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Inverting A Proposition And Growing It 10,000X
Outbrain's "1 Weird Trick To Create A New Category"

Many early-stage founders I encounter underestimate what it means to achieve “product-market fit”.
When you break this term down into its fundamental unit of measure, it means establishing a perception of radical differentiated value in the minds of best-fit prospects.
Which, is a high bar. Much higher than most think.
To articulate what radical differentiated value looks like in real life, one of my favourite B2B examples to give is Outbrain.
For those unfamiliar, I can say with supreme confidence that you have engaged with Outbrain’s offering to some degree.
They invented the “content recommendations” category in the definition it is viewed today within the adtech industry.
Which is? Those third-party generated content thumbnails you see on publisher websites and apps, as a consumer.
Screen grab of an Outbrain widget👇

Like many things, what’s obvious now wasn’t before.
Today, content recommendations are an established feature when consuming content on the open web. Part of the web furniture.
Outbrain serves billions of internal and external recommendations daily, and, compensates publishers non-trivially in return for enabling marketers to reach their audience.
They’ve been extremely successful with this model, generating over $5bn for partners since the company’s founding in 2006.
If we roll the clock back to that time, the circumstances were very different.
Their mission (as an adtech company) to put the reader first and surface the most interesting piece of content — including through paid distribution — was a divergent point of view.
This contrarian starting position is what enabled Outbrain to develop a radically differentiated value proposition and grow hypergrowth fast.
How so? What did that look like? What’s the juicy details?
Let’s start by introducing Yaron Galai, Outbrain’s founding CEO:
I’m going to share the critical thinking and guiding set of principles that enabled Yaron and his team to create and scale an entirely new category in adtech.
Yaron is a BIG believer in the power of story-telling, so I’m going to approach this post through that lens. By telling the origin story of Outbrain.
In marketing you are either sowing seeds in people’s minds, or, harvesting the plants that came from those seeds.
If you want the seed to be planted, tell a great story.
Here we go. 🥁
Problem

The genesis of the idea for Outbrain came from both Yaron’s success and frustration with a previous startup: Quigo — a contextual ad technology provider and network for digital publishers.
Quigo was a success from the perspective it was acquired by AOL (for $340m), but a frustration for Yaron in the sense that the ad experiences it fostered were spammy.
Yaron recalls: “I found myself ignoring my own company’s ads. They were annoying and interruptive. It was not a great sign for the future of advertising or publishing.”
“That was frustrating to me because I really wanted to just put really interesting links in front of people.”
It wasn’t just Quigo, though.
It was a systemic problem within adtech. The assumptions and rules of engagement that the major players (ad networks) operated on created a crappy consumer experience.
How so? The pricing unit to purchase inventory was on an impression basis (“CPM” is the metric used in adtech jargon).
This incentivised advertisers to produce ever more interruptive ads to get noticed, since they desired to attract as much attention as possible for every ad impression they purchased.
Shout louder, as oppose to speak smarter, was the MO.
It also incentivised ad networks to facilitate ever more interruptive types of inventory, so they would get paid more by advertisers. It’s a slippery slope that compounded into a runaway effect: bigger ads, animated ads, floating ads, etc.
Potently combined with this, there was relatively weak targeting ability and a widespread lack of quality control within ad networks. This enabled spurious advertisers to bid for and win a large share of ad impressions across ad networks.
They could bid the most because they had fast payback windows, ~99% post-media buy margins, and high average order values. In other words: the unit economics worked extremely well.
The lowest common denominator ads (think: ED, get rich quick schemes, miracle weight loss pills) generally won the most ad placements within the spurious segment.
Which, didn’t exactly look classy. 👇

In short: the architecture of the ad technology facilitating the transaction of display (web banner, text ad) inventory favoured serving spammy ads. This emanated from the economic incentives baked into the intrinsic design of the ecosystem.
Put another way: the infrastructure was oriented around the advertiser, of which the spurious kind profited extremely well.
It was a mess. Genuine advertisers were getting outbid. Publishers were undermining trust with readers. Readers were getting a spammy experience.
This triggered Yaron to ask the question: what type of ad would I want to click on?
Asking this question completely reframed who the ad is principally serving. The consumer, not the advertiser.
It shifted focus to a different party in the ecosystem, who Yaron determined was the most important. Without consumer trust, ads become less valuable. With it, more valuable.
But, what type of ads build consumer trust?
What type of ads do people want to click on?
What type of ads enhance the consumer’s experience?
Insight
Yaron is a prolific reader, particularly online. So, his insight to solving the advertising problem came from his own behaviour.
Hypothesis: the type of advertising that consumers will trust, engage with enthusiastically, and gain value from will mimic what people organically already use the Internet for.
In other words, content (articles) that educate, inform, and entertain. With an editorial, not advertising vibe. And, talking with the consumer, not at the consumer.
The thinking: by providing valuable content for consumers in a manner that instils buying behaviour (“sowing seeds”) for the advertiser, every party in the value chain can benefit equally. Publishers get paid, advertisers make money, consumers relish the experience.
Huh? To use an old school example, think of the Michelin Guide. This was valuable content (a list of good places to eat) distributed by Michelin tyres. It helped build affinity and instil buying behaviour with motorists.
Now, imagine an online version of this. That was a use case of Yaron’s thinking.
Other examples for the ‘content, not ads’ direction included promoting earned media (favourable press and reviews) and genuine editorial content.
But, the essence of the problem was deeper than that.
It wasn’t just about content marketing. It was about discoverability. The ability to find exactly what you want to consume in a given moment. What content really hits the spot, above everything else.
That’s a huge problem, because there’s so much content on the Internet. And, crucially, you don’t know what’s out there. Sifting through it manually, like a magazine in the old days, is impossible.
Yaron says “the biggest thing was the ability to discover a piece of content that was wonderful that I didn’t necessarily know about. For me, the problem that I’ve been trying to solve forever is the discoverability of great content.”
In a couple of words, how to find the best what’s next.
Yaron saw a clear need for a content discovery engine that could ingest content on the web, understand what each consumer is interested in, then filter and recommend the most interesting content to the reader, through linking to it.
To use an analogy: a personal sommelier for content.
Guiding a reader in content-consumption mode from the present moment to an immediately more stimulating future.
This insight naturally established a unique perspective.
Point of View
From this insight, Yaron and the Outbrain team developed a contrarian point of view within the advertising ecosystem:
The banner web advertising ecosystem has been built from the ground up focussing on the wrong things. It prioritises what’s good for adtech and advertisers, ignoring what’s good for consumers. This devalues publisher page views and is not sustainable. Outbrain exists to build a new ecosystem, utilising core principles that foster increased advertising inventory value and long-term sustainable growth:
The core principles are the fundamental factors that matter:
🤗 Consumer Oriented. The most important party in the ecosystem is the consumer, not advertisers or publishers. Orient the company around the consumer.
🏦 Bank Trust. The fundamental currency is consumer trust. Everything the company does should work to build trust, not undermine it.
🤩 Delight Consumers. Provide every consumer with the most interesting link, and they will come back for more.
The core POV elements that matter:
Get noticed: Banner advertising is spammy, interruptive
Differentiated problem: Banner adtech puts advertisers first, not consumers. Devalues page views, not sustainable.
Approach: Orient around consumer content consumption behaviour, advertising becomes more valuable and sustainable
From this, Yaron and the team developed a value hypothesis that could articulate this point of view.
Outbrain could recommend two main categories of content:
🔄 Internal (free). Content within a publisher’s own website.
Benefit for publisher: More page views.
Benefit for consumer: Discoverability.
➡️ External (paid). Content outside of a publisher’s own website.
Benefit for publisher: New revenue.
Benefit for consumer: Discoverability.
Benefit for advertiser: Enhanced engagement.
For the paid links, the vibe was to be “sponsored but good”.
This belief was so important that the name “Sponsored But Good” was at one point in contention to be the name for the company (instead of Outbrain).
A central part of this thesis was that, in order to meet Outbrain’s core principles, the architecture of the underlying technology would need to be designed in such a way so that economic incentives were aligned.
Otherwise, it would naturally default back to the issues that faced Quigo and the rest of the banner ad network category.
How so?
With an impression-based (CPM) bidding model like Quigo, there was a revenue glass ceiling in which the “scammer of the month” would often rise to the top.
Whoever paid the most and developed the most interpretive ad creatives (think animated banners) got the most exposure.
But, this approach has an intrinsic limiter. Interrupting can only get you so far. Over time, people become blind to it.
To address this, Outbrain built its model around cost-per-click (CPC) and click-through rate (CTR) metrics. It shifted the measure of value from exposure (interruption) based pricing to engagement (earned interest).
This was radically new, at the time.
Why do this?
If Outbrain can increasingly offer a more interesting link, it can keep pushing up the glass ceiling. As the algorithm gets better and more content gets produced to fuel it, engagement increases.
Consumers will click more because they are genuinely interested, advertisers get more exposure, publishers will earn more revenue.
It’s an engagement based model, with consumers voting with clicks.
Refining The Idea

Outbrain.com — 2008
Like any startup journey, converting the value hypothesis into a validated product meant testing and iterating to refine what ‘content recommendations’ meant as a category and value proposition to publishers, advertisers, and consumers.
The main questions to be answered were:
Will consumers engage, more?
Will publishers want it, then need it?
Will advertisers pay for it, then spend more?
The mission of the company was riding on these answers being a “yes”. It involved challenging assumptions that the rest of the adtech industry tacitly believed to be true — particularly, that advertisers would not pay for it.
In the beginning, Outbrain’s offering didn’t look like what we know content recommendations to be today. But, the essence was there.
It started off as a rating and recommendation system for RSS feeds — purely text links. Then it moved into blogs (personal blogs), then larger commercial blogs, news, and the established media. Along the way, thumbnails (images and text titles) were added.
All the content recommendations were internal to each publisher domain (non-paid) for the first 2-3 years.
This was a slick move since it solved the chicken and egg problem of a two-sided marketplace. Publishers got instant value from increased page views (free of charge) without the immediate expectation of advertising dollars; and Outbrain could build up a mass of inventory from which to conduct R&D (e.g. test algorithms).
However, even with meaningful publisher-install base in place, Outbrain initially had a tough time convincing advertisers to run campaigns.
They just didn’t ‘get it’.
For context, this was way before ‘native advertising’ became a thing.
Back then, the media buying crowd’s frame of reference was banners. They considered Outbrain’s inventory to be in this category (where it didn’t compete favourably in their minds).
Meanwhile, the creative ad folks understood the content marketing value proposition, but got hung up on the creative elements. It didn’t have the full set of controls they were looking for. They were mentally anchoring to completely different competitive alternatives, which put Outbrain’s offering on a back foot.
It took another two pivots to develop a value proposition that gained traction with advertisers.
One of the earlier typical customer profiles that used Outbrain for its advertising value proposition was publishers — websites like WIRED magazine.
Another typical customer profile was direct response marketers — companies like Athletic Greens.
By that time, the Outbrain we know today had taken shape. That’s when the Positioning clicked.
The combination of a finely tuned content recommendation engine, established publisher base, and appealing advertiser value proposition created a radically differentiated value proposition for all parties: consumers, publishers, advertisers.
Radical Differentiated Value
So, how did Outbrain build a perception of radical differentiated value in the minds of its prospects?
Let’s look at each constituent in the ecosystem.
Publishers
Before, content recommendations were a cost centre for publishers. They would pay to licence software (or build the functionality internally) to serve content recommendations.
With Outbrain, publishers were getting paid to to serve content recommendations. This inverted the dynamic, turning a cost centre into a profit centre for cash-strapped publishers. It was sustainable and predictable revenue. And, easy for publishers to setup (plug and play).
Zooming out a little further, Outbrain were not introducing a totally new inventory format. It already existed on publisher sites, so they were able to anchor onto it as a concept. Introducing a totally new format is much, much, harder.
They were also not directly competing against ad networks in the banner space, which was crowded and commoditised. In the mind of the prospect, they were considered separate.
Outbrain were competing in their own adtech vendor category, which they created. The closest competitive alternative (until copycats showed up) were distant enough that there were no ‘apples to apples’ comparisons that could be made in sales deals.
Advertisers
The perception of radical differentiated value depends on what type of advertiser profile (use case) we are talking about. So, let’s look at direct response marketers.
Around the time that Outbrain’s advertiser proposition launched and really started to take off, banner blindness had become a real challenge for direct response marketers.
How so? Engagement (CTR) with banner ads had tapered off massively since the 90s — consumers had become adept at spotting ads and mentally filtering them out.
Conversely, Outbrain’s advertising experience looked native to the website it was hosted on. It looked like content — conforming to the reader’s content-consumption behaviour and set of expectations to filter the interesting from the uninteresting.
As a result, engagement (CTR) was much higher with Outbrain links than banner ads pitching the exact same product. This engagement translated into sales at a proportionate rate, which made the campaigns much more effective (higher ROI).
This higher ROI combined with the unique look and feel of the Outbrain advertising experience established the perception of radical differentiated value in the minds of advertiser prospects.
Consumers
The links that Outbrain’s recommendation engine surfaced to readers were significantly more enticing than the legacy recommendation tech that came before it. People voted with their clicks; page views shot up by around 5-10% per publisher.
Crucial to this was not just the links recommended, but how they were recommended:
They inherited the ‘look and feel’ of the website’s design, making them appear ‘native’ (unusual for a third-party adtech vendor at the time).
They were placed at the end of articles, where readers were in ‘content consumption mode’ and ready for their next fix.
Guiding Principles
To build a startup with a radically differentiated value proposition, Yaron has formulated a guiding set of principles.
👀 The biggest advantage in a startup is focus
👥 Companies don’t buy products, people do
🔎 In a marketplace, figure out the key constituency
🧡 Obsess over your users, not your competition
🎯 A good KPI should apply to very few companies
🤝 Reputation and community beats buzz and hype
↔️ You can beat BigTech by approaching the same market differently
Let’s unpack some of this.
Focus
Yaron is a BIG believer in focus.
That means knowing who you are. What you do. What to do (and what not to do).
That means being resolutely focussed on the mission and taking joy in saying “no” to anything which is a distraction to that, or, compromises it.
Differentiated KPI
In order to focus, a startup needs to know where it’s headed (the mission of the company).
Yaron calls this a startup’s “lighthouse”.
The company has to always have a single lighthouse that it is pursuing. More importantly – everyone on your team has to know exactly what that lighthouse is.
The lighthouse, if properly communicated to every single person in the company, should determine pretty much everything that gets done by by each team member.
In a company with a clearly communicated lighthouse, everyone – junior or senior, engineer or biz dev, in NY HQ or in the Israel R&D – should prioritize tasks nearly identically.
For Outbrain, their lighthouse was “surfacing the most interesting link to the reader”.
How do you measure that you’re heading towards the lighthouse, though?
With a lighthouse metric.
This is a fundamental unit of measure, that, if you keep improving it, good things will happen (the company will grow).
People nowadays refer to it as a “northstar metric”.
The most powerful lighthouse metrics have these attributes:
🎯 Metric with meaning. The metric should distil exactly the unique mission of the company. As it improves, so too does the company’s and customers’ fortunes in tandem.
⚙️ Actionable. Everyone in the company should be able to act and make decisions that impact the lighthouse metric. If it’s a metric that only engineering or marketing can build towards, it doesn’t work.
🌟 Unique to the company. If you choose a lighthouse metric that is the same as your competition (like “revenue”) you are playing the same game (undifferentiated). If your metric is unique, you are playing your own game (differentiated).
💵 Indicator of revenue. Since the lighthouse metric should not itself be revenue, it should be a strong proxy for revenue. For example, if Domino's Pizza’s lighthouse metric was “orders delivered within 30 mins” that is a strong indicator of revenue.
🕶️ Invisible from the outside. Ideally, a lighthouse metric is invisible from the outside. This means your competition is second-guessing and will find it difficult to compete apples-to-apples.
A good lighthouse lets you compete in a crowded market while playing a game that’s completely different from your competition.
Takeaway
Outbrain succeeded in creating a new category because it defined a problem and then approached tackling it from a completely different perspective to all competitive alternatives.
This different perspective functioned as a ‘lighthouse’ that guided how Outbrain approached and developed building a solution, from the ground up. The outcome of this direction was a radically differentiated value proposition.
Importantly for struggling startups, Outbrain’s solution provides an example of the bar for establishing a perception of radically differentiated value in the minds of prospects.
In this case, turning a cost centre into a revenue opportunity. Inverting it. This extreme perceived contrast between the closest competitive alternative and the new proposition is essential.
A radically differentiated value proposition “shocks” prospects — so they are forced to notice and have conviction to mobilise energetically and adopt it.
Conversely, consider if Outbrain had gone down the established route (licensing their tech to publishers). They would have ended up in the ‘better wars’ trying to compete on marginal benefits with established competitors.
It would have been a grind to grow. This is exactly the type of trap that many struggling B2B startups fall into.
Lesson? If you’re struggling to compete in an existing category, consider what problems exist and how they are currently being solved. Zoom out a little bit and contemplate how you could approach an existing or hidden problem radically differently.
Like Outbrain, define what the core and enduring factors are that impact the problem, develop value hypotheses that address these factors, and then test them out with value propositions.
Like Outbrain again, sometimes asymmetric value can be unlocked by reorienting around an underserved party in the value chain.
I suggest checking out Yaron’s personal blog. It contains golden nuggets for anyone building a startup.
Here’s my content recommendations from it, that I think you’ll like:
That’s it for today. I’ll be back in your inbox soon. 🤘
Martin
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