Co-Founder @ Omni Lab | Paid Media for B2B SaaS brands

Over the last 15+ years, I've worked for 4 VC backed SaaS companies, consulted with more than 100+, helped 1 get acquired, 1 reach unicorn status, and many more generate millions in net new revenue.

I've also seen a handful of those startups go out of business...including my own SaaS business so I know many of the mistakes. 

Over that time I've noticed that the buyer's journey has evolved. 

Today buyers have the power.

Yet, many SaaS businesses still continue to run the same programs that worked a decade ago. 

They continue to over-rely on lead gen and create friction in the buying process. 

This is pushing customer acquisition costs sky high and causing many to miss their targets. 

The way forward is to take a buyer-centric approach to creating and capturing demand. 

Buyer-centric demand gen is when your funnel aligns with how the buyer wants to learn about your company. 

It means you write in the language your buyer understands, you consider how they consume information, and when and how they want to buy. 

When you take a buyer-centric approach you generate more pipeline and revenue and an enduring brand. 

This is why we started Omni Lab.

------------------------------------------------------------

What we do for Series A to Series C SaaS startups:

→ Manage and optimize paid media across any digital channel
→ Distribute content/messaging via paid to grow pipeline and revenue
→ Build out engaging ad creative
→ Focus on optimizing the funnel based on pipeline and revenue. 

Results from SaaS companies we have worked with: 

→ Unicorn Status in 10 months
→ Grew pipeline 372% and lead > opp rate 266%
→ 1,300% increase in revenue Q3 > Q4
→ 20% increase in revenue Q over Q

If you are looking to create and capture demand via paid media, let's chat :) 

email: jonathan@omnilabconsulting.com or DM me

Jonathan Bland

Guess which channel is the 2nd-most referenced by LLMs like ChatGPT?

Reddit?

Google?

Nope, it was LinkedIn. 

Semrush analyzed 230,000 prompts across ChatGPT, Google AI Mode, and Perplexity over a 13-week period and found a sharp shift in AI citation patterns.

In mid-September, ChatGPT dramatically reduced citations to Reddit and Wikipedia. But one domain moved in the opposite direction: LinkedIn.

LinkedIn showed a steady rise across all three platforms. Google’s AI Mode cited LinkedIn in nearly 15% of responses throughout the quarter, and both ChatGPT and Perplexity trended upward after the Reddit/Wikipedia drop. 

In some cases, LinkedIn appears to have absorbed the citation share that those domains lost.

What does that mean for you?

If LinkedIn is becoming a more trusted source across AI systems, that has strategic implications:

- Executive thought leadership may carry more distribution weight
- Expert-driven content could influence AI answers
- Authority on LinkedIn extends beyond the feed into AI-generated responses

The brands and individuals shaping conversations on LinkedIn may also be shaping how AI systems answer category-level questions.

So, for you, that means thinking about some of the big questions people ask LLMs as they relate to your product category, and creating content around them. 

Pretttyyyyy interestingggg. 

I'll drop the link below.

Co-Founder @ Omni Lab | Paid Media for B2B SaaS brands (HIRING)

7 Hard Truths for B2B Marketers

1.) PEOPLE DON'T BUY IN LINEAR PATHS
Gartner, Google, MTA tools and many others have already shown how many touches make up the buyers journey. People don’t experience your brand in channels.

2.) YOUR GOOGLE ADS DEPENDENCY IS HURTING YOUR BOTTOM-LINE
CTR is down, CPC is up, and people are short-listing brands before they go to Google. You need to build brand preference to capture demand more efficiently. 

3.) GATING CONTENT RESTRICTS CONSUMPTION 
People consume short-form content before they invest time in-long form content. 

4.) FOCUS ON PERSONAL PROFILES, NOT BUSINESS PROFILES
People want to make a connection with someone (Founder/SME) at the company, not build a relationship with the company. 

5.) ATTRIBUTION IS A GUIDE, NOT A DECISION MANUAL
If a UTM parameter has to be appended, you are very limited in the tactics/strategies you can use. 

6.) BETTER TO REACH 1,000 ACCOUNTS ONCE vs. 10 ACCOUNTS 10 TIMES
Data from EBB and LI B2B Institute show reach is more important than high frequency against narrow audiences. 

7.) BUYERS HAVE WAY MORE CONTROL AND ACCESS TO INFORMATION ABOUT YOUR BRAND
They can find your pricing, see your product off your website, read reviews whether you want them to or not. Control the narrative and get that information in rented channels where they spend time.

Anything missing?

I thought this post from Sam Kuehnle was pretty spot on...

This is what stood out.

"Somewhere in this process, our intuitive understanding of how buyers (and ourselves) actually behave when making purchase decisions (AKA non-linear, messy, multiple people involved) got buried under the accumulated weight of common practice (AKA linear funnels, sequenced campaigns, decision-maker is also the end user)"

I'm sure most Heads of Marketing would nod and agree to what he said, but then find themselves in the same difficult conversations with their CEO or board, trying to help them understand the impact of their investment. 

Often, we want to show data, present a logical path, and share information to convince someone that our way is the best. 

However, as Sam points out, an additional path might be to ask some really good qualitative questions to get them thinking and to come to their own conclusions. 

For example:

"Tell me about the last purchase you made for the business. What brought it to your attention? How did you go about the path to purchase?"

Or I'd even add a few more: 

- "How long did it take our best customers to decide to buy?"
- "Do we expect finance, product, or hiring decisions to show clean cause-and-effect within 30-60 days?"
- "If we only invested in activities we could perfectly measure short-term, what would we stop doing?"
- "When a prospect converts, how confident are we that the last click was the real driver? 
- "If someone hears about us on a podcast, sees a LinkedIn post, then Googles us and converts, what deserves credit?"

You don't need to ask these questions in a defensive way to prove your point. 

It's more about getting a good conversation going so that both sides understand how to make the best decision.

👏 again on this post!

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Omni Lab 

Snapdata, in the business of waste and recycling analytics, was selected to participate in NUMA's Smart City Program in Paris to connect with corporate leaders like Cisco, Suez, and City of Paris Government to discuss innovative solutions for cities. Out of 200 startups, we were one of 4 selected to participate. 

Google Exchange Program Finalist - NUMA; Paris

Ogilvy partnered with IE Business School to invite IE based startups to pitch their ideas to Ogilvy to compete in getting the chance to have Ogilvy support their branding & marketing needs as well as partnering with some of their clients to bring about new innovation. 

Ogilvy Competition, Top 3 Startups

Achieving outstanding performance during the IE Business School Startup Lab. Voted best Startup to invest in. 

Investors' Award

Small team of marketing professionals at IE Business School were tasked to develop a new marketing strategy for a SMB company called DriveGum. DriveGum distributes and manufactures CPG goods like gum, granola bars, and others in Europe. We:

•	Repositioned the key value proposition.
•	Created three new strategies to grow brand recognition and improve sales.
•	Made improvements and updates to current marketing material. 




IE Business School - Marketing Case Competition, Finalists

James Madison University Austin Alumni Chapter

Managing Director

Snapdata designs and develops a range of sensors and data analytics platforms for the Internet of Things.

Primarily responsible for European operations developing a go to market strategy and doing business development in the waste and recycling sector.

Confirmed 3 letter of intents with governments and corporate size clients to test our product. 

Developed pricing matrixes for products and services, ROI for our clients, and detailed process for proof of concepts. 

Managed Google AdWords campaigns and analyzed Google Analytics to improve our messaging and positioning. 

Won four separate competitions for leading innovative technology and startup in Spain:

Venture Day Finalist, IE Business School
Investors Award, IE Business School
Google Exchange Program Finalist, NUMA 
Top 3 Startups, Ogilvy


Snapdata

Learn how Omni Lab helps 100+ B2B SaaS brands create and capture demand with paid ads.

Book a Call

I’ve been writing on LinkedIn for around 5 years now, which is wild to think about. 

Contrary to what all the LI creators say, I had no plan, no goal, and no topic. 

I posted random Einstein quotes, random personal photos, and observations with no clear theme. 

I suppose my goal at the time was simply to build the habit of sharing publicly and get comfortable with the possibility of judgment.

After months of random posts, I started focusing on writing about sales and marketing, since it seemed easier given my background, and I wanted to get better at both. 

After a while, I started meeting a few people, including some who were looking for help. 

So I started doing a little consulting, and my writing started to center more on demand gen and paid media. 

I shared what I was learning, patterns I was seeing, and opinions on where brands could improve, basically anything that seemed like it might be interesting to others. 

Four years later, I have nearly 30,000 followers (if followers matter now at LI). More importantly, I’ve met a lot of great people, which is what social media is all about. 

I'm no Ernest Hemingway, but writing has been one of the most valuable disciplines I’ve developed over the years. 

It really forces you to think through ambiguity, clarify your stance, and better communicate your ideas 

And this is part of the reason I feel it's so important to stay close to the creative process rather than outsourcing everything to an LLM.

The more I delegate to an AI assistant:
- the less I wrestle with ideas
- the less I refine my own communication
- the less I strengthen my writing muscle

I mean, there are actual cognitive benefits of writing/thinking/doing.

Not sure if ya'll listened to an episode with Steven Bartlett, Dr. Daniel Amen, and AI neuroscientist Dr. Terry Sejnowski, but they discussed the possibility that overreliance on AI tools like ChatGPT could contribute to cognitive decline over time. 

The argument is straightforward: the brain functions like a muscle. Without regular effort, it weakens.

That doesn't mean you shouldn't use AI to help think through things, find different angles, and help edit, but I still think taking a bit of extra time to really think through what you are writing is so important. 

To each is their own, but that's my story and perspective at this point.

Most B2B SaaS paid programs aren’t underperforming because the team is bad at execution.

They’re underperforming because they’re built on an outdated assumption.

For years, it was rational to optimize around leads, CPL, and short-term conversion volume. 

- Channels were cheaper. 
- Categories were less crowded. 
- Intent data actually created an edge.

That environment no longer exists.

Categories are saturated. Buyers are risk-averse. Most of them are not in market. And by the time someone fills out a demo form, they’ve often already formed a preference.

If your entire paid strategy is built around capturing declared intent, you are competing late and paying a premium for it.

The issue is not that we need more tools, more data, or better optimization. 

It’s a mismatch between how programs are designed and how modern B2B buyers behave.

The shift that needs to happen is that paid media can’t just activate demand; it has to build its brand preference. 

That means:

- REACH: Optimize for comprehensive audience reach, not narrowing down the audience more and more
- ATTENTION: Earning attention through diversity of content themes that can be consumed in-feed (like this post)
- EFFICIENCY: Optimizing against CRM outcomes, not just platform-reported conversions

And a measurement approach that doesn't just measure paid media based on a UTM parameter appended to a contact, but also considers the overall efficiency of your inbound motion holistically. 

When you do this, what we continue to see from the brand we work with is: 

- Your capture channels get more efficient
- Pipeline quality improves
- Sales cycles shorten

Not because you forced more people into a funnel,  but because more buyers already knew, trusted, and remembered you when the moment arrived.

This is the difference between running campaigns and designing a growth system.

And in this competitive and noisy market, the latter is no longer optional.

Marketing isn’t an expense.

And most teams don’t defund marketing because they think it’s useless.

They defund it because it isn’t producing an immediate return.

- Pipeline feels thin
- Cash feels tight
- Leadership wants efficiency

So budgets get pulled back to the only thing that feels safe:

Demand capture.

- Branded search
- High-intent keywords
- Retargeting
- 3rd party in-market signals
- Bottom-of-funnel offers

Which is absolutely necessary, but inefficient on its own. 

But here’s the structural issue I continue to see across all the SaaS brands we talk to and in our portfolio. 

Most of your buyers are not in-market (no news there), and by the time they are, preferences are already forming.

When you go quiet upstream (aka out-of-market audiences), you don’t just “save money.”

You shrink future efficiency.

A few realities worth confronting:

1.) Familiarity drives conversion efficiency:

Buyers rarely choose a vendor they’ve never seen before (TrustRadius data backs this up). If your paid program only activates at the moment of intent, you’re competing late and paying more to win.

2.)  Short-term efficiency can create long-term fragility: 

Optimizing only for CPL or demo volume often narrows reach and over-indexes on a small in-market audience pools. CAC rises not because platforms are broken, but because you’re fishing in the same shrinking pond as everyone else.

3.) Silence compounds negatively:

When competitors reduce spending, attention becomes more available. Brands that maintain presence build brand preference that pays off quarters later, often when no one ties it back to the earlier investment.

4.) Momentum improves capture channels:

Broad reach and distinctive creative make search, retargeting, and direct traffic perform better. Capture becomes cheaper when a preference already exists.

The answer isn’t “never cut budget.”

It’s this:

If performance isn’t working, redesign the system.

Paid media should do three things simultaneously:

✅ Build reach across your ICP, not just signal-based audiences 
✅ Earn attention with a creative that aligns with key buying triggers and distinctive brand assets
✅ Optimize against CRM progression and revenue quality, not just platform conversions (P.S. that doesn't mean everything needs a UTM parameter)

When structured this way, marketing stops behaving like a volatile expense line.

It becomes a coherent growth system.

And in today’s market, that distinction determines whether efficiency improves over time or continues to erode quarter after quarter.

It should honestly be criminal to spend paid dollars promoting a message/content that has never been tested organically.

Yet I see teams do this all the time.

They use paid media to test messaging pillars, even though they already have more signal than they realize.

Think about how much information already exists:
- Sales calls
- Customer interviews
- Organic posts
- Events and conversations
- Comments, DMs, and replies

And if you’ve been close to your market long enough, you often know what resonates before you ever open a dashboard.

Remember, organic content is why people come to platforms like LinkedIn, Instagram, Reddit, and X in the first place. They’re there to learn, observe, and form opinions, not to be offered $100 giftcards. 

When something lands organically, it’s a signal, especially when engagement consistently clears that 3–4% range.

And I'm not just talking about thought leader ads (promoting organic posts on LI) 

I'm talking about posting the blog, guide, or short-form video BEFORE you decide to put paid dollars behind it. 

And bonus points if you can retain the same look and feel once it gets created. 

Using Rand Fishkin as an example looks like: 

1.) He posts message/content organically
2.) Looks for a high engagement rate + reviews comments (3-5%)
3.) He takes the same theme/message, builds new content pieces, and creates new ad formats
4.) Then he amplifies the messages with paid dollars that already resonate

This is how you earn attention in an increasingly crowded space where more people are tuning you out. 

The mistake isn’t spending on paid.

The mistake is failing to use internal data to derisk that investment. 

That way, you are already scaling winners vs. trying to figure out what works. 

The teams that win are paid to reinforce familiarity, not manufacture it.

Most B2B brands promote content on paid social in the same way.

- A clean 1200×1200 ad
- A headline.
- A link to download the guide.

Technically fine. Strategically limited.

I saw an example from Datadog promoting an AWS Lambda cheat sheet. 

Nothing wrong with the ad itself. But it highlights a much bigger missed opportunity.

Today, buyers rarely click ads the way they used to.

Feeds are where content is consumed.

So when a brand promotes a guide, a blog, or a cheat sheet purely as a link to click, they are asking the buyer to take on all the risk:

“Is this worth my time?”

A better approach is to bring the content into the feed itself.

Instead of just promoting the asset with a single-image ad, try: 

1.) Recording a short video via Loom, walking through it.
2.) Scroll through the guide on screen (no audio, just expose the content).
3.) Post the content organically, then promote via thought leader ads

Now the ad is the content.

The buyer can start consuming it immediately without leaving the platform.

This matters because most B2B buyers are not in-market at any given moment. Their job isn’t to download whitepapers all day. They’re skimming, learning, and forming impressions long before they ever raise their hand. 

When the content lives inside the feed:

• It reduces the friction of clicking
• It builds familiarity earlier in the buying journey
• It earns attention instead of demanding it

You can still run the traditional single-image ads.

But pair them with formats that expose the content directly in-channel.

In crowded B2B categories, the goal isn’t just to capture demand.

It’s to make sure buyers already recognize your POV by the time they start looking.

P.S. All ❤️ for the Datadog team, just some thoughts on other ways to promote this piece. :)

This B2B SaaS brand saw a spike in cost per SQL from June to August, followed by stabilization in September of 2025. Let's analyze what happened and why. 👇

The graph below shows that the cost per SQL spiked mid-year (May-Aug), which would set off alarm bells for anyone (even me).

Often, the immediate reaction most teams have in that moment is to start pulling levers, cutting budgets, restructuring campaigns, swapping targeting, and overhauling bidding.

Or worse, they have AI automations that pause keywords/campaigns based on arbitrary cost-per-SQL thresholds (seems smart, but can cause more damage than you think)

We instead took a more pragmatic and slow approach to figuring out what might be happening. 

"slow and incremental" are very important here. 

Here's the systematic approach our team took: 

- Reviewed if we are appearing for the right search terms
- Reviewed budget allocation across best/worst performing keywords in SQL
- Reviewed CTR and text ad copy to ensure benchmarks are met
- Reviewed landing pages to ensure strong alignment with ad group
- And a few other technical settings

After completing that analysis, we found literally no event change (channel-wise) that would've led to the spike. 

Zero. 

Then we reviewed historical data from the year prior (albeit campaign mix/budget was very different) and found that a similar spike occurred. 

We determined that it was a demand fluctuation, with the lull primarily driven by a lower conversion rate in the summer months. 

We spent time talking with the VP of Demand Gen, step by step, about what we were seeing, so we could communicate it to her CEO and set expectations.

Fast forward to August, and we started to see a huge decrease in cost per SQL. 

While regular maintenance was happening on the account during June-August, NO big changes were made. 

It wasn't until September that we started broadening targeting on phrase match (a match type in paid search) that we saw even more improvement in conversion rate (to SQL creation).

What's the lesson?

Demand isn't a straight line, and it isn't always a 'we need to optimize better' issue. 

It is correct for you to question results, evaluate your channel mix, and reconsider what you are doing. 

It would be irresponsible not to. 

But, if you can take away one thing from this post, it's 

- Be systematic in how you evaluate a problem
- Be slow and incremental
- Don't pull too many levers at once to avoid shocking performance

Cheers :)

If you are still running paid social like the left side of this graph, take 3 minutes and read this post. 👇

First off, I'd bet most marketers want to run paid social like the right side, but they run into internal problems justifying the budget. 

Paid media has been ingrained in every executive's mind as a "spend $1, get $3" for years. 

If it doesn't convert, doesn't show direct ROI, and doesn't append a UTM parameter to a contact, then it must not be working. 

It's the reason why you spend more of your budget on Google Ads. 

However, social channels operate very differently from search channels, as I'm sure you would agree. 

People come to search channels to:
- Compare products
- Expand the list of vendors for an evaluation
- Do research on new tools to solve x problem
- Learn something new or answer a question

People come to social channels to: 
- Look for a job
- Waste time between meetings
- Learn something new
- Network with peers

If you agree with that, then the question you should be asking your CEO/Exec team is: if those are the reasons people go to a social channel, shouldn't we align our strategy with that? 

Or ask them, "Why do you spend time on LinkedIn, Meta, Reddit, etc.?"

I'd be surprised if they say, "I come to click on ads for high-ticket SaaS products."

For years and still today, paid social continues to be run as a capture-only channel with:

- Narrow targeting
- In-market audiences
- One-off ads
- Platform-reported conversions
- Gated assets

It worked when categories were less crowded, and buyers were easier to convert.

That environment no longer exists.

Today’s buyers are risk-averse, spend most of their time out of market, and form preferences before they ever click a demo ad. 

....take a breath and think for 10 seconds about the last product you bought.....

And there is even more free/ungated content on the web, thanks to 3 big LLMs to do research before ever contacting sales. 

The shift is not about abandoning performance. It is about redesigning the system.

Many of the SaaS brands we are working with are changing the way they run paid social by: 

- Building brand preference across your ICP before the buying moment
- Broadening reach so your brand is familiar with when intent appears
- Developing distinct content themes, not random tests
- Blending CRM data with blended efficiency gains from organic, direct, and brand search traffic. 
- Optimizing for in-channel consumption to earn attention first

Paid social is your "brand megaphone," not just your click on my ad and book a demo channel. 

When paid social is structured around attention, reach, and efficiency, capture becomes cheaper because preference already exists.

You should start to see the share of search increase, brand traffic/conversion increase, and your overall funnel become more efficient. 

It doesn't happen overnight, and it doesn't mean abandoning your entire strategy; it means slowly adapting it to how buyers consume and build trust.

If Google/Bing Ads shut down tomorrow, where would you reallocate that budget and why?

Events? 
Paid social?
Community?
New program you have never had budget for? 

I know it’s a big line item for any serious mid-market SaaS brand.

We need to stop running marketing on sales math alone.

Marketing and sales serve the same outcome, revenue, but they operate differently.

Sales are primarily focused on converting in-market demand 

Marketing shapes preference before buyers come in-market and converts in-market demand. 

We know most buying decisions are influenced long before a form fill, a demo request, or a reply to an outbound email. By the time a prospect talks to sales, their shortlist is often already formed.

So when we reduce marketing to:
- MQL volume
- CPL targets
- “Marketing-sourced” pipeline
- Last-click attribution

We narrow its role to demand capture only, which changes the tactics and objectives marketing uses. 

Let me be clear, demand capture matters. It should be measured and optimized.

But it is not the full job of a marketing manager. 

Marketing’s broader responsibility is to:
- Position the company clearly within the category
- Establish a distinct narrative and point of view
- Build trust at scale before buyers are in-market
- Inform product and pricing with real market insight
- Create brand preference, so you enter deals already in the top three

If you’ve worked in sales at a strong brand, you feel the difference immediately.

Instead of:
“What do you guys do again?”

It’s:
“Our VP has been following you for a while.”

That familiarity lowers friction, shortens cycles, improves win rates, and protects pricing. It makes every outbound sequence, paid campaign, and sales conversation more efficient.

The tension between “sales-sourced” and “marketing-sourced” pipeline didn’t appear by accident. It’s a byproduct of how we chose to measure impact. Which means: 

- Over-reliance on last-click attribution
- Short-term pressure from leadership and boards
- Optimizing for immediate lead volume over long-term demand
- Treating marketing as a quota-carrying SDR team

None of this is about avoiding revenue accountability.

Marketing should be accountable for revenue.

But revenue accountability should include:
- Pipeline velocity
- Win rates
- Sales cycle length
- Brand search growth
- Direct traffic
- Share search
- Efficiencies gains in the bottom-of-the-funnel

Not just how many MQLs were sourced from marketing this quarter.

It’s solved by redesigning how we measure and compensate marketing teams. By establishing a shared number between sales and marketing and evaluating the impact not just on a single UTM-appended contact in the CRM, but on broader funnel efficiencies across all sources.

And we aren't going to solve anything by simply ungating content or testing out the next trendy tactic. 

It is solved by addressing the systematic issues that cause these symptoms and ensuring we get marketing back to doing what marketing should have been doing.

I see a lot of teams frustrated with AI right now. 

They open an LLM, type something like “write a blog post on demand gen vs. lead gen,” and then feel disappointed when the result sounds… hollow. 

Not quite right. Not something they’d ever actually say.

But think about what you’ve given it.

- No real context.
- No point of view.
- No sense of your brand, your voice, or who you’re actually trying to reach.

So, of course, the output feels generic. That’s exactly what you asked for.

Not sure if you all saw this report, but Funnel released a report showing that 39% of agency marketers and 23% of brand marketers say AI tools produce repetitive, generic campaigns.

Sidebar: Honestly, surprised it's not more. 

That tracks with what I’m seeing. And it’s not because AI “doesn’t work.” It’s because most teams haven’t done the unsexy work of giving it something to work from.

AI needs a source of truth, just like a new hire would.

Your POV.
Your tone.
Your messaging pillars.
Your positioning.
Your audience.

When you build workflows that pull from those inputs and feed them real material like drafts, transcripts, and examples, the output changes completely.

Not because the AI got smarter.

But because you did a better job teaching who you are.

Context isn’t optional. It’s the whole game.

Worth reading the report from Funnel below, some interesting stuff there. 👇

#funnelpartner

Funnel

🚨 PSA: CEOs, stop hiding behind your brand logo. 

Your brand needs a face, and it isn't your beautiful brand logo. 

This was one of the topics that Val, VP of Marketing at Unbounce, and I discussed. 

She asked me, "What types of ad creatives do you think will continue to perform well in 2026?"

I told her....

"If we are talking LinkedIn Ads, then clearly thought leader ads will continue to dominate from an engagement perspective. 

They are still the number one ad format for us, not only as an agency, but for all the brands we work with. 

The engagement rates are 5-6x those of any other ad format. And often, the conversion rate is even higher than in other formats.

And so we have a strong pull for any brand we work with that needs at least a handful of thought-leader ad campaigns running. 

It's what people expect to see when they open the feed. And so when they start scrolling and looking through things, it's natural to engage with a person rather than a company.

That's why they get such great engagement: they put a face to the brand. And I think often brands want to hide behind the logo and not get someone out there into the world. 

That actually represents the brand. It doesn't have to be the founder. It could be an SME or someone external."

What I didn't say is....

Thought leader ads ONE format and are unique to LinkedIn Ads. 

The real takeaway is broader. 

The creative that performs best is the creative that matches how people already consume content in that environment.

That principle applies everywhere, not just LinkedIn. Because ads don’t fail when targeting or bidding is wrong. They fail when they interrupt rather than integrate.

And that ties back to the bigger point we see over and over again:

If brand preference is formed before it’s captured, paid media shouldn’t focus solely on converting buyers at the end of their buying journey. 

It should reinforce familiarity and trust. 

When your ads look and feel like native content, you’re not forcing attention.

You're aligning with what people are used to. 

And that’s when paid stops feeling fragile and starts working with how buyers actually behave. 

P.S Not sure why my audio got garbled a bit...

Short-termism is killing good marketing. 

But it doesn't change the reality of what execs want: 

- Fast results
- Predictable returns
- Easy to measure channels

It then forces all product category competitors to optimize for:

- The same in-market keywords
- The same intent/signal audiences
- The same platforms
- At the same moment

That means: 

- Higher CPCs & CPMs
- Rising CAC
- Declining marginal returns

Even with “best-in-class” execution, you'll see prices increase and volume decline as you narrow down audiences. 

Meanwhile, 71% of buyers reported purchasing their first-choice product according to TrustRadius. 

And 9 out of 10 consumers name trust as a primary purchasing criterion, driving buyers to rely on familiar, trusted brands.

Keyword = "famiilar"

If you aren't a familiar, and have established brand preference BEFORE someone comes in-market, it will make it even harder to compete. 

And let's not forget how competitive product categories have become. Here's what the call recording space looks like: 

1.) Fireflies.ai
2.) Otter.ai
3.) Grain
4.) Avoma
5.) MeetGeek
6.) Read.ai
7.) Fathom
8.) Krisp
9.) Sembly AI
10.) Jamie
11.) Tactiq
12.) Supernormal
13.) Notta
14.) Fellow
15.) Nyota
16.) Airgram
17.) Gong
18.) Chorus
19.) Clari Wingman
20.) ExecVision
21.) Jiminny
22.) Modjo
23.) Observe.AI
24.) Dialpad
25.) RingCentral
26.) Aircall

Now let's go after the most obvious target, high-intent keyword "call recording software" = 880 monthly searches at $51/click (top bid)

The top three vendors will likely capture most of the demand, leaving the rest to fight over the scraps. 

And that's just one category. 

- This isn’t a tooling problem.
- It’s not a tactic problem.

It’s a misunderstanding of how B2B buyers actually make decisions.

Short-term optimization is necessary, but insufficient on its own.

Real leverage comes from shaping preferences before buyers ever show in-market signals. 

That means adjusting channel mix, objectives, budget allocation, and CTAs to focus on your narrative, what you do, your POV, proof of work, etc., before they come in-market. 

That will make your capture channels more efficient.

Please be careful when interpreting these emails from Google. 

While the intentions behind this email, I'm sure, mean well. 

These can have serious consequences without additional thought. 

For example: 

1.) Does lower CPA mean better quality down-funnel to SQL/pipeline?
2.) Does this mean I'll have better coverage on key high-intent terms?
3.) As I scale, what control do I have over keywords I'm spending money on?

No doubt, you, me, your mom, and your 2nd-cousin-removed all want greater efficiency. 

But not at the cost of quality. 

Stay safe out there.

Growing organic revenue with content & SEO | Host of Content That Grows podcast | Startup advisor

Nate Turner

Over the last 14 years, I have helped scale Sprout Social from $100k to $100m in ARR (and IPO) and held fractional leadership roles with companies like Help Scout, Zylo, Popular Pays, and Hologram.

In 2019, I left my role at Sprout Social to focus on consulting and fractional growth roles so that I could have more flexibility, more time at home with my wife and kids, and the ability to have full control over my life: from when I worked to what I worked on.

In 2020, I co-founded Ten Speed, a content optimization agency focused on helping companies accelerate their organic growth via quality content so that I could leverage my experience in high-growth startups, SEO, and content marketing to help more companies grow. 

When I'm not working on my own company or consulting, I work with founders and VCs on how to find good marketing talent and scale marketing teams and also invest in and support funds and individuals focused on diversifying tech and backing founders and ideas that are often overlooked.

Co-Founder & CEO

Ten Speed is the content optimization agency helping SaaS companies create, capture, and convert demand by getting the most out of every piece of content.

We've been leading with bottom-of-funnel (BoFu) content for most of our clients lately, and it's changed how we think about content programs entirely.

Ryan Sargent broke down our approach on the blog. Some of our 90-day roadmaps are 80% BoFu. Comparison pages, case studies, feature breakdowns, and industry use cases. When we can, we update core pages before writing any top-of-funnel content.

A few things happen when you commit to that.

First, you stay close to revenue. Every piece maps to pipeline. Your CFO asks what content is doing for the business, and you can actually answer without pulling up a multi-touch attribution deck and squinting. 🧐 

Second, you build content that works everywhere. A solid case study doesn't just rank. It converts traffic from social, events, partnerships, Slack communities, wherever. You stop relying on a single channel.

Third, you learn the product way faster. When you're writing comparison content and use case pages in month one, you're forced to understand the buying journey at a level that makes everything you build after that significantly better.

Then there's the AEO angle. 

LLMs recommend brands that have clear, specific content about what they do, whom they serve, and how they're different. That's BoFu. 

Ashley Faus has the concept of the "content playground." The idea that prospects no longer move through a funnel linearly. They show up from a ChatGPT recommendation, a podcast, or a DM. Wherever they enter, BoFu is what actually gets them over the line.

We've seen it enough times now that it's become our default starting point. 

Ryan's full breakdown is in the comments.

#ContentMarketing #SEO #AEO

Growing revenue w/ organic growth marketing | CEO @ tenspeed.io | Startup Advisor

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The Battle

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Nate Turner

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Jonathan Bland's LinkedIn Performance

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