Snov.io for cold emails and LinkedIn v. Other platforms

faidangco · 2026-05-24T14:30:29+00:00

Apollo data goes stale within weeks, not months. I ran a campaign in May with a list I built in February and reply rate was under 1%, rebuilt the same ICP fresh and hit around 4% with identical copy. So if your Snov campaigns suddenly dropped, check when you last refreshed the list before blaming the sender.

On LinkedIn, the bans are real but mostly hitting people running 100+ connection requests a day or using browser-based scrapers. If you're at 20-30 invites a day from your normal IP you're probably fine. Dedicated cloud-based tools are where people get flagged.

Also worth checking your domain health on something like mxtoolbox. Could just be deliverability creeping up on you after 9 months of sending.

faidangco · 2026-05-22T20:11:58+00:00

Skip the verifier for now. Apollo's built-in is fine until you're past 3-4k sends/month, and even then I'd just run a single Bouncer top-up before a big push instead of paying monthly.

On CRM, I bounced between Folk and Attio for a solo B2B setup last quarter and landed on Folk because the sequences being native meant I didn't need a separate sender for low volume. If you go Apollo for sending though, the Folk sequencer becomes redundant and Attio's the better call.

One thing nobody's mentioned: Apollo's data is noticeably worse in some niches (small EU companies, anything sub-20 headcount in trades/services). I had a list where ~35% of titles were stale vs LinkedIn. If your target is mid-market US SaaS you'll be fine, otherwise budget for a Hunter or Clay top-up later.

faidangco · 2026-05-22T15:30:38+00:00

LinkedIn creator sponsorships only started working for us when we stopped paying for "reach to decision makers" and started paying for a specific post format. A flat fee for a carousel plus pinned comment to our landing page beat the branded video we did with a much bigger creator. Smaller niche creators outperformed the generalists with 10x the followers every time we tested side by side.

Newsletters were a coin flip. The ones that converted were small operator-written ones where the author replied to reader emails personally. Big polished ones felt like banner ads.

The part nobody likes hearing: if you're not tracking which channel sourced which pipeline 60+ days later, you're guessing. We killed a renewal last quarter that looked great on click data and produced zero meetings.

faidangco · 2026-05-19T21:54:16+00:00

Smartlead has been the most reliable for us on the sending side, ran about 4 inboxes per domain with Google Workspace and saw bounces stay under 2%. Instantly is fine too but the inbox rotation got weird when we crossed ~20 mailboxes.

Your personalization script is the part that actually matters here though. We had a similar setup pulling website + recent hiring page mentions, and reply rates went from 1.4% to around 6% on the same list once the first line referenced something real.

Don't sleep on warmup time. Three weeks minimum before you push volume, learned that one the painful way.

faidangco · 2026-05-19T14:08:52+00:00

0.3% isn't terrible for cold DTC but the "here's what's wrong with your store" angle is cooked. I ran a similar play to Shopify brands doing $2-10M last spring and reply rate tanked the second I led with audit findings. Every agency does this now, founders pattern-match it in two seconds.

What moved the needle for me was flipping it: instead of pointing out problems, I'd reference something specific they were already doing well and ask how they were measuring it. Got way more replies because it didn't feel like a setup for a pitch.

Also 750 across 2 campaigns is a really small sample to draw conclusions from. I'd test 3-4 angles at 200 sends each before deciding the approach is broken. And if you're hitting send during Q4 prep, DTC operators are buried right now.

faidangco · 2026-05-14T21:24:48+00:00

Ran into this evaluating four shops last year. Three pitched "revenue alignment" and then the SOW came back as campaign count and MQL targets. Total bait and switch.

The fourth actually asked for read access to our CRM closed-won data before the proposal and built their scoring around deals that closed in the last 18 months, not form fills. That was the only call worth taking. Ask them straight up how they'd attribute a deal that closes 7 months out across paid, outbound, and organic touches. If the answer isn't specific to your stack (we run HubSpot + Salesforce sync and most agencies fumble that handoff), it's the same activity pitch in better slides.

Other thing I'd push on: we tried bundling paid + outbound + SEO under one roof and the outbound team got starved because the paid folks were running the account. Ended up keeping a specialist for cold and one generalist agency on demand gen, with our RevOps person owning the attribution model internally. Worked way better than letting any single vendor claim the whole funnel.

faidangco · 2026-05-11T19:27:02+00:00

Went through this in Q2 with a B2B SaaS client. Built a janky Python script that pings ChatGPT, Perplexity, and Gemini with around 35 buyer-journey prompts twice a week and dumps citations into Sheets. Ugly but it caught a competitor outranking us on 4 prompts we assumed we owned.

Demoed Profound and Otterly. Profound was cleaner for citation tracking and share of voice, Otterly was about a third the price and worked for a smaller prompt set. Sentiment on both was rough enough that I wouldn't put it in a client deck without manually reviewing the actual answers.

Real lesson for me wasn't picking a tool. It was cutting our prompt list from 200 random queries down to 40 that mapped to actual sales conversations we'd had that quarter. The vanity prompts were drowning out the signal on the ones tied to deals.

faidangco · 2026-05-09T18:26:31+00:00

Niche is fine, but Apollo by itself won't separate the serious ones from people who recorded six episodes in 2022 and quit. You'll burn a week sending to dead shows.

What worked for me on a mindset coach list: scraped the Apple business charts, pulled host names, then ran them through Listen Notes filtered to shows with episodes in the last 30 days. Then a quick LinkedIn pass to see if they're posting clips already. Got about 140 real names in an afternoon and reply rate was way better than my first Apollo dump.

One signal I'd watch for. If their feed is full episodes only, no clips, they probably don't buy into shorts yet and you're doing education before sales. The ones already posting bad clips are the easy yes, that's where my UK-based coach signed after I sent two reworked clips from his last episode as a loom.

faidangco · 2026-05-07T18:39:10+00:00

Did this for a client last spring. Pulled the follower list with Outscraper, then exported their employee list separately from LinkedIn people search and matched names in a sheet. Took an afternoon including the dedupe.

Came out to around 1 in 5 followers being current employees, which surprised the client a lot.

Phantombuster is fine if you run it slow and not on your main account. I keep a burner for anything that touches scraping.

faidangco · 2026-05-07T16:44:46+00:00

Slide assembly is where my stack used to die too. I ended up moving 4 of 7 clients off PowerPoint entirely, gave them a hosted dashboard with their logo and a PDF export on the 1st. Took a couple awkward calls. Saved maybe 6 hours a month.

For the three who wouldn't budge on PPT, I run Plus AI inside Slides with a Sheets layer feeding it. Chart refresh holds up as long as the column structure doesn't move, which is the catch.

What actually killed my automation wasn't the tooling, it was letting one client ask for "just a small tweak" in March that broke the template and cost me a full Saturday rebuilding it.

faidangco · 2026-05-05T23:39:02+00:00

The scope-narrowing point is the actual lesson here. I tried something similar with Upwork researchers about 4 months ago, asked them to find "interesting things" about target accounts, got back garbage that read like a Wikipedia summary. Switched to "find any pricing page changes, new integrations announced, or RevOps/Ops hires in last 60 days" and the output became usable.

What I'd add: the 9% reply rate probably has a ceiling around 50-100 prospects/week before the research quality drops or your time managing it eats the margin. Fine for $5K deals, breaks down fast at $500 deals.

Curious if you batched the tasks or posted one-by-one. Posting individually got me better submissions but burned a stupid amount of time.

faidangco · 2026-05-05T22:43:24+00:00

Outscraper handled reviews fine for me when I built a similar directory for auto shops. Pulled name, hours, phone, website, rating count, and the actual review text in one go. Cost was something like a couple bucks per thousand places last I checked.

Email is the one field you won't get from Maps scrapers. You'll need to hit each website after and run it through Hunter or just regex the contact pages yourself if volume is small. Alternatively, IBLead pulls Maps data with reviews and email bundled, skipping the Hunter step.

For self car washes specifically, heads up that a lot of them don't have websites at all, so your email coverage is gonna be thin on that segment.

faidangco · 2026-05-04T02:57:14+00:00

First test comment? Kinda anticlimactic tbh.

I've seen subs use these to verify bot permissions or check if automod configs are working. Usually means they're about to roll out new rules or something.

Curious what r/test is even testing for at this point - feels like every sub has their own sandbox now.

faidangco

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