I Stopped Spending 2 Hours on Research Every Morning

Monday, 7:50 AM. LinkedIn in tab one. Crunchbase in tab two. CRM in tab three. A blank spreadsheet in tab four.

Two hours from now, you'll have a list of ten companies and a sense of accomplishment that evaporates the moment you realize you haven't sent a single email yet.

---

The morning before

Here's what "doing research" actually looked like.

Start on LinkedIn. Open the company page. Scroll through their recent posts for anything you can reference in an email. Click to the CTO's profile. She posted about a conference three weeks ago. Maybe usable. Bookmark it.

Switch to Crunchbase. Check for funding. Nothing recent. Try their blog. A product update from January. Thin, but it might work as an opener. Write it down.

Check the CRM. Make sure nobody on your team already emailed them. They haven't. Add the company to your spreadsheet with the CTO's name and the product update note.

One company done. Twelve minutes.

Nine more to go before you can start sending. By 10 AM, you have your list. You also have a dull headache from context-switching between six tabs and the distinct feeling that you've been busy without actually doing anything.

The Salesforce State of Sales report (2023) put a number on this: sales reps spend 28% of their week actually selling. For SDRs, the biggest chunk of non-selling time is research. The work before the work.

What two hours actually produce

Ten companies. A few bullets next to each name.

Some of those notes are solid. A Series B last month. A VP of Sales who started two weeks ago. Those emails practically write themselves.

Most aren't. A product update from four months ago. A press release about an award. A LinkedIn post about company culture. You stretch these into opening lines that read like you stretched them.

Out of ten sends, one or two get replies. The ones with real signals behind them. The others get deleted or ignored, and you never know which ones those were because the sample is too small to learn from.

Two hours of research. Two emails that earned a reply. The other eight were busywork disguised as personalization.

What changed

I didn't have an epiphany. I had a Friday afternoon where I tracked my own time for the week and didn't like the number.

Eleven hours. That's how much of my week had gone to pre-send research. Eleven hours of browsing, cross-referencing, and note-taking to produce about 50 emails, of which maybe 7 got a reply.

The problem wasn't the research itself. The problem was I was starting from zero every morning. Blank spreadsheet, blank search, no direction. I was hunting for two things at once: companies that fit and reasons to contact them now. Combining those two searches is what takes two hours.

So I split them. I started working from signals first. Not "who matches my ICP" but "what changed this week at companies that match my ICP." A funding round. A batch of sales job postings. A new executive. When the signal comes first, the research is half done. You already know why you're reaching out. You just need to confirm the contact and write the email.

I tried doing this manually for a week. Google Alerts, checking Crunchbase daily, scanning job boards. It helped. Cut research to about an hour. But the collection itself was still manual work.

Then I started using Optifai, which does the collection automatically. Every morning: five companies with a signal attached, the right contact identified, and a draft ready to edit. The fifteen minutes I now spend is review and judgment, not research.

The morning after

8:00 AM. Open Optifai. Five companies.

One raised a Series A yesterday. Contact: CTO. Another posted three SDR roles this week. VP of Sales started last month. A third saw website traffic spike after a feature launch. Contact: Head of Marketing.

I read the context. Edit one draft to add a line about their product launch that I saw on Twitter. Skip one company — we tried them last quarter, no fit. Send the other three.

8:18 AM. Three emails out, each tied to something that happened this week. The rest of my morning is follow-ups and calls.

What the numbers said

I tracked loosely, not scientifically. But the direction was obvious within two weeks.

Research time went from roughly two hours to fifteen minutes. Emails sent per day dropped from about twelve to five or six. My manager noticed. I told him to wait two weeks.

Reply rate climbed. When every email references something that happened this week, more people respond. The specific number varied, but the gap between the old approach and the new one was visible by day ten.

Meetings booked held steady in week one, then went up. By month's end, more meetings from fewer sends. The volume math stopped working.

The surprise was how fast I learned which signals worked. At five targeted emails a day, the pattern is clear within two weeks. Funding announcements converted. Old product updates didn't. New executive hires were the best signal of all. Someone new in the role, looking to make changes, open to conversations they wouldn't have had six months ago.

At 150 sends a day, that pattern is invisible.

If you want to make the same switch

Work from signals, not profiles. Stop asking "who matches my ICP." Start asking "who matches my ICP and had something change this week." No change, no email. They're not going anywhere.

Track time-to-first-send. If your first email goes out at 10 AM, your best energy is going to research. If it goes out at 8:15, that energy went into pipeline instead.

Let the volume drop. This is the uncomfortable part, especially if your team runs an activity leaderboard. Five emails with real signals will outperform fifteen without. Give it two weeks and compare reply rate per send.

Automate the collection, keep the sending human. The bottleneck is gathering: finding the signal, identifying the contact, pulling context together. That part should be a system's job. The email itself still needs your judgment and your voice.

---

Eleven hours a week came back. Not all of it turned into more sends. Some became better follow-ups, better call prep, better conversations. The pipeline grew because the inputs got sharper, not because the volume went up.

If you want to see what signal-based mornings look like, see how Optifai works — start free, 7 days, no credit card.