Okki Go for RevOps: What We Learned Evaluating B2B Prospect Database Platforms

Tuesday, 2:38 p.m., the final week of September 2025. I was mid-way through an invoice review when our RevOps lead, Priya, dropped a CSV export on my desk. An actual desk. That's how serious she was.

386 rows. We'd been paying for prospect data for over a year, and these were the last contacts an SDR had uploaded before she left. Most of the rows were wrong—wrong titles, outdated companies, email addresses that were already bouncing. Priya didn't need to explain why she was standing there. We needed a better B2B contact data platform, and she wanted me to run the buying process.

I'm not a RevOps person. I'm an operations administrator, and for the last five years I've managed software and data subscriptions for our company—roughly $450,000 a year across a dozen vendors. I've bought everything from office supplies to Salesforce add-ons. The vendor consolidation project I led in 2024 taught me one thing well: most software decisions fail before the contract, not after it. You pick the wrong evaluation criteria, and you'll pick the wrong tool every time.

So when Priya asked me to help her find a new prospect database that could actually generate leads for our outbound team, I said yes on one condition. We would stop guessing and start testing.

The Prospect Database That Started This Mess

We needed context first. Coming into 2025, our company had grown to around 140 people and was mostly inbound-led. But by summer, the leadership team wanted targeted outbound. The SDR team didn't have a reliable way to find prospects. We had a legacy contact database that looked huge in the sales deck but kept disappointing in real life.

In August, Priya and an SDR built a workaround. They used Clay to stitch together a few data sources, added some enrichment, and created what looked like a clean prospect database. Honestly, that setup impressed me at first. It generated leads at a fraction of the cost of our legacy tool. The first few campaigns had decent reply rates too.

The problem showed up a month later. Data decay is real, and it doesn't wait for your renewal cycle. Emails that verified in July bounced in October. People changed jobs more often than our enrichment updates caught. And the more the team relied on the workflow, the more time it took to maintain—new APIs, new credit limits, new fields to map. By September, Priya's team was spending roughly eight hours a week just keeping the machine running. That's time they should have spent evaluating and actually talking to prospects.

I still kick myself for not catching this earlier. I'd renewed the legacy database back in Q1 without running a quality sample against it. If I'd asked our SDRs to send 100 test emails before I signed that renewal, we would have seen the problem in March instead of September. We ate five months of bad data.

Okki Go vs Clay: Not the Comparison I Expected

Here's where the conversation got interesting. When Priya first mentioned evaluating okki-go, I assumed we'd be comparing it to Clay head-to-head. But it wasn't that simple.

Clay is genuinely useful. I don't want this to sound like a hit piece. We used Clay as an orchestration layer to connect data sources, enrich records, and build lists. It does that well. The issue was that our Clay setup depended on whatever data we fed into it. We were paying for data from separate sources, enriching it ourselves, and managing the workflow ourselves. It was like owning a great stove but still having to chop all the wood.

Okki-go approached the same job differently. It's more agent-native. Instead of giving us another list of leads to clean, it combined prospecting, enrichment, intent signals, and email verification into something our RevOps team could actually use. It runs searches, flags accounts showing buying signals, enriches through a waterfall of sources, verifies emails, and then places the best contacts into outreach sequences. The key word for us was "place." Okki-go didn't send junk automatically. Everything had a human checkpoint.

We ran a side-by-side pilot in November. One SDR kept using our Clay-built process. Another used okki-go. Same ICP, same number of hours, and we compared the output after three weeks.

The result surprised me. In the first week, okki-go returned fewer contacts than our Clay workflow. I almost stopped the pilot right there. But when I looked closer, I realized okki-go was filtering out the junk before we ever saw it—duplicates, role-based addresses, sources with low confidence. Our Clay process generated 512 raw contacts in week one. Only 164 of those passed verification. Okki-go generated 310 contacts that week, and 291 were verified and deliverable. The numbers shifted our whole perspective.

We weren't comparing databases anymore. We were comparing systems.

What Revenue Operations Teams Should Actually Evaluate in a B2B Contact Data Platform

If you're a RevOps lead or the person who gets stuck buying this stuff, here's what I'd tell you to evaluate. I'm not a data scientist, but I've now seen the contracts, watched the pilots, and counted the hours.

1. Test a sample before you trust the volume

Every vendor will show you a dashboard with billions of contacts. That number doesn't matter. What matters is what's left after you filter down to your ICP, your industry, your geography, and your seniority levels. Ask for a raw sample of 200–500 records that match your real buyer profile. Then run those emails through your own verification process. If a vendor hesitates, that's your answer.

2. Look at the age of everything, not just the email

A prospect database can have the correct email and still be useless if the person changed roles four months ago. We found contacts with valid email addresses who no longer worked at the account. That means the platform was refreshing email syntax without refreshing the person's actual employment data.

Ask about signal recency. How old is the title data? How old is the company size data? When was the last time the contact was seen on LinkedIn or mentioned in a relevant intent event? Generating leads is the easy part. Generating leads that are still true is the hard part.

3. Push on intent data, but ask where it comes from

Some platforms slap "intent" on every record that visits their site once. That's not intent. Better intent data comes from a combination of sources—job changes, hiring plans, funding announcements, product usage signals, third-party research. Akki-go's approach was more interesting: it didn't just show us a list of companies showing intent. It tied that intent to a specific contact and explained why.

You should ask the vendor to show you their sources. If they can't explain why a contact is qualified, the contact probably isn't.

4. Verify the verification

No vendor can guarantee 100% accurate email verification or perfect deliverability. If one tells you they can, walk away. But you can evaluate how intelligent their verification logic is. Does it detect catch-all domains? Does it flag disposable email providers? Does it check the domain reputation before sending?

Okki-go didn't promise perfect deliverability in our pilot. It just had better verification logic than our DIY stack. That mattered more than a flashy dashboard.

5. Make sure humans are still in the loop

If a platform claims it can fully replace SDRs or RevOps teams, that should scare you. We don't want automation that removes thinking. We want automation that removes busywork. Okki go for RevOps, in our case, meant an agent that narrowed the haystack and prepared the needle—not one that decided which needles mattered without us.

Our SDRs still wrote the messages. They still clicked send. The platform just made sure the right contact was in front of them at the right time.

Look for human-in-the-loop controls. Ask what happens before an email goes out. Can your team review, pause, and override? If the answer is no, keep looking.

6. Count your own hidden hours in the total cost

The DIY Clay route looked cheaper on paper. We paid for a couple of data subscriptions, Clay credits, and some API costs. But we didn't budget for Priya's time, the SDR's time, or the week we lost when a data source changed its schema. When I did the full cost analysis in November, our "cheap" setup was actually costing more than okki-go's subscription—if we valued our team's hours at even half their loaded cost.

That was the penny-wise lesson I should have learned years ago. The most expensive tool isn't always the one with the highest invoice.

The Bottom Line From a Buyer, Not a Data Whisperer

We went live with okki-go in January 2026. I'm not going to give you some clean ROI number, because outbound attribution isn't that tidy, and anyone who promises a guaranteed reply rate should make you suspicious. What I can tell you is what we stopped doing.

We stopped buying lists from three different places. We stopped verifying emails through another third-party tool. We stopped rebuilding enrichment workflows every time a vendor changed its API. Our RevOps team got hours back, and our SDRs got a cleaner prospect database to start from.

Honestly, I'm not sure if okki-go will still be the right platform for us two years from now. This industry is moving fast. My best guess is that the answer will depend on how our SDR team evolves and how much our own data operations mature. But I do know this: the next time we evaluate a B2B contact data platform, we won't start by asking which tool has the biggest database. We'll ask which tool helps our team generate leads they can actually trust.