I’ve been thinking about this a lot lately. I’ve got LiSeller set up, and I’m basically running two different approaches right now—one where I filter heavily upfront (looking for high-intent signals, recent posting activity, specific job titles, company size ranges), and another where I just cast a wide net and let the sequence do the filtering.
The wide-net approach feels faster—I can load up 1,000+ prospects and run the sequence. But I’m getting super low reply rates from that group. Maybe 1-2%.
With the filtered group, I’m being way more selective. I’m probably only messaging 200-300 people per week, but my reply rates are better—sitting around 4-5%, sometimes higher. So obviously the filtered approach is working, right? But here’s my question: am I just cutting out the noise, or am I actually better off spending my setup time on filtering instead of just increasing my send volume straight-up?
Like, if I could send to 5,000 people at 2% conversion vs. 500 people at 5% conversion, which is actually better for my business? It feels like the math works out the same, but the operational overhead is completely different. One requires way more work upfront, and the other is basically just plug-and-play.
Also, I’m curious if anyone’s actually tested this with LiSeller’s smart filtering feature. Does it actually save you time compared to doing manual list cleanup, or am I just moving the problem around?
What’s your experience been? Is it worth the setup time to filter before you send, or should I just blast and optimize the follow-up sequences?
You’re asking the wrong question. It’s not about conversion math—it’s about message-market fit. When you’re sending to random people, even if you hit 5% eventually with the right copy, you’re writing generic messages. You’re optimizing for “people who will respond to anything.”
When you filter first, you can write messages that actually speak to that specific person’s problems. Your hooks get sharper. Your personalization gets deeper. And suddenly your message-to-response ratio goes from “decent” to “really good.”
Here’s the thing: a 5,000-person blast at 2% is 100 conversations. But half of those are probably people who aren’t actually qualified. You’re spending mental energy on tire-kickers.
500 people at 5% is 25 conversations, but most of them are actually interested in what you’re selling. That’s way more valuable than 100 lukewarm responses.
So yeah, filter first. It also forces you to understand your ideal customer profile better, which makes your copy sharper across the board. It’s not extra work—it’s foundational work.
The filtering question is actually a systems design issue, not just a volume thing. Here’s how I think about it:
LiSeller’s smart filtering uses behavioral signals—job changes, posting activity, engagement patterns. If you use that before you send, the system is essentially pre-qualifying your list against intent indicators. You’re leveraging the AI upfront instead of hoping it works out at the message level.
What I’d do: set up a workflow where your raw prospect list feeds through a filtered view in LiSeller (or connect it to a CRM like HubSpot via API if you want to get fancy). Filter for 3-4 key signals—recent engagement, job title match, company size. This takes like 10 minutes to set up, and then it’s automated.
You’re not choosing between “filter or blast.” You’re choosing to filter systematically vs. manually, which is a different conversation. And yeah, the manual overhead drops significantly once you automate it.
So: 500 filtered people at 5% beats 5,000 random people at 2% because your follow-ups are also more efficient. You’re not chasing dead leads.
In recruiting, filtering is absolutely non-negotiable. If I sent to every software engineer on LinkedIn, my message-to-hires ratio would be garbage. Instead, I look for people who match specific criteria: recent job changes, companies we work with, specific skill endorsements, activity in the last 30 days.
The upfront time investment pays off because my personalization is so much stronger. When you know they just switched companies or are active in their industry, you can write messages that feel timely and relevant. That’s what moves reply rates from 2% to 5-6%.
But here’s the real win: your follow-up sequences are way more efficient. When you’re following up with someone who actually has intent signals, they’re more likely to engage with your follow-ups too. So you’re not just improving the first touch—you’re improving the whole funnel.
I’d say: filter. Yes, it takes time upfront, but you get better reply rates, better qualified leads, and way shorter sales cycles. That compounds.
From an account health perspective, filtering is actually essential, not optional. Here’s why: if you send to 5,000 random people, LinkedIn’s algorithm flags that as spammy behavior. Account sending patterns get flagged way before message content does. Large, indiscriminate blasts trigger rate limits and action blocks.
When you filter to 500 high-intent people and send quality messages instead, your account looks normal. Your sending pattern looks intentional, not desperate.
So beyond the conversion math, filtering actually protects your account. It’s not just better for ROI—it’s better for account longevity. Send smaller volumes of higher-quality outreach, and you fly under the radar. Send massive blasts, and you risk getting restricted.
My recommendation: always filter. It’s literally safer, and it converts better. That’s a no-brainer.
I used to think volume was the answer. Just send more, optimize later. Then I actually looked at my pipeline quality, and I realized I was wasting time on calls with people who had zero budget. My close rate was trash because I was talking to the wrong people.
Once I started filtering upfront—looking for companies with recent funding, hiring activity, revenue signals if I could find them—my close rate almost doubled. And my sales reps stopped complaining about garbage leads.
So from a business perspective: 500 filtered people at 5% conversion is way better than 5,000 random people at 2%. You get fewer conversations, but they’re better conversations. Your sales cycle is shorter. Your close rate is higher. Your team is happier.
Filter first. Always.
This is a fundamental question in B2B outreach strategy. The answer is: always filter. Here’s the data perspective:
5,000 at 2% = 100 conversations, but most of those are wrong-fit prospects.
500 at 5% = 25 conversations, almost all of them right-fit.
But here’s what matters: your cost per qualified conversation is radically different. With the filtered approach, you’re spending less time on follow-ups with unqualified people, your message quality is higher, and your sales team gets warm, pre-qualified leads.
Beyond the math, filtering forces you to understand your ideal customer profile. This actually makes your entire campaign stronger—from targeting to messaging to follow-ups.
I’d set this up: establish clear filtering criteria based on your ICP—job title, company size, industry signals, activity level. Apply those filters before you start any sequence. Yes, it takes 20-30 minutes to map out, but it compounds across every campaign you run.
You’re not just optimizing for immediate conversion—you’re optimizing for pipeline quality and long-term ROI.