u/cole-interteam

One thing I keep noticing is teams trying to push cold traffic straight into demo requests before the prospect even knows who they are. Then they say LinkedIn doesn’t work because CPLs are high and pipeline quality is inconsistent. In most cases, the issue is the setup, not the platform.

A few patterns I’ve seen repeatedly:

A lot of accounts use the same CTA for every audience. But cold audiences usually respond much better to lower-friction stuff like useful content, webinars, guides, or short demo videos. Demo CTAs tend to work better once there’s already some awareness or intent. Use offers that match the buyer’s stage in the funnel.

Another big one is leaving on things like Audience Expansion or the LinkedIn Audience Network. On paper it increases reach, but in practice it often pushes delivery way outside your actual ICP. On a platform where clicks are expensive, bad targeting gets costly fast.

Retargeting is also usually way too broad. Some accounts retarget basically every visitor the same way instead of focusing on high-intent segments like pricing page visitors, repeat site visitors, or demo drop offs.

And lastly, tracking is probably the biggest issue overall. A lot of teams are optimizing around CPL because attribution between LinkedIn, CRM, and pipeline stages is messy. Once you start optimizing around SQLs, opportunities, and revenue instead of just leads, the platform looks very different.

Would love to hear what other people are seeing with LinkedIn Ads lately. If you have any strategies, targeting setups, or optimization checklists that have worked well for you, drop them below. Might help someone else in the thread too 💪

One thing I keep noticing is teams trying to push cold traffic straight into demo requests before the prospect even knows who they are. Then they say LinkedIn doesn’t work because CPLs are high and pipeline quality is inconsistent. In most cases, the issue is the setup, not the platform.

A few patterns I’ve seen repeatedly:

A lot of accounts use the same CTA for every audience. But cold audiences usually respond much better to lower-friction stuff like useful content, webinars, guides, or short demo videos. Demo CTAs tend to work better once there’s already some awareness or intent. Use offers that match the buyer’s stage in the funnel.

Another big one is leaving on things like Audience Expansion or the LinkedIn Audience Network. On paper it increases reach, but in practice it often pushes delivery way outside your actual ICP. On a platform where clicks are expensive, bad targeting gets costly fast.

Retargeting is also usually way too broad. Some accounts retarget basically every visitor the same way instead of focusing on high-intent segments like pricing page visitors, repeat site visitors, or demo drop offs.

And lastly, tracking is probably the biggest issue overall. A lot of teams are optimizing around CPL because attribution between LinkedIn, CRM, and pipeline stages is messy. Once you start optimizing around SQLs, opportunities, and revenue instead of just leads, the platform looks very different.

Would love to hear what other people are seeing with LinkedIn Ads lately. If you have any strategies, targeting setups, or optimization checklists that have worked well for you, drop them below. Might help someone else in the thread too 💪

A pattern I'm seeing more often are that a lot of funnels that look healthy on the surface are almost always bleeding money underneath. Leads are coming in and dashboards look active but during our audits we always find pipeline quality is weak, attribution is a mess, and nobody knows where the revenue is coming from. We ran into this recently with another client and thought I’d share it here just in case it’s useful to any of you.

Their first instinct was “the ads aren’t working.” But the ads weren’t really the problem. The issue was that every channel was trying to do every job at once. LinkedIn was being used for cold demand gen and retargeting, Google was driving clicks but not qualified intent, retargeting barely existed & follow up after form fills was super inconsistent. So instead of tweaking creatives for the 100th time, we rebuilt the system around buyer intent.

Google handled existing demand, LinkedIn was used for direct access to decision makers, Reddit became a surprisingly good place to test messaging and surface pain points early and retargeting connected all the touchpoints instead of treating each channel separately. After this, performance stabilized pretty quickly.

Then we found something even more interesting. The biggest conversion gains had nothing to do with media buying. There was a broken reCAPTCHA on some devices, the CTA was buried too low on the page and the form had too much friction. That alone moved conversion rate from 9% to 13% without increasing spend. Then we looked at follow up. Leads were just sitting there after converting. So we added instant email response, embedded calendar on confirmation page and a simple nurture sequence and booked meetings started to increase. 

I think a lot of founders and agencies underestimate how much revenue gets lost between stages rather than at the ad level itself. Everyone talks about CAC and creatives but fewer people talk about response speed, handoff friction, attribution gaps, channel roles & conversion bottlenecks. Yes it might be the boring nitty gritty stuff but usually that’s where the real gains are.

Recently I’ve been seeing some of the AI-generated creative coming out of Facebook and it’s gotten pretty wild.

The image variants feel like they’re being pushed in a direction where anything goes as long as it counts as a “variation.” You end up with strange compositions, distorted text, and odd details that don’t really make sense together, like a random teenager holding an IPhone 😅

It’s funny at first glance, but it's also highlighted something more important to me. A lot of platforms right now are clearly optimizing for output at scale. More variations, more options, more automated creative suggestions. The idea is that giving people more choices should lead to better results. But what often happens instead is that quality gets diluted. Good creative usually isn’t the result of randomness like you all know. It comes from intention. There’s usually one clear idea at the center, and everything is designed to support that idea in a way that is easy to understand quickly.

What AI systems tend to do is the opposite. They maximize variation, not what's clear. They explore possibilities, but they don’t really understand which version actually communicates best or feels right for a brand. That’s where the trade off shows up. Speed starts to win over strategy, volume over taste, and automation over real understanding of what makes something effective.

AI can generate infinite variations. But it still can’t replace good judgement. And if anything, this is where brands need to be more careful not less. Because when everything starts to look slightly off, slightly generic, slightly “AI", the brands that stand out will be the ones that feel human on purpose.

So yes, AI isn’t cutting edge anymore, being human is. Use the tools. But don’t outsource your judgment.

How are you guys seeing this play out, especially if you’re working with AI-assisted creative at scale?

Recently I’ve been seeing some of the AI-generated creative coming out of Facebook and it’s gotten pretty wild.

The image variants feel like they’re being pushed in a direction where anything goes as long as it counts as a “variation.” You end up with strange compositions, distorted text, and odd details that don’t really make sense together, like random background characters holding an IPhone 😅

It’s funny at first glance, but it's also highlighted something more important to me. A lot of platforms right now are clearly optimizing for output at scale. More variations, more options, more automated creative suggestions. The idea is that giving people more choices should lead to better results. But what often happens instead is that quality gets diluted. Good creative usually isn’t the result of randomness like you all know. It comes from intention. There’s usually one clear idea at the center, and everything is designed to support that idea in a way that is easy to understand quickly.

What AI systems tend to do is the opposite. They maximize variation, not what's clear. They explore possibilities, but they don’t really understand which version actually communicates best or feels right for a brand. That’s where the trade off shows up. Speed starts to win over strategy, volume over taste, and automation over real understanding of what makes something effective.

AI can generate infinite variations. But it still can’t replace good judgement. And if anything, this is where brands need to be more careful not less. Because when everything starts to look slightly off, slightly generic, slightly “AI", the brands that stand out will be the ones that feel human on purpose.

So yes, AI isn’t cutting edge anymore, being human is. Use the tools. But don’t outsource your judgment.

How are you guys seeing this play out, especially if you’re working with AI-assisted creative at scale?

Everyone in digital marketing loves debating tactics around content. Especially these days when everyone and their grandma has some sort of social channel or platform. They constantly debate post frequency, best posting times, how many hours between posts or what the algorithm likes this month etc and depending on who you ask, all of it is correct. One person says post 3x a day. Another says once every 48 hours or you’ll get suppressed. And weirdly both can be right in their own context. But here's my point. When opposite strategies both work, the variable isn’t the algorithm, it’s the content itself.

Now, caveat: yes, timing, cadence, and platform mechanics absolutely affect distribution. You can have a genuinely strong post that still underperforms because it hit at the wrong time or got buried early. But I feel like most people today get the order wrong. They try to 'solve' distribution before they have something worth distributing. They optimize posting schedules, hooks, formats, and timing…while the actual content is still generic, surface level, or just crap.

And even when they “figure out the algorithm,” it doesn’t save them long term. Because platforms don’t reward impressions, they reward retention, engagement, watch time etc
If people don’t stop, read, watch, or care, the algorithm doesn’t push it farther. It quietly dies after the initial push. So you end up in this loop:

1. Post
2. Low engagement
3. Tweak timing/optimization
4. Still low engagement
5. Assume algorithm issue
6. Repeat.

When the real issue is there’s nothing compelling enough to hold attention in the first place. The common denominator across platforms, niches, and formats is, does the content actually matter to the person seeing it? Does it reflect something real, a pain point, a perspective, an insight, or an experience that feels specific and human? That’s where quality actually lives:

- A POV only you could reasonably have.

- Lived experience instead of recycled advice

- Specificity over general tips

- Personality instead of templated content esp during this AI age.

Once you have that, then distribution starts to matter because now you’re amplifying something worth amplifying. Without that, even perfect timing just means the algorithm ousts your content faster.

So my hot take is: most of the time “algorithm problems” are actually just content problems

I've talked with a couple of companies that had issues with Reddit posts that weren't positive ranking very high on their organic search. Sometimes they're in the second organic spot, so it's a major issue for these companies.

Often the posts aren't even that bad, but there are a couple of lukewarm comments so it's not the best first impression.

Anyways, I'm a PPC guy, so this isn't really my area of expertise, but it's an interesting PR issue, so I thought I'd post and see what others would do.

Have any of you been in this situation? If so, what did you do to resolve it?

If anybody has any insights on why Reddit content ranks so high on some branded keywords that would be great too. It seems like it's maybe industry dependent, I've noticed this in mental health and travel which both have big Reddit followings.

Excited to hear your thoughts!