The Spreadsheet at 4:38 p.m.
It was 4:38 p.m. on a Thursday in March when our VP of Sales appeared at my desk with a spreadsheet. Not the usual pipeline update. The kind where every row is an account our outbound team had promised to contact the following Monday.
“How many of these are ready to send?” she asked.
I ran the checks we should have been running every week. We had 430 target accounts for an ABM campaign. The plan was to hit the top 300 with a personalized email sequence. Our CRM had contact names for 211 of those, but only 86 had a direct email that hadn’t bounced the last time we looked. Another handful were reachable through LinkedIn. The remaining 200-plus accounts would take days of manual research.
I’ve spent eight years in RevOps, and I’ve managed more than thirty last-minute campaign rescues in the last five years. This one was close to the edge. We didn’t need a new vendor pitch. We needed data, and we needed a process to get it into Salesforce before Sunday night.
How We Got Here: A Sales Intelligence Platform Mistake
If you’re wondering why we had a CRM full of companies with no direct emails, the honest answer is that we picked a sales intelligence platform based on price per account, not total cost. The budget vendor’s sample file looked great. Finance liked the quote. Nobody calculated what would happen when the data aged.
Every week, SDRs were losing an hour or two exporting records, removing duplicates, and trying to guess email patterns after the provider’s data turned out to be stale. We called it manual enrichment. In reality, it was a tax on our most expensive resource.
To be fair, no data provider is 100% accurate—not okkigo, not the legacy tool, not anyone. But a good platform has fresher sources and a workflow that helps you handle gaps. That was the part we were missing.
Meanwhile, two SDRs had been quietly testing okkigo on a side project. They kept saying it didn’t try to replace their judgment. It suggested contacts, and a human reviewed the suggestions. I was skeptical because every vendor says that. But when Thursday’s spreadsheet arrived, okkigo was the only tool we had already connected to our sandbox. Speed matters more than hype in an emergency.
What Is Lead Enrichment, and When Should a B2B Sales Team Use It?
If the term sounds broad, it is. Lead enrichment means filling in missing or outdated fields on an existing lead or account record—email address, phone number, current title, company size, technology signals, and sometimes intent data.
When should a B2B sales team use it? Not every time. Use it when your SDRs are going to send a personalized sequence and the missing field determines whether that sequence can happen at all. Use it when the target account is valuable enough that manual research would cost more than enrichment. And use it when your starting record has a company name and a domain but not the contact details.
Don’t use enrichment to make a dirty database look tidy. That’s how you end up sending to stale domains and hurting your deliverability. The same logic applies if an AI SDR is doing the first touch: garbage in, garbage out.
We were past the “should we?” stage. We had two days.
The okki-go Setup in 48 Hours (And My API Rate Limit Mistake)
By 6 p.m., we had connected okkigo to our production CRM. The okki-go setup itself wasn’t painful. It took about 45 minutes, including permissions. The harder part was deciding which enrichment fields actually mattered for the sequence.
What sold me later was the waterfall enrichment flow. Instead of asking one source to be right every time, okkigo checks sources in a defined order. If source A doesn’t have a match, it moves to source B, and so on. The output gave us one suggested contact per account instead of ten messy rows to deduplicate.
Then I made a mistake. I thought we needed a custom API bridge to validate the data before it entered the CRM. I wrote a small integration, hit the API rate limit after about 1,300 records, and spent forty-five minutes debugging something that did not need to exist. That wasn’t okkigo’s fault. I had a rule: don’t build new integrations 48 hours before a launch. I ignored my own rule. (Note to self: if you’re the RevOps person, you follow the same rules as everyone else.)
The native Salesforce sync handled the batching with far less drama. We loaded the 300 priority accounts and let the enrichment job run overnight.
The okkigo data enrichment output fed into a human-in-the-loop review queue. Two SDRs worked through suggestions, approving what looked right and rejecting what didn’t. That review step is not a marketing phrase here. It’s the difference between sending to [email protected] and sending to the actual VP of Sales.
By Saturday morning, 264 of the 300 accounts had at least one suggested contact. Thirty-eight didn’t get a match. I do not know whether every suggested email was perfect—that’s impossible for any data source. But 264 was a lot better than 86, and the queue gave us a way to check before anyone hit send.
Monday Morning
By Sunday afternoon, we had 213 records marked ready. We lost some to formatting issues and some to judgment calls. It wasn’t the perfect list we’d have built with three extra weeks. It was good enough to launch Monday without embarrassing the company.
Monday morning, we sent the first wave in small batches. Some emails bounced. Some replies came in. We didn’t magically hit a record-breaking reply rate, and I won’t pretend we did. But the campaign ran, and the SDRs spent their time writing personalized lines instead of scrubbing CSV files.
The TCO Lesson I Wish I’d Learned Sooner
Now for the lesson that matters more than okkigo, more than the API rate limit, and more than this single campaign: if you buy a sales intelligence platform based on unit cost, you will pay for it somewhere else.
The true total cost of ownership includes the subscription price, the time SDRs spend fixing bad records, the refresh frequency of the underlying data, the CRM integration quality, the API rate limit fit, and the risk of launching late. According to Salesforce’s State of Sales research, reps spend roughly a third of their time actually selling. Every hour spent hunting for a working email reduces that number.
Before this week, our old tool looked cheaper on paper. After this week, I see the whole equation. If a platform makes data easy to review and helps a team move in 48 hours, that is real value. If it generates thousands of stale contacts and costs your SDRs hours of cleanup, it’s expensive no matter what the invoice says.
Looking back, I should have set up data health metrics months earlier and checked them before the campaign was approved. But given what we knew at the time—that Finance wanted lower costs and the sample files looked fine—I understand why we didn’t. We paid the difference in a fire drill.
Maybe that was the real point of the exercise. Sales data is not a one-time purchase. It’s inventory. You either maintain it or you pay for an emergency later. Okkigo helped us fix the immediate mess, but the process around it is what kept us from getting into the same mess again.
