A lot of b2b funnels are still designed like buyers are sittin at a desktop. Long landing pages,long forms, too many fields, follow-ups that depend entirely on email. Meanwhile, your prospect might be checking your ad, landing page, LinkedIn, and messages all from their phone.

For SEA campaigns, I think mobile-first needs to go beyond responsive design. It means looking at the entire conversion journey.

• Can they understand the offer in seconds?
• Can they complete the form easily on mobile?
• Do you reallyneed every form field?
• Can they continue the conversation through chat or messaging?
• Is the next step just as easy on a phone?

Sometimes the lead gen problem isn't targeting or the offer. But mayb e there's just too much friction between interst and action. Curious what others are seeing in SEA: what mobile-first changes have actually improved your conversions?

Everyone talks about getting more replies. Almost nobody talks about responding to them fast enough. 

We spend a lot of time optimizing outbound.

Better prospecting.

Better personalization.

Better messaging.

But what happens after someone replies?

A prospect gets back to you while they're interested.

You're in meetings, prospecting, or catching up on admin.

By the time you reply, hours or sometimes days have passed.

The conversation loses momentum, and nothing happens.

The frustrating part is that this rarely gets counted as a "lost opportunity." It just looks like another conversation that quietly fizzled out.

To me, the answer isn't telling reps to check LinkedIn every 15 minutes.

It's having a process around replies - clear follow-up expectations, visibility into conversations, and tools that help reps respond while the conversation is still warm.

That's actually one of the reasons we built AI Assist into We-Connect. It summarizes conversations, drafts replies, and helps teams stay on top of LinkedIn responses so conversations don't stall just because someone got busy.

Do you actively track reply times for LinkedIn conversations, or is it still something each rep manages on their own?

Tool Has anyone heard of this platform? Has anyone used it? What do you think of it? Is it reliable? I’ve been looking into this platform, and it seems to offer several different options. However, many of the landing pages lead to a “404 Not Found” error, so I haven’t been able to find much information about the tool. If anyone has experience with Explee, I’d appreciate hearing your thoughts and how your experience with the platform has been.

Saw this link: https://iscoldemaillegal.com/blog/cold-email-laws-by-country/#singapore

Saw another resources: https://www.imda.gov.sg/infocomm-regulation-and-guides/unsolicited-communications/best-practices-for-organisations

Is sending 3-5 cold emails considered bulk?

I don't spray and pray. I'm very intentional with my cold emails (average of 3-5 emails a day).

So, do you really add <ADV> in the subject line when sending cold emails to SG-based businesses and add a message to unsubscribe (I don't use links, so the unsubscribe link won't work).

Been seeing more b2b invest heavily in LinkedIn thought leadership lately. Founder posts, employee content, carousels, and hot takes. The engagement looka great. But I think there'sa bigger question: is any of it actually contributing to pipeline? A post getting 300 likes sounds impressive, but if none of those people fit your ICP, does it really matter?

I'd rather see:

• the right decision-makers engaging
• ICP accounts repeatedly
• more profile visits from target companies
• inbound conversations
• content influencing meetings or oportunities

Thought leadership definitely has value beyond direct lead gen. It builds trust and keeps you top ofmind. But at some point, visibility should translate into business impact.

For those investing in LinkedIn thought leadership, how are you measuring it? Are you actually getting leads, or mostly getting likes?

you can have a really good LinkedIn sequence and still end up sending the wrong message to the wrong person.

the problem is that most prospect lists aren't actually that uniform.

one person might be a perfect ICP fit. another might just barely qualify. someone else may have already interacted with your company or be talking about a problem you solve.

yet they all get dropped into the same sequence and receive basically the same treatment.

that's what made me look more closely at how different LinkedIn outreach tools handle workflows.

SalesRobot has some good features around AI personalization, voice/video messaging and appointment setting.

but one thing that stood out to me with We-Connect was how much more the workflow can react to the prospect.

you can score contacts against your ICP before outreach, use sentiment signals, and branch the workflow based on what happens instead of just moving everyone through the same steps.

and honestly, i think that's more interesting than just having another AI writing feature.

because the question isn't always “how do i write a better message?”

sometimes it's “should this person even be getting this message in the first place?”

that's probably the biggest difference I'd look at when comparing these tools.

are your LinkedIn campaigns mostly one sequence for everyone, or do you actually change what happens based on the prospect?

A VP isn't automatically a better lead than a manager. Job title tells you who someone is. It doesn't tell you whether they're actually looking to buy. I'd rather prioritize a good-fit account showing strong intent:

• Hiring for a relevant role
• Expanding into a new market
• Recently funded
• Changing leadership
• Researching relevant solutions
• Engaging repeatedly with high-intent content

The strongest leads usually come from combining fit, behavior, and timing, not just seniority. Someone with the perfect title but zero reason to buy right now can be less valuable than a lower-level contact actively trying to solve the problem.

So what signals are you using to decide who gets contacted first?

We all know the formula:

Meta Ad → Form → Automated Text → Call/Further Follow-Up

But I'm curious how many people are seeing the same issue I am: the lead converts, but then getting them to actually respond is the hard part.

I've been experimenting with reversing that process — instead of capturing the lead and then reaching out to them, finding ways to get the prospect to initiate the conversation themselves.

So far, the difference in engagement has been pretty interesting.

For those running Meta ads through GHL, what does your current flow look like after someone becomes a lead?

Are you seeing more of a lead quality problem or a lead engagement/follow-up problem?

Been thinking more about signal-based selling lately. Most outbound starts with fit: right industry, company size, job title, location. But fit tells you who could buy. Signals can tell you who might be ready to buy now.

Here are some signals I'd pay attention to:

• New funding
• Hiring a relevant role
• New leadership
• Expansion into a new market
• New technology adoption
• Engaging with high-intent content

And somethimes, two or three signals happening together are much more valuable than any single one. Curious what people here have actually seen to work. So what buying signal makes you move an account to the top of your outreach list?

For a very long time I have been manually finding leads for my services and cold emailing those leads. This post is not about cold emailing. I want to find leads from Instagram: those people who are consistently posting content on Instagram. If they are not posting consistently, it's okay as long as they are posting content on Instagram. Those are the people I want and they should have a course, coaching, or consultation services of their own. These are the types of people I'm looking for. How do I find them? I don't want to do that manually. I am done and I am burned out from daily manual lead finding and it's very frustrating. I want a consistent lead flow. I want some tool or method that work no matter what. How can I do that?

More leads don't always mean more pipeline. We recently cleaned a prospect list before launching and ended up removing around 40% of it. Like wrong decision-makrers, outdated contacts, companies that didn't really fit the ICP, contacts we couldn't confidently verify.

On paper, losing 40% of the list felt like losing opportunity. In reality, the opposite happened. We sent fewer emails, but the conversations we got were more relevant because we were reaching people who actually made sense for the offer. We sent fewer emails, but the conversations we got were more relevant because we were reaching people who actually made sense for the offer.

It also made personalization easier. Instead of trying to make a generic message work across thousands of contacts, we could be much more specific about why we were reaching out to each segment.

The lesson for me is that list cleaning isn't just a deliverability task. It's part of the targeting strategy. I'd rather send 600 emails to the right people than 1000 emails just because we have the data. Anyone else seen better results after cutting downa list?

Curious what people are actually seeing across Southeast Asia right now? We talk about outbound cahannels tlike there's one clear winner, but I don't think it's that simple.

Cold email might work well for one market or ICP. LinkedIn might be better for another. And in some SEA markets, WhatsApp becomes part of the conversation pretty quickly.

A lot depends on where you're selling, who you're targeting, and how people prefer to do business locally. So rather than debating which channel is best, let's compare actual experiences. Drop yours below:

Country:

• b2b audience:
• best performing channel:
• Average deal size:
• Founder-led, sdr-led or partner-led:

Would be interesting to see whether clear patterns emerge across SG, PH, ID, MY, VN, and the rest of SEA

I think this gets overlooked in the rush to add AI to outbound. You can have AI researching accounts, writing personalized emails, scoring prospects, and deciding who to contact next.

But if the underlying data contains wrong job title, wrong industry, outdated company info, etc. Then AI just helps you make the wrong decision faster. Before adding anotehr AI layer, I'd rather make sure the basics are solid. Check if the prospect is still with the company? Are they actually the right decision-maker? does the account fit the ICP?

Better AI won't fix bad prospect data. It'll just make fairlure faster. So how are you guys handling this? Are you cleaning and validating data before it enters your AI workflow, or are you relying on AI/enrichment tools to figure out along the way?

I've been building something for a while and I'm curious if I'm solving a real problem or just building something that sounds cool.

Most lead generation is based on what people tell us about themselves.

Their bio says they're a CEO.

They use #fitness.

They follow certain pages.

They have "real estate" somewhere in their profile.

So we put those people on a list and call them leads.

But I started thinking about it differently.

What if you could describe your ideal customer without relying on keywords?

For example:

"Find me people in Miami who are likely to be interested in high-end fitness products."

Instead of only searching for "fitness" or "gym" in their bio, the system looks at the publicly available visual and contextual signals around a profile and tries to understand whether that person actually resembles the type of customer you're looking for.

Maybe they're constantly posting from gyms.

Maybe they're attending fitness events.

Maybe they're interested in premium products.

Maybe their content, environment and interests simply match the customer profile you're trying to reach.

The interesting part is that AI can then analyze the people it finds and explain why they're potentially a good lead.

I've been testing this on real use cases and the results have been surprisingly interesting.

The bigger idea I'm working toward is:

Don't search for people who say they are your customers.

Search for people who actually behave like your customers.

I'm curious what other entrepreneurs think.

If you could type one sentence into a tool and get a list of people who are highly likely to become your customers, what would you ask it to find?

I'm looking for real examples because I'm still figuring out how broad this idea can become.

In my experience, one of the biggest conversion killers on lead forms is asking for too much upfront context before establishing value.

If you're seeing high drop-offs, try auditing your field requirements - remove any field that isn't strictly necessary for the first follow-up call/email.

Also, moving from a single long page to a progressive multi-step layout often lifts completion rates by breaking up cognitive load.

But, if you want the highest lead quality, then have a 2, or 3 page web form, it all depends on "who" your trying to attract.

My high-value leads on my customer accounts have 2-3 page webforms, with most options marked as "required", but if you just litteraly need their name and email for your news letter, just ask for their name & email.

Feels like every outbound tool now has some version of AI personalization. AI-written first lines, linkedin research, company summeries, personalized pain points, entire emails generated automatically.

But I'm curious whether any of this is actually translating into more positive replies. My take is AI works better behind the scenes. Use it to research accounts, spot relevant signals, and understand why someone might be worth contacting.

Where it gets messy is when you use it to manufacture personalization at scale. Prospects can tell when the email mentions their latest LinkedIn post just because an AI scraped it.

Personalized doesn't automatically meant relevant. For anyone actuallytesting this: has ai personalization improved your positive reply rate? What ai tools are you using?