r/b2bmarketing

I think buyers have started filtering cold emails the same way people filter LinkedIn posts now.

Not technically. But mentally.

You see the first two lines and you already know what’s coming.

“Loved your recent post about scaling revenue ops…”

“Quick question…”

“Thought this might be valuable…”

Then some vague business advice that could apply to literally any company with a website.

The weird thing is that some of these emails are probably “good” by old standards. They’re clean, personalized enough, not full of obvious mistakes, and maybe even sent to the right person.

But they all have the same shape.

And once everyone has the same AI tools and the same outbound playbooks, that shape becomes the spam signal.

I don’t think the issue is just deliverability or targeting anymore. A lot of buyers can smell the template before they even process the offer.

The stuff that still gets my attention usually has one specific thing that proves a human actually looked at me or the company.

Not fake personalization like “I saw you’re hiring.”

More like a weirdly specific observation, a sharp one-liner, or something visual/custom that clearly wasn’t dropped into a prompt and mass-produced.

I’m starting to think AI is better used for research and finding the right hook, not for writing the actual message.

Let AI help figure out what might matter. Then have a human add the part that makes it feel like it was actually made for that person.

Quick caveat: this only works if you already have at least one client you'd want to clone. If you're still figuring out who you're actually for, file this away for later.

A few years ago we landed a manufacturing company I'll call Copon. Good margins, long-term relationship, real problems worth solving. The kind of client you want ten more of. The obvious move was LinkedIn outreach to similar companies. We tried it, and it worked poorly.

What actually worked was becoming a sponsor of the industry trade fair Copon attended every year.

Here's the thing: Copon didn't just buy from us, they vouched for us inside their world. The people at that fair were, almost by definition, the same buyer. Same industry, same size, same problems, same trust framework. We didn't arrive cold. We arrived as "the tech partners Copon works with". That changes everything about how a conversation starts.

The lesson I took from it is this: if you've found one client that fits, the fastest path to more of them is entering their ecosystem rather than searching from scratch. The ICP research is already done. The trust infrastructure already exists. You just need to show up where they show up.

In practice this can look like:

1. Sponsoring the niche event your best client attends
2. Asking your best client for a warm intro in a room of 100 ideal buyers. That's worth more than 1,000 cold emails
3. Writing a case study together and distributing it in the channels their peers actually read
4. Partnering with non-competing vendors who already serve the same buyer

Our sponsorship cost less than a mid-range paid campaign, and it came with real conversations, not clicks.

Curious if anyone else has used this kind of ecosystem-entry approach, and what form it took in your context.

Hi folks, I'm working in an APAC manufacturing/industrial business that has a very niche target market - with only around 500-5000 other manufacturing companies in the country that would buy our different product lines. They also would only buy our product or shop around every 5 years or so.

What's the best way of measuring whether your marketing efforts are working during the very long sales cycle? Enquiries as leads is one way, but I'd like to get more insights on whether our ads, sale enablement or content is working whilst an opportunity is open or in a nurture stage

I sell ignition interlock devices, basically breathalyzers wired into vehicles so people can't drive drunk. Customers are transport companies, construction firms, fleet managers. It’s a niche product that we sell exclusively in the Netherlands.

I didn't think LinkedIn outreach would work for me, but it did.

A recent campaign got 19% acceptance and 61% reply rate. My whole strategy was to not ask for anything.

Connection request was just a qualifying question: "I saw you work in transport, is it still true you're in this industry?"

The reason for this is people change jobs and don't update LinkedIn. Filters them out before they accept and then the message lands on someone who's been in a different industry for two years.

First message after connecting had no pitch at all. I asked if they knew anyone in their network who might want a free trial.

What usually happens is they say they don't personally know anyone but they'll point me to a specific company or give me a name. Now I can reach out to that company and say so-and-so suggested I contact you. 

That's a completely different conversation than cold. Even when they say no they don't know anyone, we've already had an exchange. It's not a complete dead end.

Sequence was 3 follow-ups after that. 2nd message was a shorter version of the same ask, 2 days later. Third added a line about alcohol-related incidents in fleets, 3 days after. Breakup message 7 days after that.

I’m using SalesRobot for this right now. Switched from a Chrome extension tool a while ago.

Two things I want to test next: stretching follow-up intervals to 5-7 days because every 3 days felt like a lot. 

And a re-engagement message 1-2 months later to the 40% who never replied. That's still 400 people per 1,000 who might just have been busy.

The thing I'd tell anyone starting this: respond fast when someone replies. I lost a few good conversations just by coming back 5-6 days late. The reply rate is only half of it.

Over the past month I’ve been researching AI visibility / GEO platforms. There are now dozens of tools trying to solve the same core problem:

How do brands appear inside ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews?

I started compiling the main players I could find and here’s the list so far:

1-Profound — enterprise AI visibility analytics and competitive monitoring

2-Scrunch AI — tracks brand presence across AI search engines

3-Otterly — monitors mentions in ChatGPT, Gemini, and Perplexity

4-AthenaHQ — AI search visibility scoring and reporting

5-Peec AI — prompt-level tracking and citation monitoring

6-Promptwatch — LLM interaction and prompt observability

7-Vismore — AI answer monitoring for marketing teams

8-Mentionable — tracks entity and brand mentions in AI-generated responses

9-Rankscale — GEO rankings and AI search performance tracking

10-Friction AI — measures recommendation share across AI platforms

11-Gauge — dashboards for AI visibility analytics

12-SearchTides — AI search performance intelligence

13-Meridian— visibility monitoring for AI-driven discover GrackerAI AI SEO and optimization workflows

14-Nobori — AI search observability and monitoring

15-RankPrompt --AI visibility monitoring and content optimzation tool, also compares competitors ranking and share where your brand is lacking

Most platforms focus heavily on citations, mentions, and rankings

Reddit + third-party authority signals seem extremely important

Very few tools can tie AI visibility back to actual business outcomes

Everyone is still experimenting with what metrics matter most GEO/AEO feels more like the next layer of SEO rather than a replacement

The space still feels very early, but it’s moving fast.

I want to know what others here are seeing:

Which AI visibility tools are you actively using? Any platforms actually delivering useful insights?

As the title says, I’m curious what folks’ opinion is on direct marketing campaigns in the WFH age? Is anyone having success with them?

I work adjacent to the pharma/life sciences industry particularly at the exec level. Recently we’ve had some conversations around direct mailing opportunities to cut through some of the digital noise.

If it helps our target markets are across the US, UK, and EU.

Hi guys, I'm launching a new service, and I was wondering what works better for you to hunt tech founders and close the deals?

I don’t think it’s talked about enough but all the “gurus” out there (both marketing and sales gurus) teach these awful tactics that everyone then pivots towards and it becomes unoriginal and stale. A lot of people watch one video and think they suddenly can build an entire email campaign that gets a 5% reply rate a 15+ appointments a month. Then they get frustrated when the reply rate is 0.9% and stuff is landing in spam.

All my clients have a 5%+ reply rate and most of it was from doing what I learned as a sales rep over 6 years and not what the talking heads tell you. I learned very quickly that personalization/signals are fantastic but only if it’s RELEVANT. People will put {{JobTitle}} and think that’ll do it.

Overall point here, the people who are doing this the best aren’t sharing their secrets on the internet that would create competition for their business. They purposely put out bad tactics so you fail and then have to pay them to help. Its basic business.

Everyone is optimizing the top of the funnel. Better sequences, more personalization, higher send volume. But the moment a prospect replies, most teams have no real infrastructure for what happens next.

When the outbound actually works, reply volume scales with it. But the reply side is still one person, one inbox, handling it manually. The send infrastructure scales. The reply infrastructure doesn't.

We ran into this ourselves. The outbound was working. Replies were coming in. But the conversion from reply to meeting was inconsistent in a way that had nothing to do with the quality of the leads. It was purely a handling problem.

The reply is the signal. The outbound is just volume.

If you're optimizing send rates but not reply handling, you're spending on the wrong end of the funnel.

What does your team's reply infrastructure actually look like?

Thank you for answering my questions.

Could you please refer me to the best sources for the following. (I received flawed answers from LLMs):

1. ¨These days the real money is in B2B Trade Publication. Search for industries with high ticket products (manufacturing, medical tech, enterprise saas). Usually I find them by looking where the industry leaders are running their whitepaper ads.¨ Where do industry leaders run these ads? (by extension: sponsored articles - how can I find this)?

2. Where can I find databases/ lists of B2B magazines/ journals - not trade journals or commercial magazines?

. How can I find trade journals and/ or writing opportunities through industry associations and conference sponsor lists?

4. Do newsletters pay freelance writers relatively well? Even today? If so, where can I find them?

---

Research shows me none of the old ¨tricks¨ for finding high-paying writing opportunities work today. Even for trade journals. A shrunk market and hyper-saturated. I need to be creative. I plan to approach emerging publications and publications in foreign countries. (Tracking back from bylines no longer works nor do keyword-insertions in LI and the like). Do you have any other supremely creative ideas that i could try?

Every time I consult with founders/entrepreneurs before shipping or product launch, I spend more time on the messaging than every other part of sales.

Why?

Because in sales, messaging has only one goal - to push the prospect to take action - in this case, make a purchase.

One of the first questions I ask before anything is this - is the message framed the exact way the prospect ask talks about the impact online?

The mistake many founders make is thinking that messaging should speak to pain points. That is true though, but only if your goal is visibility or awareness.

If your goal is conversion, your messaging should speak to impact the problem has on the business or outcome of solving the problem as soon as possible. It shouldn't just speak to the impact or outcome, but should speak to it the exact way the prospect talks about it.

Here is an example:

Customer problem:

I am tired of my finance team wasting 15 hours every week manually fixing invoice errors.

Message 1:

We help finance teams automate invoice processing.

Message 2:

We help finance teams process invoices faster and reduce manual errors.

Two different messages speaking to the same problem. However, only one can trigger action and it's definitely not message 1.

Another example.

Customer problem:

I want to stop straining my voice during high notes and sing confidently during solos.

Message 1:

I offer classical voice training for choristers.

Message 2:

I teach choristers how to sing high notes without straining their voice.

To a customer who has the above problem, which message will trigger action?

Same offer. Different messaging.

These are the things that shape sales before outreach even begins.

And no!

They are not new knowledge, they are just not applied.

If I clearly understand what a problem is costing me, I will act faster. If I can vividly see the outcome of solving the problem, objections reduce naturally.

As a matter of fact, the right messaging handles 50% of the sales objection.

Hey folks, I need to get my shit together and build a real outreach list for warm outbound. By that I mean, people I know/have spoken to/have interacted with on LinkedIn/have met with.

I think my data sources for this are:
- Google Takeout calendar exports for 'who I've met with'
- LinkedIn data exports for who I'm connected to and have DM'd or engaged with
- my existing CRM, Hubspot Free plan

Some enrichment will be needed, since those data sets will have to be mashed together in a way that yields contact data I can act on.

The target person I'm looking for here are heads of marketing and the owners of marketing agencies that do social media for their clients, so I'll need some sort of 'business model analyzer', even a rough one, that tells me if either a contact's business offers social media services to their clients, or if the person fits a marketing leadership role at their company.

Questions:

1. I'm on Hubspot Free; are there clear and pressing reasons to not keep this as the main data warehouse?
2. What would you use to enrich? I've used Apollo in the past, and I find Clay expensive and confusing, and I have a QuickEnrich account with a ton of credit on it
3. How, mechanically, do you suggest combining and combing through these data sets? Claude Cowork? Something else?

The end goal is to be able to set up 20-50 meetings from contacting 80-150 people that I have some sort of connection to (fortunately since these are relatively warm relationships, or at least 'not cold', I expect a relatively high response rate; the issue is moreso sorting through my tens of thousands of connections, contacts, and other data sitting in a variety of spreadsheets or in a LinkedIn data dump that I'm awaiting).

Particularly looking forward to hearing from GTM/RevOps people. Oh and for context, the product in this case is a social media management/scheduling tool, with an average subscription fee of ~$30-70/mo on the low end, ~$100-300/mo for small and growing agencies, and $500+/mo for larger agencies (or corporates with many different internal brands/divisions).

Thanks for any help y'all can offer!

P.S. Please no ChatGPT responses, pitch-and-ghost tool mentions, etc... much appreciated.

The agency I work at was recently passing around a recent study from Semrush, and it had some interesting insights for B2B brands. As AI tools become a bigger discovery engine for buyers, execs, and decision-makers, our content isn’t just being consumed by people, it’s being indexed and reinterpreted by LLMs too.

One of the biggest takeaways (and you’re probably already seeing this in your own AI search results): LinkedIn posts, articles, newsletters, and even Reddit threads are some of the most commonly cited formats in AI-generated responses.

This makes a lot of sense for most of our audiences. B2B buyers are increasingly using AI to understand complex topics, compare vendors, research products and solutions and (big one) validate expertise.

That changes how we should tailor our content. It means clearer, upfront positioning, identifiable terminology, POV-led content, and plugging expertise over branded or corporate copy. Employee-generated and exec content has a big role to play too in building brand credibility and thought leadership.

A lot of B2C brands are using this to increase discoverability within platform, but there’s a huge opportunity for B2B brands to show up outside the platform and influence those lower-funner research stages. We’re learning what the balance between “optimizing for engagement” and “optimizing for trust” really looks like.

Curious if others have seen this article (or similar research) and what your thoughts are. How are you integrating AI discoverability into your strategies? While AI remains a hot topic, it might not be a bad idea to start building these strategies early to stay ahead of the curve.

For a long time we thought of gated content as a lead gen mechanic. Fill in the form, get the PDF. Simple transaction.

What changed our thinking was looking at the drop-off data. Lots of people were downloading our gated content and then going completely cold. Unsubscribes, low open rates, no downstream conversion. The content was pulling quantity, not quality.

We reframed it. Instead of thinking about gated content as something we exchange for an email address, we started thinking about it as a digital product we were giving away. That reframe changed how we wrote it, how we positioned it, and how we gated it.

A few specific changes:

The opt-in copy stopped describing the content and started describing the outcome. "Download our enterprise security checklist" became "The checklist our team uses before every client audit." Same asset, different frame. The second one tells you it's been used in practice, which matters to a B2B buyer evaluating whether this is worth their contact details.

We stopped gating everything. The content we gave away freely got read more and shared more, which built more trust than any gated piece was doing. We reserved gating for the genuinely high-effort assets, the ones where a qualified lead would recognize the value immediately.

We added a thank-you page popup instead of a landing page popup. Catching someone right after they've already opted in, when they're already in a receptive mindset, worked better than interrupting them before they'd decided to trust us.

All of this runs through OptinMonster. The URL-based targeting made it easy to set different campaigns for different content types.

Anyone else treating gated content more like a product than a form? Curious what's moved the needle on lead quality for other B2B teams.

Gonna be honest, most SDR model conversations I've been in skip straight to "what's the cost" and never ask what the model actually delivers.

So here are the benchmarks I'd hold any outbound model to before signing anything:

Positive reply rate: 3–6% for technical B2B outbound —> Show rate on booked meetings: 75%+ —> Cost per qualified meeting: $300–$600 —> Pipeline return on SDR spend: 5×–8×

Most providers won't quote you these upfront. That alone tells you something.

Here's how the three main models actually work:

Full-time in-house is the right long-term play, after you've proven the motion. 90 days to source, 60 to ramp, $80–120K/year before a single qualified meeting. Pre-Series B or testing a new segment? You're probably hiring too early.

High-volume agencies work in one situation: simple product, fast SMB buyer, transactional sale. The moment your deal cycle crosses 60 days or your buyer is technical, the model falls apart. You get meetings. You don't get pipeline.

Fractional SDR is what most early-stage B2B tech companies actually need and almost never consider first. Senior rep, modern stack, outreach built on real signals, hiring activity, funding rounds, tech stack shifts. Not mail merge with a first name.

Want the full breakdown? what each model costs, where each one breaks down, and the exact questions to ask any provider before you sign? text here and I'll send it over.

What's your current outbound setup : in-house, agency, fractional, or something else?

putting this down now while the scars are still fresh because i know in 6 months ill convince myself it wasnt that bad and make the same mistakes again at whatever company i end up at next

i joined as the first ops hire at a series A company about 3 years ago. background was marketing ops, mostly HubSpot and Marketo stuff, some Salesforce admin work. the CEO wanted to build an outbound motion from scratch and i figured cold email infrastructure couldnt be that different from marketing automation. that assumption cost us roughly 4 months and somewhere around $14k in wasted spend before things started actually working

the first thing that broke was the most embarrassing one. i set up 8 google workspace accounts, pointed them all at the same domain, loaded them into Smartlead, and started sending the next day. no warmup. i didnt even know warmup was a thing because in marketing ops you send from established domains with years of history and dedicated IPs and all that. within 11 days every single one of those inboxes was hitting spam on gmail. the SDR team was furious because they had been promised pipeline by end of month and i had basically torched our primary domain's reputation. we had to buy a new set of domains, wait 2 weeks for them to age, then do a proper 3 week warmup cycle. so thats 5 weeks of zero outbound because i didnt spend 20 minutes reading about email deliverability before jumping in. the SDR lead and i didnt talk much during that stretch lol

the bigger issue though was data flow. or more accurately the complete absence of any data flow. i had the SDRs pulling contacts manually from LinkedIn Sales Navigator, pasting them into a google sheet, then someone on my team would enrich the emails through Prospeo for enrichment and run verification through ZeroBounce, then paste the verified contacts back into a different sheet, then the SDRs would manually import those into Smartlead. this process took anywhere from 4 to 8 hours per batch depending on list size. the SDRs hated it. they kept skipping the verification step because it was too slow, which meant bounce rates were creeping up to 6-7% on some campaigns, which meant more deliverability problems. i was so focused on getting the tools working individually that i completely missed how the handoffs between them were where everything fell apart. took me about 2 months to realize the problem wasnt any single tool, it was that nothing talked to anything else. we eventually rebuilt the whole pipeline in Clay, pulling from Sales Navigator exports, enriching, verifying through ZeroBounce via API, scoring, and pushing directly into Smartlead through a webhook. that single change probably saved 15-20 hours a week across the team. but those first 2 months of manual copy paste workflows were brutal and the friction between ops and the SDR team got really bad because they saw us as a bottleneck (which... we were)

what really killed us though was the reporting gap. for the first 4 months i had no unified view of anything. Smartlead had send and reply data. HubSpot had deal data. the google sheets had list quality data. nothing connected. the VP of sales would ask me simple questions like "whats our cost per meeting from outbound" and id have to spend 2 hours manually pulling numbers from 3 different systems to give him a number that was probably wrong anyway. we were spending about $2,800/mo across all tools and inboxes (Smartlead at $94/mo, ZeroBounce maybe $40/mo, Clay at $149/mo, plus 12 inboxes through Maildoso at around $4 each, plus Sales Navigator licenses for 3 SDRs, plus ZoomInfo which was like $1,200/mo and honestly i still dont know if we got enough value from that contract). but i couldnt tell you if that $2,800 was generating $28k or $280k in pipeline because the data lived in 5 different places. we eventually built a reporting layer by pushing everything into HubSpot via Clay workflows and some custom API work, tagging each contact with campaign source and enrichment metadata so we could trace a meeting all the way back to which list and which sequence generated it. once we had that visibility we realized that 3 of our 7 active campaigns were producing basically nothing, like sub 0.3% reply rates, and we were able to kill them and reallocate those sends to the sequences that were actually converting at 2.8-3.4% reply rates

oh and one more thing i forgot to mention. inbox management. when we scaled from 8 inboxes to 20 i tried to manage the DNS records and warmup schedules manually in a spreadsheet. missed a DKIM record on 3 of the new domains. didnt catch it for almost 2 weeks. those 3 domains were basically sending unauthenticated email the whole time which tanked their sender scores before they even got through warmup. if youre managing more than like 5 inboxes you need something that handles the DNS setup for you or at minimum you need a checklist that you actually follow every time. i was too proud to use a checklist for something i thought was simple. it wasnt simple

the meta lesson from all of this is that cold email infrastructure is a system not a collection of tools. every tool decision is actually an integration decision. every integration decision is actually a data flow decision. and if you dont think about the data flow first youll end up rebuilding everything 3 months in which is exactly what happened to us

anyway thats the damage report. we're in a much better place now but getting here was way more expensive and painful than it needed to be

Trying to put together a list of who's actually going to be on the floor before I get there. Less interested in the booth crawl and more in finding the teams working on the GTM ops and signal intelligence side of things to have actual conversations with. Anyone know who's attending or already have a list of exhibitors worth paying attention to?

Been researching how businesses get discovered online and it feels like search is changing fast.

Some brands dominate Google Maps.
Some show up consistently in ChatGPT, Gemini, and Perplexity.
Others barely appear anywhere despite offering great services.

From what I’ve seen, visibility now depends a lot on things like:
• Reviews & reputation
• Google Business Profile setup
• Brand mentions online
• Website structure/content
• Local SEO signals
• Consistent positioning across the web

Happy to look at a few businesses in the comments and share what I notice about their Google Maps + AI visibility.

hello hello fellow marketers 👋

On 1st May 2026 I decided to hire my first AI employee or agent in the form of Hermes agent

i tried Openclaw in March but sooner gave up on it because of lack of understanding and I wasn't able to connect it with external tools

But this time I was affirmative to learn and use it

results:

Time saved: 10-15 hours per week

New revenue generated: $0 (assigned tasks do not directly impact revenue)

Tasks I am using it for:

1. Reporting assistant

2. SEO analyst

3. LinkedIn analyst

All in all its great I call it Risebot as it's training on my sessions it will soon be able to make it's own decisions based on guardrails and constraints which means it will be completely Autonomous to act on the analysis that would be crazy to implement

all in all 10/10 recommend it if your job involves reporting sheets, ppts and analysis

for setup coming from a non-technical background was a nightmare but here is what I have tested and working with so far not a single problem faced:

1. Hosted on railway using a template

2. Tg for chat and tg groups for different sessions

3. AllToken (primary) for model routing along with codex and openrouter free models for session titles.

4. Composio or Maton MCP for tool calling

won't say it's rock solid but it has honestly worked great for my use case

free to share your thoughts or setups I will share a step by step setup tutorial if enough marketers are interested :)

Not trying to be negative, but it feels like traditional LinkedIn outreach is getting harder every month. A few months ago we were getting decent replies just from manual prospecting with cold messages, but now the response rates feel much lower even with personalization. Recently started testing a different approach using tools like Clay, Lemlist, satellyte.ai, to focus more on people already active in the niche instead of completely cold prospects. is others are seeing the same thing with LinkedIn prospecting in 2026?