I’ve been running outreach for a few months, and I keep getting stuck on the same problem: how do I actually know if someone is worth reaching out to before I spend time personalizing and following up?
Right now, my filtering is pretty basic. I search for people with certain job titles in certain industries, and I just do a rough manual check—are they a decision-maker? Do they work at a company big enough to afford our solution? Then I send.
But my conversion rate is around 5-6%, and I have this nagging feeling that I’m wasting effort on a bunch of people who were never going to be interested anyway.
I started thinking about what “high-intent” actually means. It’s not just someone in the right role at the right company, right? There are other signals. Like, are they actively engaged on LinkedIn? Did they recently change jobs? Are they posting about problems my solution solves?
So I started layering in more filters: looking for recent job changes, checking if they’ve been active in the last 30 days, scanning their recent activity for any mention of pain points relevant to what I’m selling. It’s more work upfront, but I feel like my personalization is better because I’m targeting people who are obviously paying attention.
The question is: am I overthinking this? Is there a point where smarter filtering just becomes procrastination disguised as strategy? And what signals are actually predictive of someone saying yes versus just being noise?
You’re on the right track, but you’re thinking about intent wrong. High-intent isn’t just about their activity level. It’s about whether they have the PAIN POINT your solution solves.
Forget about job changes and activity. Instead: Is their company clearly struggling with the problem you solve? Did they post about it? Do they work in an industry where that problem is acute? Those are your high-intent signals.
Example: if you sell LinkedIn automation, someone who just became a sales leader and their company is in hyper-growth mode is high-intent. Someone who posts about hiring challenges is high-intent. A random VP of Sales at a stable company? Medium intent at best.
Filter by pain relevance first. Everything else is secondary.
This is where smart filtering in LiSeller becomes powerful. You can layer conditions: job title AND company size AND activity level AND keyword mentions all in one filter. Then pull that list, segment it further, and run different message variants against each segment to see what converts.
Then here’s the hack: track which FILTER CONDITIONS showed the best conversion rates. Over time, you’ll realize only 3-4 of your filters actually matter. Strip everything else away. You’ll cut your list size by 70% and double your conversion rate.
In recruiting, we call this “passive candidate” vs. “active candidate.” Active candidates are looking right now. Passive candidates might be open but not actively searching.
High-intent signals for me: Recent profile updates, recent job change, active in industry groups, posting about leadership challenges or career growth. These people are thinking about their next move.
I avoid filtering by just company size or title alone. A VP at a tiny startup might be more high-intent than a VP at a Fortune 500 because they’re in growth mode and actually making decisions.
From an account safety perspective, I’d actually caution against over-filtering. The more granular your filters, the smaller your list, and the more tempted you’ll be to send to the same people multiple times or in quick succession to “make up” for the smaller list.
That’s when you get flagged by LinkedIn. Instead: use reasonable filters (title, company size, location), accept that some outreach won’t convert, and focus on QUALITY per person rather than trying to perfectly predict intent.
Spread your outreach over time and across a decent-sized list. That’s safer and more sustainable.
I struggled with this too. I realized I was spending 3 hours filtering for every 1 hour of actual outreach. That was backwards.
What worked: I created a super simple scoring system. Recent job change = 2 points. Posted in last 7 days = 1 point. Company size >50 employees = 1 point. Target only people with 3+ points. Sent my list out, tracked reply rates by score level.
Turns out, job change was the ONLY signal that mattered for my offer. So I stripped everything else away, cut my filtering time from 3 hours to 30 minutes, and conversion actually stayed the same.
Test your filters. Most of them are probably unnecessary.
LiSeller’s smart lead filtering is exactly built for this. You can set up filters based on: company characteristics, role, activity (when they last posted, profile updated, etc.), and even keyword mentions from their posts and about section.
Here’s what most users don’t realize: you can SAVE filter combinations and A/B test them. Run outreach with Filter Set A versus Filter Set B across similar time periods. Compare conversion rates. This tells you which combination of signals is actually predictive for YOUR audience.
That’s how you stop guessing and start following data.
You’re asking exactly the right question, but the answer requires testing, not theorizing. Here’s the framework:
- Start with a reasonable baseline filter (title, company size, location, activity in last 30 days).
- Send outreach to 200+ people matching that filter.
- Track conversion by additional variables you could filter by (recent job change, post activity, keyword matches).
- Analyze: Did high-job-change prospects convert better? Did keyword mentions matter?
- Layer in ONLY the filters that showed statistical significance.
You’ll likely find 1-2 variables that matter and 5-6 that don’t. This is when your targeting becomes truly powerful. But you can’t know until you test.