into four distinct jobs:

• Finding the right accounts (email search, list building, intent data)
• Reaching them (sales dialer, LinkedIn, SMS)
• Writing the message (manual, or an AI email writer)
• Automating the follow-up (sequencing)

So what is email search and when should a B2B sales team use it? Plain version: it's the practice of finding and verifying a person's work email before you reach out. You should use it when you're running cold outbound, when you're following up on a high-intent lead, or when you just can't afford bounces and a damaged domain reputation.

If you're only following up on inbound leads that came with a business email already attached, you probably don't need email search. If you're building a cold list of a few hundred accounts from scratch, you absolutely do.

Not ideal to admit, but I bought a list-building tool once when my actual bottleneck was list-scoring. Six months of shelf time. A lesson learned the hard way.

Step 2: Map your current stack before you buy anything new

Boring step. Saves thousands.

Open your SaaS admin panel. Build a table: what you're paying for, actual seat usage, renewal date, and who'd genuinely push back if you cancelled it. I ran this last spring and found two seats nobody had logged into since onboarding, plus a sales dialer that overlapped about 40% with our contact-data platform.

We cut one. Kept the other. Switched the dialer.

Step 3: Split tools by the four jobs, not by vendor brand

The same vendor can show up twice on your list. That's fine. What's not fine is evaluating by logo.

An AI email writer plugged into your sequencer doesn't solve your contact-data problem. A sales dialer makes reps faster on the phone but does nothing for email reach. Score each tool on the job it does—not the category the vendor's marketing team invented for it.

Decide by function first. Consolidate vendors last.

Step 4: Run okki-go and its competitors on the same list

This is where you bring in okki-go and any other candidates.

Not a demo. Your data.

Take a real segment—say, the last 50 accounts you worked manually. Push them through each tool. Track:

• How many contacts each platform found
• How many of those were actually reachable (not "valid"—reachable)
• How long it took to tag, enrich, and add custom fields
• How clean the export was

The numbers once said go with the cheaper option—maybe 15% less per record, similar feature list. My gut said stick with the incumbent. Went with my gut. Two service outages later on the cheaper platform, and one of my peers was caught mid-campaign during one of them. Turns out that "slow to reply during the trial" wasn't a fluke. It was a preview.

If you want public okki go prospecting examples, the framing they usually publish centers on waterfall enrichment combined with intent signals—routing each contact through multiple data sources and ranking by best hit. Reasonable design. Still needs to be tested against your 50 accounts, not their case study.

On okki go competitors—the field splits roughly into three camps: pure contact-data vendors, engagement-and-sequencing platforms, and full-stack prospecting suites. Okki-go currently sits closest to the third camp. That positioning matters more than any individual feature because it changes what else you can turn off.

Step 5: Score on total cost, not sticker price

This is where most teams get burned.

Sticker price is one line. The rest of the invoice looks like this:

• Per-seat fees
• Credit-based or verification-based metering
• Time to build integrations
• Time to train reps on a new workflow
• Cost of re-doing lists when you discover A works but B doesn't
• The invisible cost of reps abandoning the tool because the data quality killed their confidence

That last line is usually the decider.

Do the math once, in a spreadsheet, with real estimates. Then compare the two totals side by side. When I ran Q1 vs Q2 quotes this way—same requirement, different specs—the cheaper-looking option landed around 22% more expensive once I added integration time and one expected redo.

Step 6: Pilot with real reps on a real segment—not a test list

This is the step most people skip. They pilot on a one-off test list, the numbers look shiny, they sign, and then usage collapses in week three.

Here's why. Test lists are clean. They're prepped. Real rep lists are messy, ad-hoc, and full of weird custom fields. An AI email writer that produces beautiful output on clean data will produce polite garbage the moment it's fed a half-enriched CRM record.

Better approach: give two reps a real segment of 30 accounts each, for 30 days. Compare reply rates—but also compare the read. Do the emails sound human? Or do they sound like a template with a first name pasted in?

Only reply rate is a trap. If your brand voice is distinctive, a stiff, generic AI-drafted email can do more damage than the reply it earned. At least, that's been my experience in a service-brand context.

(Should mention: we did this pilot with two of our most skeptical reps. They killed two tools faster than any spreadsheet would have.)

Step 7: Set review triggers before you sign

Before you put ink on the order form, write down the exit conditions. Example:

• If activation is under 60% at day 30, we re-evaluate
• If error rate stays above 5% at day 60, we switch
• If the sales team hasn't adopted it by day 90, it gets cut

Put them in the PO notes. This protects against three things: sunk-cost drift, vendor inertia, and the slow death of "we already pay for it, let's give it another quarter" stretching into two years.

Cautions and common mistakes

A few things worth writing down:

• Don't run an okki-go comparison off a demo. Demos are choreographed.
• Don't judge an AI email writer from a 20-email A/B test. You need at least 200 sends before the signal holds.
• Don't buy a sales dialer because a sales leader says it's faster. Ask the rep who actually has to make the calls.
• Don't sign a prospecting contract in Q4. Nobody pilots properly in December, and then you're locked in for Q1.

And one red flag worth naming: any tool that promises 100% verified emails or guaranteed reply rates is quietly pushing the risk onto you. Email data has a decay rate. The vendors who are honest about that are the ones you can actually work with.

Bottom line—every step on this list is designed to force you to test your own assumptions with your own data, without a vendor in the room. It's slower. It's the least expensive thing you'll do all year.