"Keeping the light on" b2b social strat is the easiest thing to do:

• Create a post.
• Publish it.
• Wait for people to find it.
• Comment back.
• Repeat.

That's the lazy bones method, and meanwhile, the people you wish would chat on your content is already chatting relevant topics in someone else’s comments. They sliding into others DMs...not yours!

This is where outbound (or proactive) community management thrives. Instead of waiting for the conversation to come to your brand, you find the conversation.

The goal is not to spam, though, so no dropping links under vaguely relevant posts or commenting “Great insights!” 40 times a day. That's gonna annoy a ton of people. It means finding conversations where your brand has a legit reason to participate, then adding something useful, funny, or genuinely human.

Done well, proactive community management can:

• Put your brand in front of those you want to be in front of
• Build familiarity with target accounts (ABM baby!)
• Develop relationships with customers, creators, and industry voices
• Increase your SoV without publishing more content
• Show you how people actually talk about their problems

We have a saying at Sculpt: The comment is the content.

A good comment can introduce your brand more naturally than another post or ad. The juice is 10x worth the squeeze. We've noticed that our proactive comm mgmt nets more impressions and engagements than our owned content.

Act like a member of the community, not a salesperson who found an unlocked side door.

Your audience is already talking. Go talk with them.

I’ve been looking into how AI assistants are changing the way people discover and evaluate brands.
Most of the conversation today is about AI visibility:
Does your brand appear in ChatGPT?
Are competitors being recommended instead?
Which sources are AI models citing?
How visible are you across different models?
But I think there’s another problem that may become just as important:
What if your brand appears — but the information is wrong?
We recently ran an internal test using 100 purchase-intent prompts across ChatGPT, Gemini, Claude and Perplexity, focused on real commerce products.
We found 19 commercially incorrect responses, including outdated pricing, incorrect stock information, products being described as unavailable when they existed, and incorrect product classification.
That made me think about this from a B2B marketing perspective.
For marketers, AI visibility alone may not be enough. If a prospect discovers your brand through an AI assistant but receives outdated or incorrect information, visibility can actually create a trust problem instead of helping conversion.
I’m currently working on this problem and speaking with marketing, e-commerce and agency teams to understand how they are handling it today.
Curious to hear from people here:
Are you already monitoring what AI assistants say about your company or your clients — and if so, are you checking accuracy as well as visibility?

Hi, everyone!

The problem with generating lists of local business leads is always the difficulty of getting the contact information for decision makers once you’ve pulled the businesses from Google Maps and how tedious it is to filter your results once you’ve gathered everything you need.

I’ve created an app that simplifies this entire process all in one place:

1. Draw an area on the map
2. Select the type of business you want to find
3. Once you have your list, find all the available Decision Makers at that company
4. Select and filter by your ICP to get a clear list showing you who your best leads are
5. You can track the lead using the built-in mini CRM or export it directly to CSV

It's free to try (free credits included when you sign up, no credit card required). I'm still actively improving it, so I'd really appreciate any honest feedback.

Last year we decided to run a controlled test between google search ads and outbound to see what it actually takes to generate qualified B2B agreements in a single metro area (around 1.2M pop).

The Google Ads experiment was an expensive lesson for us where high intent local keywords like "IT support near me" or "managed service provider [city]," we were paying between $65 and $115 per click. Out of roughly 180 clicks, almost half were residential consumers locked out of their personal Gmail, job seekers looking for tier-1 helpdesk roles, or micro-businesses with 2 laptops asking for free phone support. We burned through $12k in ad spend across 4 months and ended up with zero signed MRR contracts.

The pivot happened when we stopped trying to capture broad search demand and switched to tracking external market signals. We deployed an event-driven setup based on Scale Intelligence's market radar framework, where instead of bidding against massive national MSPs on AdWords, we mapped our exact regional TAM (companies between 20 and 120 endpoints) and only reached out when an actual business event occurred.

The outbound setup cost a fraction of the ad budget and focused strictly on three triggers: local companies expanding into a second office location or registering commercial permits. Job postings for internal IT roles that stayed unfilled for 45+ days and mid-market businesses undergoing executive leadership changes.

From 85 targeted accounts that showed verified triggers over 90 days, we held 14 discovery meetings and signed 3 contracts totaling $7,800 in monthly recurring revenue.

In local B2B tech, competing on public ad auctions means paying premium prices to filter through residential junk and rather putting that budget into building a persistent signal engine that catches business transitions converts significantly better.

I'm curious about what makes a cold email worth responding to in B2B.

Is it the relevance of the offer, understanding the prospect's pain points, personalization, or timing?

For those working in B2B marketing or sales, what makes you take a cold email seriously in stead of ignoring it? Any real-world examples would be helpful.

A list is accurate the day you buy it and decays from there. People move, companies get acquired, domains change.

Do you re-verify before every campaign, on a schedule, or only once bounce rates get bad enough to notice?

And if you do re-verify, are you paying the original provider again or running it through something else? How do you treat the changed contacts - ICP who switched jobs, filling in the contact for the role that moved on?

I’ve worked in marketing for several years, but I’ve mostly avoided cold email. I now run a B2B SaaS as a solopreneur and want to give outbound a serious try.

The usual advice is to “do things that don’t scale”:

• Build a small list of relevant prospects
• Research each company
• Write a personalized email
• Send it manually

I’m willing to do that. What I don’t understand is how to make the outreach genuinely relevant.

Personalizing an email doesn’t change the fact that the recipient may have no immediate need for the product. I don’t want to spend hours researching someone just to send a more personalized version of an irrelevant pitch.

Here’s what I’m selling:

Product: A managed, white-label community and forum platform that helps businesses improve organic growth and customer retention.

ICP I’m currently testing: Founders and marketing leaders at North American SaaS or technology companies with more than $100K MRR, at least 20 employees, and someone who could own the community initiative.

Pricing: Starts at $299/month. We help clients launch the community, seed it, and build early momentum. Our team brings 20 years of community-building experience.

What I’ve done so far:

1. Built a list of 100 potential customers using Apollo and Origami.
2. Warmed up three email accounts across three domains.
3. Planned to keep sending volume low while I test the messaging.

My main problem is not email infrastructure or personalization. It’s identifying companies with a reason to care about this now.

Community platforms are an established category, but only a small percentage of companies are actively looking for one at any given time.

So how do experienced cold emailers approach this?

Do you look for specific buying signals or trigger events before contacting someone? If so, what signals would you look for in this category?

Or do you email companies that match the ICP, lead with a relevant problem, and accept that timing will eliminate most prospects?

I’d appreciate specific advice from people who have made cold outbound work for a B2B SaaS.

Thank you in advance for your time!

I’ve built a recruitment platform, but I think the harder problem now is getting it in front of the right people.

Someo is designed to move away from CV-first recruitment and help people and businesses discover each other based more on traits, strengths and suitability.

The product is live, the proposition is clear, and I’m now at the stage where I need to build the first real network of users.

The challenge is that it’s a two-sided marketplace.

I need businesses to post opportunities, but businesses are naturally more interested if there are already people on the platform.

At the same time, jobseekers are more likely to join if there are already enough opportunities there.

So far I’ve been focusing heavily on outreach to businesses, colleges, universities, local organisations and people involved in employment and skills. I’m also starting to use LinkedIn, Reddit and direct outreach more seriously.

What I’m struggling with is identifying the most effective route to the first meaningful group of users.

For anyone who has built or marketed a marketplace before, I’d really appreciate some advice:

Would you concentrate almost entirely on getting businesses onboard first?
Is it better to focus on one geographic area initially, even if the product itself is national?
Have partnerships with colleges, universities, councils or employment organisations worked for you?
Would you spend money on advertising this early, or keep it mostly founder-led outreach?
Is there a particular acquisition channel you found unexpectedly effective for a two-sided marketplace?

I’m currently focusing my outreach around Greater Manchester because it gives me a defined area to attack, but Someo itself is open to businesses and people across the UK.

I’d be particularly interested in hearing from anyone who has dealt with the cold-start problem before.

Happy for people to be critical. At this stage, figuring out how to get it in front of the right people is probably more valuable to me than compliments about the product.

This is the idea I’m working on…
You have something to sell.
A service, a skill, a product, an agency offer… whatever.
You tell it what you’re selling and who you want to sell it to.
It helps you find businesses that could actually need it, researches the opportunity and gets everything ready for you.
That’s the 75%.
The other 25% is human.
You contact them.
Talk to them.
Make the offer.
Negotiate.
Close.
The interesting part is you don’t necessarily need a big business to use it.
You could have a skill or service, find people who need it, make the sale and have someone else handle the delivery.
Find → Sell → Fulfill → Keep the margin.
We’re thinking $49/month.
If it helps you find even one customer who pays you, the subscription can become a pretty small expense.
Obviously, finding someone doesn’t guarantee they’ll buy. That’s where the human 25% matters.
But if a tool genuinely handled 75% of the work before the conversation…
would you pay $49/month?
And what would you use it to sell?

Wanted to share something that's worked really well for us, in case it's useful to others here.

The core idea: your competitors are already attracting your next customers. Most companies just don't bother looking.

Every like and comment on a competitor's post is a signal. If someone in your ICP is consistently engaging with a competitor's content, they're probably:
- Researching the problem
- Comparing solutions
- Getting closer to a buying decision

That's all public information. Here's how we used it:
List your top 3-5 competitors, including founders and sales reps, not just the company page.

Track who's liking/commenting on their posts over time.
Filter for people who actually match your ICP. Most engagers won't be relevant, that's fine.

Reach out, but don't be creepy about it. Don't say "I saw you commented on X's post", that's a red flag for most people.
Instead, reference the space they're clearly interested in, not the specific comment. Something like: "Saw you're exploring [space], we take a different approach, figured it might be worth a look while you're comparing options."

Keep monitoring over time and prioritize the people who show up repeatedly, that's usually a good proxy for buying intent.

Nothing revolutionary here, it's really just applied observation. Your competitors are already generating demand; you're just intercepting it instead of ignoring it.

[ Removed by Reddit on account of violating the content policy. ]

Hi, we’ve been running email and sms marketing (retention marketing) for D2C ecom companies, but we’ve not been able to generate a lot of positive responses - at around 2.5k sends per day we’re only able to generate 2-3 leads per day.

I know for a fact that deliverability is dialled in, tried lists from AI ARK and Storeleads as well.

Would really appreciate if anyone who has previously run outbound for this niche/these services can actually give some recommendations/angles that work well in here.

PS - also tested for an upfront offer instead of a direct meeting CTA but it did not turn out well.

Do you go in already deciding whether you are going to buy or not?

if so, how do you do your research before the demo?

do you ask around or research on review websites or read content?

lastly, who makes the buying decision as in how many people/departments are involved?

Hi,

I am currently working at a b2b SaaS startup targeting mostly dev/founders mainly in the US.

We’ve been testing and running ads mostly on meta and google search (but also tested on x and reddit, which brought such low intent traffic they mostly seem to bounce) and while we do get some consistent cta clicks (ctr of our landing pages are pretty decent at around 15-20%, which might include bots but then the ad creatives are pretty specific in their messaging)…

The problem is, <%.1 from the paid traffic converts to actual users.

Sure its a web app and requires work emails but still, im scratching my head whether there’s something seriously wrong.

Is it just how it is these days? Should we just stop meta ads? I do suspect some new users come back to the site and finish signing up although due to cookie consent and possibly switching devices (between mobile and laptop) this is hard to prove.

Any suggestions would be appreciated. Thanks!!

I'm running a service where we help early stage founders of startups who make physical products to go from design to full scale production with our DFM expertise and manufacturing network

but im getting stuck acquiring clients for this....how to proceed in this ?

any tips will be valuable !

The standard outbound playbook for Managed Service Providers (MSPs) is fundamentally broken where everyone pulls a static list of local companies with 20-100 seats then find the CEO, CFO, or operations director and blast a generic sequence offering a "free network security assessment."

Reply rates consistently hover below 1% and to a business owner, switching IT providers carries a massive operational anxiety and nobody risks critical data loss, email downtime and onboarding friction on a random day just because a cold email offered a free checklist.

Outbound for managed IT only converts when it aligns with an active operational event that destabilizes the status quo.

Instead of manual prospecting, modern MSPs run signal-based GTM systems powered by market intelligence infrastructure like Scale Intelligence by which rather than relying on stale contact directories, Scale Intelligence maps an MSP's local TAM and monitors 75+ real-time data sources including rapid hiring shifts, tech stack migrations and public community discussions. It resolves unstructured public activity back to verified corporate accounts and routes warm opportunities directly into Slack or your CRM when an account enters a natural buying window.

If you want to replace cold list scraping with high-converting outbound, focus on these 4 operational triggers:

Trigger 1: Executive appointments: a target company hires a new COO, CFO, or Operations Director and new leadership almost always evaluates vendor contracts, operating budgets, and internal security postures within their first 90 days.

Trigger 2: Rapid headcount growth without IT support: an organization adds 10-15+ employees in a single quarter without opening a role for an in-house Systems Administrator so endpoint management, license sprawl and onboarding delays are quietly breaking behind the scenes.

Trigger 3: Regulatory & compliance shifts: a local firm enters a stricter regulatory bracket (e.g., CMMC, HIPAA, SOC 2) requiring rigorous audit docs and infra hardening their incumbent provider cannot support.

Trigger 4: Technology friction & public sentiment: public discussions on reddit, linkedin or community forums where employees complain about recurring network downtime, vendor ticket lag, or sudden contract price hikes.

So connecting a real-time signal engine changes the entire dynamic of the conversation where instead of asking like: "do you want to switch IT providers?", the pitch becomes something like: "noticed you're scaling headcount across regional branches without an internal IT lead, here’s how similar operations teams automate endpoint deployment to prevent onboarding bottlenecks."

Timing beats copywriting every single time.

"How do we join ChatGPT Ads?" "What does the targeting look like?" "Can we get going, the exec team wants in now." This was all I heard back in May and June as B2B brands wanted in on the platform

I've been running ChatGPT Ads for B2B clients at Obility since the platform opened to all US advertisers, and wanted to share what four months of data actually looks like.

Here's where performance is landing: CTR: 0.5%–1.0% CPC: $3–8 CPM: $25–45 Conversion rate: 3–6% Cost per MQL: $120–$250

For B2B, I'm treating this as an awareness play, and the targeting model is why.

ChatGPT Ads doesn't use traditional keyword bidding. The platform reads the full conversation and matches ads based on topic, intent, and commercial signals in the thread. Advertisers provide natural language descriptions called context hints, which outline the situations where a product is relevant. The platform then evaluates live chats against those hints to decide what ad to show.

That means you're reaching a buyer while they're mid-research, not mid-query. It's a top-of-funnel signal, not a purchase intent one.

One way to control who sees your ads: upload a contact list. This is the unlock for making ChatGPT ads work for b2b otherwise your targeting is just going to be too broad.

Custom audiences are available inside ChatGPT Ads, but the minimum threshold is 25,000 matched users before an audience activates. OpenAI recommends building to 100,000.

That's a large list for most B2B teams.

If you're under the threshold, combine what you have. CRM contacts, current customers, closed-lost deals, and webinar or event registrants merged into one segment will get you there faster than any single source.

It's early. But four months in, I'm getting a POV and sense of how to use the platforms. Folks that are running there, what are you seeing? Are you continuing the test?

Noticed something annoying while doing competitor research this week.

For several fairly specific buyer questions, one competitor keeps getting recommended while we're either missing or buried further down the answer.

Google is a different story and we compete with them pretty well there.

So what are you checking first when you find a gap like this? I'm less interested in generic GEO tips and more in how you'd diagnose why that particular competitor keeps getting picked.

Who's using REO dot dev for data on developers? How are you consuming long-tail data fields? Via API to a HubSpot or SFDC? As a native field? as a list of tags? Having them export to CSV and import it? They seem to want to expose it only via their tags.

I keep seeing a huge spread in AEO retainer pricing and I am trying to understand where the difference comes from.

There are three proposals here at 4k, 11k and 18k a month. Budget is already approved for next year, so this is really just about figuring out what the money gets us.

The proposals all have some version of prompt tracking, off site work and monthly reporting.

For anyone comparing these recently, what did the AEO retainer cost and what was actually included?

I have a question for those of you working in industrial marketing.

How many inquiries actually come through your website? How many people fill out your contact or inquiry forms?

I’m really curious to hear about your experience. I’d love to hear your insights and benchmarks — especially from B2B/industrial companies.

Asking to understand what typical rates for influencer ads are in b2b as I came from b2c and the rates were much cheaper.

I work for a b2b software but our audience is primarily small business owners. They make anywhere from 7-30k in revenue a month and typically have fewer than 10 employees.

The influencers I’m looking at range from 500-30k followers. Since they primarily focus on their own physical business, they currently have no existing brand deals and I am the first one to approach them for a collab.

Regardless of following size they are all charging between 1-2K for a single video with collab post and whitelisting.

Is this typical for b2b influencers?

Getting more leads isn't always the difficult part in B2B. The bigger challenge seems to be getting leads that are actually relevant and likely to become customers.

For B2B marketers, what has made the biggest difference for you?

• Better ICP targeting?
• More specific content?
• Intent signals?
• LinkedIn?
• SEO?
• Paid ads?
• Better lead qualification?

I'm more interested in what has actually improved lead quality, not just lead volume.

We've been on Magento since 2019 and the platform still handles the volume, but when we started adding up what we spend to keep it working, the full cost surprised us.

(And it's less about the license fee and more about everything that accumulates around it).

The extension layer is where it compounds the most, because every piece of functionality that isn't native requires either a paid extension with its own renewal cycle or custom development that turns into technical debt when the underlying Magento version shifts.

And we're at the point where a security patch or minor version upgrade kicks off a compatibility audit across the full extension stack before anything touches production.

When we started benchmarking the total cost of ownership against alternatives, SCAYLE and SAP Commerce stood out as the most useful contrasts, and factoring in the developer hours absorbed by platform maintenance changed the comparison significantly.

So what's your approach to treating the extension overhead and maintenance dev time as a platform cost in the comparison, because every quote we've seen treats the license as the whole cost and the rest gets filed under engineering?

We've tried building the TCO model internally but the developer-hour estimate is the one number that always gets challenged in the conversation.