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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

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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

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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.