What if your Linkedin outreach only went to people who were already paying attention?
Here's how it works:
You tell us what to monitor:
→ Your competitors' pages and their leadership's profiles
→ Your own company page and team members' posts
→ Keywords that matter to your business
When someone in your ICP engages with any of this, likes, comments, follows, we catch it. They land in your leads list automatically with full context on what they engaged with, when, and how many times.
Then the interesting part:
They don't get a generic "Hey {first_name}" template. The system builds a message around the actual signal. Which post they liked. What they commented on. What their role tells us they care about.
You control exactly how deep the personalization goes. Set it once and every message sounds like you spent 10 minutes researching them. Because the system actually did.
We're calling it shadow selling.
We're opening early access to the first 50 people. Here's the early access link: https://networkhq.io/warms-leads-and-personalisation
I'm personally onboarding every one of them.
good points
The intent signal is the right wedge. Where this will make or break adoption: the first message phrasing after the signal fires.
"I noticed you engaged with X" reads creepy to ~50% of recipients, especially anyone non-marketing. Doesn't matter how warm the signal is.
Move that actually works: be signal-aware in your targeting but not in your message text. Message should sound like cold outreach the recipient could've gotten from anyone. The targeting precision is invisible to them and that's where your moat is — you only spend tokens on warm prospects.
Also worth: 24-hour cooldown after the signal fires. "Liked your post in the last hour, here's an email" is creepy speed. 1-2 days feels like coincidence.
The intent signal makes sense. The part I'd add: for B2B service businesses, the first message doesn't need to close — it just needs to earn a reply. A quiz or scored assessment as the CTA works better than "book a call" here because it gives the prospect something to do that feels low commitment. By the time they finish it, they've self-qualified.
The model is right. Most LinkedIn outreach loses because the only personalization is the first name. The risk to navigate: 'I noticed you liked Greg's post' reads as creepy to anyone who knows LinkedIn isn't Twitter. The signal needs to be invisible in the message. The best outreach I've seen mentions the topic the person engaged with, not the act of engaging. Two things I'd test fast. One: does conversion hold when you blind A/B against generic outreach to the same ICP? Engagement might be correlated with buying intent but not causal. Two: how are you handling LinkedIn TOS? They've cracked down hard on monitoring tools.
Linkedin is solid
The personalization angle is brilliant—most B2B outreach is so generic that people don't realize someone actually spent time researching them. The "shadow selling" framing is perfect; you're building actual signals of real interest before the pitch. Love that you're onboarding the first 50 manually; that level of touch and iteration on messaging is exactly what separates high-converting outreach from spam. Curious: does the early access product tie into your outreach at all, or is it positioned separately?
I didn't understand your question entirely.
We already have a product that does prospecting, auto outreach etc.
The features that I mentioned are now in closed beta and not accessible through the existing product.
Once we come out of the beta - it'll be within the existing product and there'll be two tiers (one with what we have) and the second tier (with existing features + signals+ warm leads + personalisation)
You should sign up on the waitlist. It's great product :)
Fellow Indian SaaS builder here. VoiceAI Studio TTS plus RevenueSystem AI tools — targeting Indian creators who need AI voice and automation. Bootstrapped with UPI payments built in. Happy to connect if you're also building for India.
LinkedIn is getting incredibly aggressive with their anti automation filters and AI detection for DMs recently.
We don't use your linkedin account for any of the signals or even drafting messages.
On the personalized messages - they sound exactly human.
In fact, we have so many banned phrases, banned writing styles etc already baked in and we provide the user to fine tune it even more by providing options for it.
fair point, the ICP filter handling dedup makes sense. didn't think about it that way. what i'm wondering though is what happens when ICP definitions start looking the same. most saas tools in a category target roughly the same persona. if 50 hr tools all filter for "people engaging with hr content," does the overlap stay small or does that specific niche get saturated fast?
Sales leader for 10+ years before I started building my own thing. The intent signal IS real. The part I'd push on is the follow-up CTA, not the first touch quality.
In B2B, the person engaging publicly with a competitor's content is rarely the person who signs the PO. They're usually a senior IC scoping for an actual buyer one level up. So you can get 5x open rates on the first message and still close zero.
The wedge isn't 'how personal is the opener'. It's 'does the opener ask the right question'. The question that converts off intent signals isn't 'want to book a call' - it's something like 'You looked at [X]. Are you evaluating this directly, or pointing it out to someone who would? Happy to send them a 90-sec walkthrough.'
That reframes the engaged person from prospect-to-close into champion-to-recruit. Which is the actual job-to-be-done with intent data in mid-market and up. Curious if your scoring nudges users toward champion-recruit messaging vs direct-close messaging based on the engager's role.
Dylan, this is super useful. How do I contact you?
If it isn't too much of an ask - would you mind signing up?
This actually feels interesting because timing matters way more than most people realize in outreach. Reaching out to someone already paying attention to your space makes a lot more sense than sending cold messages to random ICP lists. Curious to see what the response rates look like once the first users start testing it.
Would love for you to sign up and see the results for yourself, Rahul :)
Too many outbound tools optimise for volume. What you're describing is a shift from spam to signal.
I work with founders on SEO and outreach, and the pattern I see is that signal-based outreach always converts better than spray-and-pray. The real advantage here is that you're eliminating the 'why should I care?' friction before the first message.
One thing worth tracking: do the early access users who come from competitor monitoring convert differently than those from their own brand tracking? I suspect the intent level differs, and that would shape pricing tiers.
yes - certainly there would be a difference - if someone is monitoring your brand as opposed to competitor than you'd have a higher chance. But someone evaluating your competitor is also a potential prospect that your team would need to focus on :)
The signal is the easy part. The harder part is what happens after they reply. Engagement-based outreach gets higher initial response rates because it feels less cold, but conversion to pipeline depends on your second and third messages. The other thing worth thinking about: a lot of people who engage with a competitor's content are not in market, they're researching, benchmarking, or working in adjacent roles. The lift over a well-built ICP filter is usually smaller than it looks in the demo. Curious what your early data shows on reply rate vs meetings booked, that's where this wedge has to prove itself.
Would be great if you signed up.
You don't have to use your linkedin account at all.
And then you can see the results for yourself :)
Genuinely sounds very interesting, applied for the waitlist too.
Is it it built on frontier LLMs or OSS model are included too?
It's built on frontier LLMs. Bring your own provider and key is something that's on the roadmap.
Thanks for applying.
Curious to see when this is further along after your early test.
Can you sign up?
You don't have to use your linkedin account at all.
The engagement-as-warmth-signal layer is the right wedge. Sales Nav has a version of this, but it's clunky and doesn't tell you what someone engaged with, just that they did.
Two things I'd think hard about for v1:
LinkedIn detection. The same pattern your tool produces (monitor → outbound to engagers) is one LinkedIn already trains its abuse models on. Accounts running this will need real rate limits and probably human approval gates before send, otherwise you'll see early users get restricted within a few weeks and blame the product.
Novelty decay on the personalization line. "I saw you commented on X" lands great the first 6 months across an industry. Once it becomes a known pattern (and it will, because that's how outbound trends die) reply rates drop hard. The defensible move is probably the message NOT looking like an outreach at all. Something closer to a peer comment than a pitch.
The intent capture is the real product. The message generation is the part that needs the most thought because that's where everyone will converge.
Thanks for the feedback :)
Would love for you to sign up :)
the repeated engagement filter is the part i was skeptical about. single likes are noise but same person same topic three times in a week is a real pattern. curious what happens when this scales though. if 500 users all see the same person engage with a post, does that person get 500 messages? or is the signal distributed enough that it doesn't matter?
Good question. Short answer - the ICP filter solves most of this naturally.
500 users aren't all watching the same competitors with the same ICP criteria. A fintech sales tool, an HR platform, and a design agency might all monitor the same popular SaaS founder's posts. But their ICP filters are completely different. The same engager only surfaces for the user whose ICP they actually match. In practice the overlap is tiny.
Even in cases where two users share a similar ICP and monitor the same competitor - the messages are different. Built from different signal combinations, different personalization settings, different writing styles. The prospect gets two relevant messages from two different companies about two different products. That's just normal business. They probably already get that from manual outreach.
The signal-based personalization is the part that actually works. Generic "Hey {first_name}, I noticed you work in X" is dead — everyone knows it's a template. But "I saw you commented on [specific post] about [specific problem]" lands completely differently because it's true.
We do something similar on the inbound side — when someone hits our Founding Member page and doesn't convert, we know they were at minimum interested enough to read the offer. That context changes the whole follow-up conversation.
"Shadow selling" is a great name for this. The warm signal is doing all the heavy lifting before the first message even gets sent.
The signal-based angle makes sense. Cold outreach usually fails because the timing is random, not just because the copy is bad.
I like the idea of building the message around something the person actually engaged with, but I think the tricky part is making it feel relevant without feeling like surveillance. That personalization depth control is probably important.
Curious how you’re thinking about the line between “this person showed intent” and “this message feels a little too aware of everything I did on LinkedIn.”
The stacked signal logic is the part that makes this interesting. A single like is noise but someone from your ICP liking a competitor post, commenting on a problem discussion, and having a relevant role change in the same week is a pattern worth acting on.
The timing angle you raised is underrated. Most outreach tools compete on database size. Competing on timing is a fundamentally different game and much harder to copy.
One tension worth exploring as you scale: the more automated this gets, the more recipients will start recognising the pattern. Not because it is bad, but because the moment 500 people run the same signal approach, the bar for what feels personalised shifts upward. Curious how you think about staying ahead of that.
True, the bar will shift upwards. So we as a company will innovate too. Interesting times ahead.
That's the right mindset. The tools that win long term are the ones that keep the human judgment in the loop rather than fully automating it away. Looking forward to seeing how you solve it.
Filtering by people who are already engaged with your space before sending a message is the right instinct. Cold outreach to warm signals should outperform cold to cold by a lot. Curious how the response rates look vs traditional outreach after you get the first 50 onboarded.
Yes - would love for you to try it out yourself too - sign up if you are interested :)
letting users pick the window is smart. most default to reach out now and skip the freshness question entirely. curious what range people actually choose - same-day cluster or more spread?
Mostly same day - within a couple of hours.
Intent signal layered on LinkedIn engagement is a strong wedge. The make-or-break for this category is usually deliverability and rate limits, not personalization quality. Once volume goes up, LinkedIn throttles or flags. How are you handling that: dedicated IPs, warmup, randomized send patterns? Also worth thinking about a confidence score on the signal itself.
Intent signal layered on LinkedIn engagement is a strong wedge. The make-or-break for this category is usually deliverability and rate limits, not personalization quality. Once volume goes up, LinkedIn throttles or flags. How are you handling that, dedicated IPs, warmup, randomized send patterns? Also worth thinking about a confidence score on the signal itself. A like on a leadership post is not the same intent as a comment on a job ad. Buyers will pay more for the high-confidence list than for raw volume.
Every lead we surface comes with a confidence score and the reasoning behind it.
"dedicated IPs, warmup, randomized send patterns" - yes, we do that. Nevertheless, wanted to clarify that user accounts are not used to surface these leads.
Also, when you have high precision leads - you wouldn't have to worry about Linkedin's algo because:
This is a smart shift from cold outreach to intent-based outreach.
Most LinkedIn automation fails because it ignores timing and context. Reaching out after someone has already engaged with relevant content makes the conversation feel natural instead of forced.
The personalization layer is the interesting part here. Referencing actual engagement signals instead of generic templates could seriously improve response quality and trust.
“Shadow selling” is a strong concept if executed carefully without becoming spammy. Curious to see how you handle signal quality and avoid over-automation as this scales.
This is a smart way to think about outreach.
Targeting people who are already engaged makes a big difference.
Do you think this works better than cold outreach in the long run?
Certainly better than cold outreach, any day.
The signal-based targeting makes sense for engaged accounts, but I'd watch out for the false positive problem. People like and comment for a lot of reasons that aren't buying intent (curiosity, supporting friends, content marketing of their own). At scale, even 5% noise in the engagement signal compounds into a lot of wasted outreach. How are you filtering for actual buying-stage intent vs general engagement?
When a lead appears, we don’t just look at the surface-level signal.
We look at the full context.
Repeated engagement around the same topic, category, or pain point usually tells a much stronger story - hence, buyer intent
curious how the timing works. if someone likes a post and gets outreach 2 hours later, does that feel serendipitous or like being watched? seen both play out depending on the gap.
We've seen that within a couple of works best in our case.
But we give our users the choice to decide within what window, they want to act.
Thing to remember is that it should be fast enough that the context is still fresh.
The other thing that helps is the message never references the engagement directly.
It doesn't say "saw you liked this post." It's built around what their profile and activity tells us they care about. The signal decides when to reach out. The personalization is about who they are, not what they clicked.
So the prospect gets a relevant message that lands at the right moment.
Interesting concept — are you tracking profile views or post engagement to flag "warm" leads? Curious how you avoid false positives.
Both actually. Post engagement is the main trigger - who's liking, commenting, sharing stuff from your competitors, your team, or keyword discussions in your space.
But a like on its own tells you almost nothing. So we dig deeper.
Once someone shows up we look at everything. Who are they, What's their company doing, What have they been talking about - not just today but over the past few weeks. Is this a one-off like or have they been consistently engaging with content in your category.
That layering is what kills false positives. One like from a random person? You never see it.
Doesn't matter how active they are. You only see people where the signals, the profile, and the activity all line up.
The signal stacking framing makes sense. A single like is noise; three overlapping signals in the same week is a pattern worth acting on.
The part I find most interesting is the timing advantage. Most outreach optimizes for who to reach — this shifts the focus to when. That's underrated. The same message sent to the same person at the right moment converts at a totally different rate.
The harder problem down the road is that the moment this gets widely adopted, the signal degrades. Early movers win the most. Curious how you're thinking about defensibility — is it the quality of the signal model, or the speed of the workflow?
On defensibility - it's both, but they compound differently.
Signal quality gets better the more data flows through the system. Every user adds new competitors to monitor, new keywords to track, new ICP definitions. The system learns which signal combinations actually convert to replies and which ones look good on paper but go nowhere. That feedback loop gets stronger with every campaign that runs. A new entrant starts that loop from zero.
Speed of workflow is the more immediate moat. Catching a signal is step one. But the gap between catching it and reaching out is where most setups fall apart. If you're piping signals from one tool into an enrichment layer into an outreach tool, that's hours or days of latency. We collapse that into minutes because the detection, enrichment, personalization, and outreach all live in the same system. By the time a competitor's stitched-together stack processes the same signal, our user's message already landed.
I am building a brand relating to SEO Blogs and Founders' Interviews. How should I get more reach on LinkedIn?
Two channels. Most people only do one.
You're sitting on a goldmine with the founder interviews. Every founder you interview shares it with their audience. That's free distribution.
But don't just publish and move on. Extract the best insights and post them as native LinkedIn content too.
"I've interviewed 50+ founders this year. The ones growing fastest all do one thing with content that the rest don't." That gets engagement.
Same with your SEO expertise. Share specific results, not tips. "Our client went from page 3 to position 2 by doing [specific thing]. Took 6 weeks." Your ideal client reads that and thinks "I need to talk to these people."
Signals that tell you someone needs SEO content right now:
a. Companies hiring for "Content Marketing Manager" - they're investing in content but don't have the team yet.
b. Founders posting about a new product or market - they'll need landing pages and comparison content.
c. People asking SEO questions in comment sections - they're trying to figure it out themselves.
Reach out with something specific. Not "we do SEO content." More like "saw you're hiring a content lead - we could cover your Q3 pipeline while you're looking. Here's what we'd prioritize based on your current rankings."
shadow selling is a good name but i'd push on what happens at scale. one well-researched message to someone who liked a relevant post feels like good selling. the same approach running automatically across hundreds of people per week starts feeling like surveillance with a mail merge. where's the line in your product between 'this feels thoughtful' and 'this feels like a bot figured out my browsing behavior and is using it against me
Honest answer - the line is in the volume, not the mechanism.
The same salesperson who manually checks a prospect's activity, reads their recent posts, checks other signals and writes a thoughtful DM is doing exactly what the system does. Nobody calls that surveillance. They call it good selling. The discomfort starts when you imagine that happening to multiple people simultaneously.
The real red line isn't automated vs manual. It's relevant vs irrelevant. A manually written message that references your job title and says "thought this might be useful" feels like a bot. An automated message that references a specific discussion you participated in yesterday and connects it to a problem your company is actually facing feels like someone paying attention.
The creepy feeling comes from being targeted with information you didn't expect someone to have. But everything we use is public activity on a public platform.
Where I do agree with you: if someone runs this at high volume with lazy personalization settings, it will feel exactly like what you described. That's a user problem we try to solve through deep personalization that's anchored to who the person is, not just what they clicked.
Interesting article... If you are looking for leads to help boost your sales and marketing... I have lists of high networth investors and could tailor customers that could either invest or boost customer sales. We have also helped founders get featured on Forbes, Bloomberg and many more. shoot me a message on telegram @caseyimafidon
LinkedIn is not always a good option for new startups
It is - but one needs to build credibility first like any other place. So probably just then the push factor ie. cold outreach, one needs to create the pull factor too - insightfut content. I do agree that it takes time, but its probably the only place where you have mostly real verified people.
Solid angle, the stacked-signal logic is the right instinct.
Saw Galyna's reply that you already filter by role, geography, industry and headcount on the ICP side, which is more than most outreach tools do.
Quick question from a potential user perspective: do you also filter on company-level financial or growth signals? Things like funding stage, recent funding date, revenue bracket, headcount trajectory over the last 6-12 months. For some ICPs, those filters matter more than the static ones, because a 50-person company that just raised Series A and grew 40% in 6 months is a very different buyer than a 50-person company that's been flat for 3 years.
Either way, betting on signal-led vs volume-based feels right. Good luck with the launch.
Thank you. Yes, we do all the signals that you mentioned and more. Would love for you to try the new feature by signing up.
The stacked signal idea is what separates this from vanilla intent data. One like is noise. Three overlapping signals in the same week is an opening.
The part that resonates most: the engagement is the trigger, not the message. Most tools try to make the signal the personalization. The good ones use it for timing and build the actual message around something real about the person.
We use a version of this at Genie 007 — looking for people posting about keyboard fatigue, RSI, or productivity frustration. One post is mildly interesting. Same person, multiple signals, same week? That's worth reaching out.
Yes- would be super useful if you stack intent data. Would love for you to use our tool. You could try it out - worth a great shot at improving conversions on Linkedin
This is actually a smart angle because most outreach fails before the message itself even matters. Targeting people who already showed intent or engagement makes a lot more sense than scaling cold outreach volume endlessly. I also like that you focused on signal quality instead of pure automation because that is usually where LinkedIn tools become spammy fast. Feels more aligned with how real relationship building should work on the platform. Good point overall 🙂👍
That's great to hear. Would love for you to enrol in the closed beta. It'll be a great tool to have.
Intent-based outreach is a completely different game from volume-based outreach. The mental model shift from "send to everyone in ICP" to "send to people already showing buying signals" is massive for conversion rates. Most outreach tools compete on database size — what you're describing competes on timing, which is way harder to replicate and way more valuable. Building for consumer right now (habit app) and the same principle applies: reaching someone the moment they're already thinking about changing a habit is infinitely more powerful than reaching them cold. Really smart angle here.
On top of the fact that intent based outreach garners more responses from prospects. it also respects Linkedin's algorithm - no same templatized spammy messages across, high value and low volume outreach makes our outreach be within their unofficial quota etc.
Great idea. So is the product or mvp ready ?
The product is in closed beta. Thoroughly tested. Opening to the public slowly. Do you want to try?
Awesome Idea. How can I control how deep the personalisation goes?
You get full control over what the system references and what it doesn't. Think of it as a set of toggles:
What to reference:
How to sound:
How much human review:
This is a strong angle because you’re not selling “LinkedIn automation,” you’re selling timing. Most outreach tools still start from cold lists, then try to fake relevance with personalization. Your wedge is better: wait until the buyer has already shown attention, then turn that signal into a specific message.
That should probably be the core category frame. “Shadow selling” is interesting, but it may sound a bit vague or slightly dark from the outside. The sharper positioning is signal-led outbound: outreach triggered by real buyer attention, not guessed intent.
Naming matters here because NetworkHQ feels broad and generic for something this specific. If this becomes a serious sales intelligence layer around attention signals, a stronger SaaS brand like Beryxa .com would carry the product with more authority than a name that sounds like a general networking hub.
Thanks for the helpful points:
Appreciate it
One practical thought.
Since the full domain decision may be too early, I can help in a lighter way.
The signal-led outbound framing is strong, but the risk is that NetworkHQ may still make buyers read it as a generic networking tool instead of a sales intelligence layer around real buyer attention.
I do focused naming and positioning audits for early products: current name risk, category framing, domain perception, stronger positioning direction, and whether the brand can hold up before more demos, landing pages, and user memory build around it.
Not a long consulting thing. Just a sharp written breakdown with practical recommendations.
I’m doing a few at $99 while refining the format. If useful, I can do one for NetworkHQ and give you a clear outside read before you commit further to the current brand frame.
Glad it was useful.
The key thing I’d watch is whether NetworkHQ stays a broad networking frame or whether the product is really becoming a signal-led outbound layer.
If it is just a positioning note, no need to overthink the name yet. But if Beryxa is genuinely the kind of SaaS brand you could see carrying the product beyond “networking hub,” I’d pressure-test it before NetworkHQ gets baked into demos, landing pages, and early user memory.
I do not want to turn the thread into a public domain discussion, but if it is seriously on your shortlist, message me here:
https://www.linkedin.com/in/aryan-y-0163b0278/
Hi, how do you handle the false positives? Someone liking a competitor's post does not always mean ICP intent. Sometimes it is curiosity, sometimes a former coworker, sometimes accidental scroll-tap. Are you filtering by role-fit before the message fires, or letting the user filter manually?
We filter by the ICP definition that the user provides: role, geography, industry, company headcount etc before sending the leads to the users.
Makes sense. ICP-fit plus engagement context is already more than what 90% of outreach tools do. Will keep an eye on the launch.
Thank you. Can you sign up for the waitlist. I'll personally onboard you and be your poc going forward as well for you and your team.
"Shadow selling" is a sharp frame, but it rests on engagement = intent. It doesn't.
Someone liking a competitor's post is an attention signal, not a buying one. Most LinkedIn engagement is reflexive. And the people most likely to engage with content about a problem space are peers, competitors, and job-seekers studying it — not buyers. Competitors like a company's posts far more than its prospects do. You'll surface a lot of motion that looks like signal and isn't.
Bigger issue: the personalization paradox. "Sounds like you spent 10 minutes researching" works because almost nobody does it. Once a few hundred people run this, recipients get "I saw you liked [post]" at scale — and the signal dies the moment it's automated en masse.
Both fair points. Let me push back on each though.
On engagement not equaling intent - you're right, a single like is a weak signal. We don't treat it as a buying signal. We treat it as an attention signal. The value isn't "this person liked a post, pitch them now." The value is "this person is paying attention to this space right now, and that's a better starting point than a cold list where you have zero timing context."
The real signal strength comes from stacking. One like means nothing. But when someone from your ICP likes from your competitor's post a problem or pain point, comments on a keyword discussion about the problem you solve, and their company just posted a hiring role in your category - then you see a pattern. We score on the stack, not the individual action.
On the personalization paradox - 100% agree this is the long-term risk. "I saw you liked [post]" will die the same way "I saw your recent post about [topic]" already did.
That's why the personalization isn't anchored to the engagement itself. The engagement is the trigger. The message is built around their role, their recent activity, what they've been posting about. The signal tells us when to reach out. The personalization is about who they are, not what they clicked.
Will this advantage compress over time as more tools do it? Probably. But right now the bar is "Hey {first_name}, love what you're building" and we're a long way from that becoming sophisticated enough to erode signal-based personalization.
Good pushback though.
Fair pushback that actually changes my read. The stacking framework + trigger-vs-identity split are more defensible than the soft-promo suggested. Most "intent signal" tools don't make either distinction.
One thing neither addresses though: sender saturation. Stacking solves "signal too weak." Trigger/identity split solves "personalization decays into spam." But the recipient's attention budget for thoughtful outreach has a ceiling, same one regardless of how well each sender does the work.
Smart personalization tools in email worked brilliantly for early adopters, then plateaued as competitors copied. Not because personalization stopped working — recipients stopped having capacity to engage with five "researched" messages a week. The signal doesn't compress. The attention does.
This is the kind of second-order problem worth pressure-testing — HiveMind (myosin.xyz/hivemind) is built for exactly this if useful.
This feels like the natural evolution of outbound in the AI era.
The companies that win won’t necessarily be the ones sending more messages.
They’ll be the ones responding to real intent signals faster and more intelligently.
Also smart that you’re combining:
behavioral data
context-aware messaging
controlled personalization depth
That combination can make outreach feel much more human instead of automated.
https://teams.live.com/l/invite/FAAk3iOSJkDyS11JQE?v=g1
Shadow selling seems like a powerful unlock. Too much time gets wasted in babysitting the oureach pipeline. Definitely excited to see if this can help me spend my time on actual conversions instead.
That sounds great - could you please add yourself to the list in the shared url?
high time we stopped pretending "oh I just happened to stumble upon your profile" out of a billion other users. sure you did. you found them for a reason, and the message can actually say so.
hehe - yes, that would sound more authentic
The best LinkedIn outreach is when the buyer is already paying attention. You're just removing the friction of them finding you first.
yes - you should enrol yourself in the waitlist. It'll be of immense help in your outreach.