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Realtime Kills Everything

Our first ad campaigns are live and the results are exciting. The campaign ran on a premium publisher in the women’s lifestyle vertical and beat the publisher’s control group on Click- Through-Rate (CTR) by 77% on the 728 x 90 unit and 194% on the 300 x 250. There were over 1M impressions in the campaign served on this domain over a 2-week period. Yieldbot is now serving the entire campaign.  

Most exciting to us are some of the individual results:

  • The best performing keyword has a CTR of 1.56%. 
  • The best creative unit (a 300 x 250) is getting 1.01%

We are running IAB standard banner units. This is not text. This is not rich media.

According to MediaMind the industry average CTR for the campaign vertical is 0.07%

The most matched keyword intent has a CTR of .43%. It also has a CPC of $5. 

That math works out to an eCPM of $21.44. That’s pretty exciting stuff. Even more so when you factor in that this campaign is running in what was unsold inventory.

When I shared the results with one of our Board Members he asked me, what at the time I thought was a simple question. “Why are the results so good?” But then, I actually had to think hard about the answer. I had to boil down a year of beta testing and then another year of building a scalable platform into what deserved to be a simple answer.

Realtime.

Realtime was my one word answer. Never before was every page view of intent for this publisher’s visitors captured in realtime – let alone used to make a call to an ad server at that very moment.

Realtime is different. Realtime kills everything before it. As such, Yieldbot is not building ad technology for the web. We are building web technology for ads. Since nothing is more important for advertising success than timing it makes sense that nothing is more valuable for results than realtime.

Realtime was a big buzzword for a while but the hype has died down. That’s good. In the Hype Cycle we’re now somewhere moving from the “Trough of Disillusionment” to the “Slope of Enlightenment.” It is however this ability of the web to react in realtime that makes the future of the medium so exciting. 

Twitter of course is the best representative example. Twitter changed everything about media that came before it. Used to be that breaking the story was the big deal Now, even online news seemed stodgy compared to people giving realtime updates that planes have landed on rivers, people being killed and opining on a live show right along with it. 

As technology continues to get better at processing the trillions of inputs from millions of people going about their daily lives – doing everything from riding their car to work, buying a pack of chips, surfing the web – the web will respond in realtime. Because of that it will be relevant. The idea of an ad campaign will seem like owning a 32 volumes set of Encyclopedia Britannica. Everything becomes response because the technology is responsive. Calculations need inputs. The web will be measuring just about everything you do and know the moment you are doing it. Nothing will be sold. Everything will be bought.

It’s that realtime pull that creates these new valuations of the media. That new value of the media is what we have been working to create at Yieldbot. That is why these results are so exciting. Best of all, we’re just getting started. We’ve got a bunch of new campaigns about to get underway and we’re only going to get smarter and more relevant. We’ll continue to keep you posted on how it’s going and if you’re running Yieldbot you’ll know yourself. In realtime.

 

Serendipity Is Not An Intent

Serendipity-unexpected

Wired had two amazing pieces on online advertising yesterday and while Felix Salmon’s piece The Future of Online Advertising could be Yieldbot’s manifesto it is the piece Can ‘Serendipity’ Be a Business Model? that deals more directly with our favorite topic, intent.

The piece discusses Jack Dorsey’s views on online advertising and where Twitter is going with it. I had a hard time connecting the dots.

“…all of that following, all of that interest expressed, is intent. It’s a signal that you like certain things,” 

Following a user on Twitter is not any kind of intent other than the intent to get future messages from that account. If it’s a signal that you like certain things it’s a signal akin to the weak behavioral data gleaned from site visitations.

Webster’s dictionary describes intent as a “purpose” and a “state of mind with which an act is done.” Intent is about fulfilling a specific goal. Those goals fall into two classes, recovery and discovery.

Dorsey goes on:

When it (Google AdWords) first launched, Dorsey says, “people were somewhat resistant to having these ads in their search results. But I find, and Google has found, that it makes the search results better.”

At the dawn of AdWords I sat with many searchers studying their behavior on the Search Engine Results Pages. What I and others like Gord Hotchkiss who also studied searcher behavior at the time learned, was people were not as much resistant to Search Ads as they were oblivious to them. People did not know they were ads!

Search ads make the results better because they are pull. Your inputs into the system are what pull the ads. So how does this reconcile with the core of Twitters ad products that are promotions? Promos need scale to be effective. Promos are push. Precisely the opposite of Search where the smallest slices of inventory (exact match) produces the highest prices and best ROI.

Twitter is the greatest discovery engine ever created on the web. But discovery can be and not be serendipitous. Sometimes, as Dorsey alludes to, you discover things you had no idea existed. More often, you discover things after you have intent around what you want to discover. This is an important differentiation for Twitter to consider because it’s a different algorithm. 

Discovery intent is not an algo about “how do we introduce you to something that would otherwise be difficult for you to find, but something that you probably have a deep interest in?” There is no “introduce” and “probably” in the discovery intent algo. Most importantly, there is no “we.” It’s an algo about “how do you discover what you’re interested in.”

Discovering more about what you’re interested in has always been Twitter’s greatest strength. It leverages both user-defined inputs and the rich content streams where context and realtime matching can occur. Just like Search.

If Twitter wants to build a discovery system for advertising it should look like this.

We Love the Mess of Ad Tech and Wouldn't Want it Any Other Way

My introduction to ad tech (roughly): "Ad networks are a mess, you wouldn't believe what a technical mess the industry is".

That was in my first meeting with David Cancel (then at Lookery, who since founded Performable, acquired by Hubspot) as I was bouncing an idea off of him that touched on the edges of the ad tech space.

Fast forward 6 months from then (almost exactly two years ago), I got a Twitter DM from David: "Friend is starting a new startup in the ad space. Looking for a CTO and/or help. Any interest?"

About a month later I was the CTO of Yieldbot.

Two years on I can say he was definitely right, ad tech is a mess. Part of it is how it's evolved and part of it is structural and baked into its nature.

I'll step it up and say this: ad serving may be the most complex distributed application there is.

The proof is in explaining why.

You Control Almost Nothing

There are so many degrees of freedom it can make your head spin.

You basically have a micro-application running embedded in a variety of site architectures each with their own particular constraints, whose users are distributed around the world running all manner of execution environments (browsers).

When you have your own site or application you still have to deal with (or choose what to support of) the myriad browsers and browser versions, complete with differences in language (javascript) version (or even whether javascript is enabled) and issues like what fonts are available on client systems.

If you are creating a destination site, that keeps your team's hands full. If you're serving ads, that's just a warmup. Because you also don't control the site architecture that you are embedded in.

You might need to sit behind any number of ad servers the publisher might be running everything through.

You might be in iframes on the page.

You might need to execute code in specific places relative to other ad serving technology also embedded on the page.

Navigation through the site may or may not involve full page refreshes.

But that's not all...

Distributed Worldwide with Time Constraints

Remember those environments you don't control? They are the customers' websites, and they don't want their users' UX degraded.

Serve ads, optimize it for relevance, and don't slow down page load times.

Most websites have some level of focused geographic distribution to their users. Even if it's as broad as US or even US+Europe.

But for ad serving, your user base is the set of users aggregated across all of the sites using your service. The world is your oyster. And the footprint of what you need to service. Quickly.

But wait! There's more!

Content Relevant To The User At That Moment

At least if you want to be as cool as Yieldbot.

Look, a CDN serving up a static image can satisfy all of the above if all you want to do is serve the same image to every user across all of your customers' websites.

Scattershot low value ads picked fairly at random would approximate that level of ease as well.

But there's no sport (or value) in that!

Our goal here is actually to serve content that is the most relevant to what the user is doing at that particular moment. When done right (we do), everyone wins.

So - simply serve the content that best fits what the user is doing at that moment, where they came from, and what they've expressed interest in *right now*, on whatever they happen to be running on, and wherever they happen to be. And make it snappy, would ya?

We Wouldn't Want It Any Other Way

So, that's what I signed up for - and I love it. And so does the rest of the Yieldbot team.

We started our first intent-based ad serving on a live site a couple months after coding started and started learning real world lessons immediately. And 20 months later it's still going.

I've always loved to work on systems with complex dynamics, so considering all of the above it's not that surprising I ended up finding my way to ad tech.

What I love about building Yieldbot technology? All of the above is only half the story. We also do Big Data(tm) analytics for our system to learn the intent of the users coming to our publishers' sites. We provide them visualizations and data views that teaches them what the intent to their site is. And *then* we enable them to serve ads that make that intent actionable.

#winning

 

Hacking Display Advertising

Hackers
Being as passionate as we are about the huge advances in dynamic web languages and event based programming it is tough to love display advertising. Display advertising was never about web programming or data networking. It was nested on the web as a rogue aggregation and delivery mechanism. The ability of display to deliver relevance remains hindered by this disjointed architecture. It is not threaded into site experiences and the realtime goals of the visits on the pages where it resides. This is exactly why we’re hacking it into something else.  

Vanilla Sky

In Q2 2007 while most of the industry was living some sort of vanilla sky of Behavioral Targeting one company came in and paid, what at the time seemed to most people way too much money, to own a controlling interest in display. No, I’m not referring to AOL buying TACODA. The company I’m talking about has maintained a focus since day one on hacking what you are interested in at that very moment. Unlike other content aggregators it tied its advertising system in the core user experience of its pages and the realtime relevance they delivered. Their stated Display strategy has little to do with cookie matching and everything to do with realtime context and creative optimization with the purpose of “capturing relevant moments.” It is now the most powerful company in Display. That company is of course Google.

Lucid Dreaming

The first lesson here is about the medium itself. This is a different medium and the old media buying and selling template breaks here. Behavioral Targeting may have changed names to the less scary “Audience Buying” but seven years later performance expectations have not been met and it has dragged display into the mud of issues like privacy, ad verification, cookie stuffing and more.

By contrast, Search and email – the most important of the web’s applications - have little use for tracking people across the web, let alone reach and frequency measures. They are the opposite of that. Search (and the web itself) was built by hackers to solve information management and retrieval problems.

The second lesson is that in this medium three pieces of data are valuable – context, timing and performance. The rest is just pipes. Understanding the context of an impression or click at the moment the page is loading and the ability to optimize the message is what the web was built for. It took Search to turn it into a marketing channel but growth (~20% YoY with no end in sight) and the size ($46B in 2013 per eMarketer estimates) of that channel shows how powerful that data is and how helpful understanding it can be to consumers.

Waking Up

The fact that it is referred to as display “advertising” is reason enough to know it’s from another time. This medium kills advertising. Everything on the web is marketing. As Suzie Reider, national director of display sales for Google said recently “display needs to move beyond advertising and into interacting.” Yesterday, Krux CEO Tom Chavez wrote a thoughtful blog post on how it is time for display to move beyond advertising. We agree and we're walking the walk.

This doesn’t mean that publisher will not show ‘graphical’ units as Google calls them. Of course they will. It doesn’t mean that prime real estate isn’t going to be turned over to these units, they will. We’re headed to a world with fewer messages that will be bigger and more interactive. But if we have learned anything from Search it is that format and size don’t matter when the message is relevant, helpful and useful at that moment.

Billions of Relevant Moments

As long as technology to understand context and timing are progressing as fast as they are (and as places like Betaworks where realtime is the thesis of the new medium value creation the startups are hacking away) there is a bright future. Search has proven that the web is the greatest and most democratic marketing medium ever created. The hackers working with dynamic web languages and event driven programming can unlock an order of magnitude of more relevant moments. There are literally billions of them out there waiting to be captured and created. At Yieldbot we see this scale everyday in the inventory of web publishers and if you’re a hacker and remaking the staid idea of advertising appeals to you we would be interested in speaking with you.

 

Rise of the Publisher Arbitrage Model

Screen_shot_2011-09-15_at_12

The business of the web is traffic. Always has been. Always will be. That’s why I was a bit surprised with how much play Rishad Tobaccowala’s quote received last week in the WSJ:

"Most people make money pointing to content, not creating, curating or collecting content."

The original lessons of how to make money on the web got lost because at some point everyone with a web site thought they could go on forever just selling impressions. They didn’t foresee two things:

A) The massive amounts of inventory being unleashed on the web. In the last two years alone Google’s index has gone from 15B pages to 45B pages.

B) The explosive rise of the ad exchange model with its third party cookie matching business that gave advertisers the ability to reach a publisher’s audience off the publisher site and on much cheaper inventory.

Fortunately the more things change on the web the more they stay the same – especially the business models.  Traffic arbitrage, the web’s original model, is a more viable model than ever for publishers and likely the only hope to build a sustainable business in the digital age.

The web is literally built around traffic. Here’s what it looks like right now.

From Search to Email to Affiliate the value and monetization of the web occurs in sending and routing these clicks or as Tobaccowala said “pointing out” at a higher return than your cost of acquiring the traffic.

Google of course is the biggest player in the arb business. 75% of the intent Google harvests costs them nothing. They’ve been able to leverage all the intent generation created in other channels like TV that shifts to Google for free. Just take a look at how much TV drives Search. But Google also pays for traffic. Last year they spent over $7.3 Billion or 25% of revenue on what they call TAC (traffic acquisition cost) to get intent. Of course you need this kind of blended model to be successful as Google is with arb.

With the growing (and free) traffic generating intent to publishers it is time they got in this game. Organic Search continues to drive higher percentages of traffic to top publishers (and the Panda update has pushed that even higher). YouTube, Facebook and Twitter are also sending more traffic all the time at no cost to Pubs. The seeds of a huge arb model continue to be sown.

Vivek Shah CEO of Ziff Davis speaking to Ad Exchanger about ‘What Solutions are Still Needed For Today’s Premium, Digital Publisher’ put it this way:

“…you need to invest in technology that can sort through terabytes of data to find true insights into a person’s intent… not just surface “behaviors.”

This speaks directly to the arb model and how it becomes a true revenue engine for publishers. Once you understand the intent that is present on your site you can then quantify its value. Once you quantify the value you can figure what intent you need to get more of, seed that intent with new content and how figure out how much you can spend to drive traffic to it. This is exactly the model we’ve been working with publishers - using Yieldbot to qualify and quantify the intent on their sites.

So the future of the web looks a lot like the past. There will be marketing levers and technologies that optimize what traffic you drive in and there will be marketing technologies that optimizes where and at what value that same traffic goes out. Everything else you will do in your business will support those value creation events. Yieldbot just wanted to “point out” that for publishers.

 

Why Publishers are the Bread in the Intent Sandwich

Katz-pastrami
There are few main theses that I’ve spent my 14 year career online successfully operating under. The most successful one has always been to leverage the fact that the web is the only user controlled medium. The more ability you give for visitor events to define run-time or dynamic rules the better your ability to deliver relevance. Put another way, there is no better segmentation than self-segmentation.

In marketing terms this means pull instead of push. The best representative example of this is, of course, Search. A visitor action provides an input (query) and everything else processes based off that rule*. Relevance is delivered (and the most successful advertising technology is born) by pulling content to data input rules. Dynamic landing page optimization works the same way.

So why does this matter to publishers whose business is one of “pushing” content? It matters because of one incredible fact about Search that seems to get lost on Publishers. Neither the intent that precipitates the query or the content used to deliver relevance to it belongs to Search. People bring their intent to Search and Search sends it to content created by digital publishers.

Search maybe the meat in the intent sandwich but you can’t have a sandwich without bread. Bread is the media generating intent and receiving intent. Publishers are the bread in the intent sandwich and bread is what publishers have been leaving on the table.

Two years ago I wrote about the opportunity to build an intent harvesting platform for publishers and Chris Dixon followed up with a piece Why Content Sites are Getting Ripped Off. In the ensuing time our team went ahead and built that platform. Because of the complex level of intelligence and scale needed it has taken until now to bring Yieldbot to market. In fact we spent a full-year in invite only beta doing nothing but learning. Now that we’ve released Yieldbot we’re finding out even more amazing things about intent on the Publisher side and the opportunities are obvious and bode very, very well for the future of ad supported publishers.

The most important thing may be that publisher inventory for realtime intent dwarfs Search. As David Koretz figured out a couple years ago the top 200 pubs generate 2000% more pageviews than Google. We see that dichotomy everyday in our data. The amount of inventory using first party (better) data also dwarfs third-party data as Chris O’Hara at Traffiq recently pointed out.

"You have an entire ecosystem built around audience targeting using 3rd party data. The problem? The companies with better and deeper first-party data have a lot more audience"

We also see that most of the advertisers who are buying this intent in Search are not buying from the Pubs that have the exact same intent on their site. Even better the pubs intent is more down-funnel, has greater context, is less competitive and has the influential power of being in a branded domain and can leverage creative in ways search cannot. Publisher side intent should be more valuable to advertisers than Search with its SERP landscape of crowded text link ads and arcane rules.

As we work with pubs to understand this information arbitrage opportunity it’s clear that intent matched with timing and context can improve visit monetization by an order of magnitude. And why shouldn’t it? Yieldbot structures the data from the page that is clicked on and the subsequent pages that are clicked to. This scenario happens millions of times a day on large sites and these (click) streams of data provide rich realtime intent data that fuel our intent classifications and matching rules.

The bottom line is publishers are in the unique position to both classify the intent on their sites and use pull rules once that intent is recognized to deliver the highest levels of relevance in realtime - just like Search. Even better, they never lose ownership of their data and can monetize it directly with advertisers - even using their own ad server. This is game changing. This is the bread in the Intent sandwich. This is Yieldbot.

The Yieldbot team will be writing a lot more about our data and technology right here on our blog. We hope you join the conversation about the power shift to publishers and their data in the ad ecosystem.

* there are additional rules that are used with the query as well such as geo, temporal, query number, however the query itself is the primary rule.