Are Ad Exchanges and Real Time Bidding The Next Big Thing?

There is a great deal of buzz in the industry around Ad Exchanges and the technology associated with them. However, it is not well understood how they operate and what the benefits to publishers and advertisers are. In researching this topic, we found that while Real Time Bidding (RTB) receives a great deal of attention, there are other attributes of Ad Exchanges that are not widely discussed, yet have the potential to make a major impact on the digital marketing ecosystem. We’ll attempt to clarify some of the concepts used in the Ad Exchange technology stack in this article. First let’s examine traditional Ad Networks.

How Ad Networks Operate

In the Ad Network model, the building blocks are the traditional components of web advertising: Web Content Servers, Publisher Ad Servers, Advertiser (third party) Ad Servers, Database Providers, Cookies, Tracking Pixels and Content Delivery Networks (CDN).

The process generally works as follows (simplified for clarity):

• User begins to load a web page.
• Web page issues a request for an advertisement from the Publisher’s Ad Server which logs the request and returns a “NET TAG”.
• Web page issues request to the Ad Network Server, which processes its pixel, reads and/or drops its cookie, queries its database and applies targeting (demographic, geographic, contextual, behavioral or all of the above) algorithms. It then applies the rules set in the contract with the advertiser. If it finds a profitable match it issues an ADV TAG and logs the transaction. If it does not find a match, the Ad Network may pass the request on to a partner Network, which repeats the process to determine if it has a profitable ad to display and so on until a network claims the impression. This processes typically involves multiple http requests and redirects, which impact load time negatively.
• Web page processes the ADV TAG resulting in the Advertiser Ad Server either serving the ad or handing off the request to a Content Delivery Network (CDN).
• The browser loads the ad, if the user hasn’t already moved on to another page.

This architecture has evolved as the online advertising industry has matured. At this point, it has become what tech types refer to as a “kluge”- a process which is inefficient, slow to serve creative, problematic to traffic, difficult to report upon and expensive relative to the real cost of the media. Add in secondary networks, yield management techniques and third party data sources and you have a cumbersome architecture that does not scale well.

What Ad Exchanges Do

If you have read this far, you now understand one of the most important (if not often publicized) rationales for Ad Exchanges: Efficiency. Suppose instead of the “Round Robin” approach described above, there was a centralized mechanism for aggregating the impressions offered across multiple Ad Networks and matching them (based on the advertiser’s target, budget and placement requirements) with the most appropriate ads?  What if this mechanism existed in the cloud with a well understood API (application programming interface) for audience targeting data and there was dynamic auction functionality around pricing which allowed the publisher to supply his impression to the highest bidder at any given instant? Add self-serve applications for ad creation, traffic, campaign management and reporting and you have the basic components an Ad Exchange or Demand Side Platform (DSP)

Real Time Bidding (RTB)

Real Time Bidding is a dynamic auction process where each impression is bid for in (near) real time versus a static auction where the impressions are typically bundled in groups of 1,000. The potential advantages are cost efficiency, higher performance and greater granularity with targeting and measurement.

Demand Side Platforms (DSP)

Demand side platforms (DSPs) give buyers direct RTB access to multiple sources of inventory. They typically streamline ad operations with applications that simplify workflow and reporting. These products are directed at agencies, agency holding companies and large advertisers (the buyers). The technology stack that powers an Ad Exchange can also provide the foundation for a DSP, thus there is a synergy for plays in both spaces.

Supply Side Platforms (SSP)

Large publishers incorporate yield management techniques to increase ad revenue. This typically involves managing multiple networks. The SSP play uses the data generated from impression level bidding to help the publisher increase the value of his inventory by being on target. Applications to manage ad operations are also bundled into these solutions. Again, the technology is adapted from the Ad Exchange tech stack.

Obstacles to Adoption

While this technology sounds promising, there are arguments against Ad Exchanges:

• Questionable ability to appropriately value premium inventory.
• Devaluation of direct sales efforts.
• Fear of the commoditization of inventory (allegedly suppressing price).
• Suitability of addressing Branding as well as Direct Response objectives and goals.

While the jury is certainly still out, sentiments on these issues are leaning in a positive direction based upon these assumptions:

• Homepage takeovers, guarantees and deep integration on major properties will continue to command premium pricing and require the efforts of direct sales teams to package, promote and manage.
• Because Ad Exchanges increase reach and provide hooks for multiple third party data sources to plug in to the ecosystem, the ability of the architecture to leverage RTB functionality with accurate targeting potentially raises the value of inventory. Perhaps advertisers will pay more to reach consumers that have been qualified by current, actionable data and are therefore more likely to have immediate brand interest or purchase intent.
• The tactical advantages of Ad Exchanges potentially make branding campaigns across premium inventory more effective by broadening reach. Additionally the tools for targeting, traffic, frequency capping, rotation and reporting are ROI enhancing to brand as well as direct response efforts.

The Players

The technology supporting Ad Exchanges is complex and expensive. In order to scale up to handle the level of traffic enterprise clients demand, software engineers often have to code tools from scratch. Open source and/or off the shelf databases just can’t handle the load.

Therefore, it’s no surprise that the big three (Google, Yahoo and Microsoft) are taking the lead in building out Ad Exchange infrastructure. Their deep benches and pockets allow them to invest the resources necessary to make technology like RTB actually work.

Yahoo’s Right Media was arguably the first out of the gate with an exchange. With broad reach across the Yahoo network it is well positioned and has recently committed to offering more premium inventory.

Google AdEx leverages the DoubleClick Ad Serving platform with RTB. As is typical with Google, the technology stack is the most sophisticated of the top tier exchanges.

Microsoft AdECN is Microsoft’s Ad Exchange for the Microsoft Media Network.

AdMeld helps premium publishers maximize revenue from their ad inventory, reduce operating costs and eliminate unwanted ads by giving publishers access to demand from ad networks, exchanges and DSPs.

PubMatic is an ad monetization and management solution which combines impression-level ad auction technology, brand protection tools and ad operations support.

The Rubicon Project offers Supply and Demand platforms with integrated API’s for data providers.

ContextWeb provides real-time contextual targeting.

AdBrite is an advertising exchange focused targeting and optimization, has real-time bidding, API functionality and a self-service account management interface.

OpenX combines ad serving and yield management with RTB.

Media Math is a demand side buying and analytics  platform that aggregates the AdEx, Right Media and AdECN exchanges.

DataXu offers a real-time ad optimization platform which manages buys on an impression-by-impression basis across AdEX and Right Media.

AppNexus is single-point integration to exchanges and inventory aggregators, including Google’s DoubleClick, Microsoft’s AdECN, and others.

Turn is a demand side platform with targeting, exchange integration and analytics.

Audience Science specializes in segmentation and targeting data.

x+1 is a targeting platform for advertisers and publishers. They also build dynamically assembled landing pages and micro-sites based on demographic and behavioral data.

Triggit integrates with Ad Exchanges via its RTB Platform.

Invite Media’s Bid Manager is a RTB buying application.

Content Monetized by RTB Technology

The evolution of the technical infrastructure supporting display advertising is all the more interesting because this tech stack conceivably is applicable to other media types as well. Imagine video on whatever screen supported by ads delivered with this technology…

Source: advertisingperspectives.com

Online display advertising ecosystem

The biggest divide in the online advertising world is search advertising v/s display advertising. Search sounds exactly like what it is: the ads next to search results on Google, Yahoo, Bing, and competitors. Search is bigger than display by revenues, and much more concentrated. 

The benefit of search to advertisers is it corresponds much better than display advertising to intent.  A searcher for “hotels in Palm Springs” is most likely in the market for a hotel in Palm Springs. The other thing search has going for it is its easy and quantifiable — you can sign into Google Adwords with nothing more than your credit card, type up some text ads, and be running campaigns with impression and click reporting within hours.

The display advertising world is structured differently. Display ads are obviously those pictures you see plastered all over the sites you visit. There’s less intent so individual impressions earn a lot less money. Typically the prices are measured as CPM, Cost Per Mille, i.e. cost per 1k impressions. It’s also important to understand the structure of the market a bit. 

In the beginning (90s), advertisers pretty naively bought ad impressions millions at a time on popular sites. Performance was often evaluated based on pure impressions or CTR, click through rates. Ads were often sold on the basis of quantifiability — you could, for the first time, measure how many ads were seen, who clicked, how often, where he or she went, etc. As search advertising evolved, I think a lot of the people chasing quantifiable advertising moved to that, while display became more about branding. This, btw, is the value of facebook — brand advertisers want to be able to precisely target age, gender, income, and other demographics; on facebook, users freely and generally accurately share this information.

The display ecosystem has a bunch of moving pieces. If you look at the display advertising tech landscape graphic from Luma Partners, you’ll see:

Agencies 

These are the big advertising agencies that run most large advertising accounts go through. Companies like Toyota, GM, General Mills, etc, will give these companies tend to hundreds of millions of dollars to run ad campaigns on their behalf.

Media Buying Desks 

The ad agencies weren’t really capable of managing digital campaigns. That is, when ad agencies came about, your media outlets were maybe 10 national TV networks, radio stations, local newspapers, and a couple national magazines. And the media buying process was pretty simple: the agencies would send out an RFP that said we want manly men in their 40s who buy outdoorsy cologne and the aforementioned publishers would respond and say how their audience matched that profile. Compared to the online world of today, where there are thousands of premier publishers such as the NYT, ESPN, online magazine versions, etc; this was much simpler. 

Today, trafficking ads is an order of magnitude more work and advertisers must decide what they want to buy, where, on which site, when, with what creative, etc. So the agencies built or bought companies that have the capability to build digital media, traffic campaigns, optimize the ads, and create the necessary reporting. Eg Vivaki is Publicis, b3 is WPP, etc.

Ad Exchanges 

These are, well, exchanges where publishers and advertisers come together to sell and buy remnant ad inventory. Basically, there is premier and remnant inventory. Premier inventory is something like display ads on high quality reporting on ESPN or ads on articles on ARS Technica. These are often sold by in house salespeople in a process remarkably similar to how everything used to work, though people mostly email PDFs instead of sending faxes. Every ad impression that isn’t sold as premier is referred to as remnant, and these remnant impressions are offered to ad exchanges such as Right Media — RMX, owned by Yahoo — in exchange for a cut.

So the way this works is I can buy, with some rules, 1MM impressions on RMX and RMX will put these impressions on their publishers such as ESPN in ad impressions that ESPN didn’t sell in house. These impressions go for an order of magnitude less money than premier. RMX is one of the more technically sophisticated. The benefit for publishers is they get some money for inventory they didn’t fill. Just to be clear, a good eCPM for premier might be $20-$40 and a good eCPM for remnant might be $3-$5.

Demand Site Platform

A DSP helps advertisers purchase remnant ads across multiple ad sources including exchanges, ad networks, and individual publishers. A good DSP will have sophisticated targeting and optimization algorithms that incorporate first and third party data on behalf of the advertisers. Typically, a DSP’s clients are advertisers that aren’t big enough to go to one of the big seven agencies. Often these advertisers spend $10 – $50k / month, for example a local Toyota dealership instead of the national dealer chain, etc.

Ad Servers 

These help publishers. See Exp: OpenX, DoubleClick Dart, etc. Particularly for larger publishers, coordinating all these ad purchases is complicated. Your advertisers want to give you rules, such as user bleaching rules (only so many impressions to a given user per some amount of time), time of day, what pages an ad can run on (few people want to run next to naked folks, etc). 

They also want to be able to update and optimize their creative or even change the creative or the landing page they go to. Advertisers, or their agencies, also demand reporting — how many times was an ad seen. On what pages did users click on the Ad etc., within publishers the ad sales or monetization folks don’t want to be releasing the site every time they tweak Ads. Ad servers are internal or external software that manages all this and can be quite complex.

Data optimization 

This requires some explanation. In the beginning, people basically bought broad swaths of display ads. The value to optimization is the more targeted you can make your ad, the more value it has. My favorite example is espn: assume 10% of their online audience is female. If you’re an advertiser that wants to sell female sports jerseys, your CTR amongst women is 5%, your conversion rate is 5%, and a conversion is worth $50, your value per 1k impressions is 1000 * .1 * .05 * .05 * 50 = $12.5, so your CPM has to be < $12.50. However, if espn could pick out the women and sell the publisher only that segment (with some error, obviously), but say espn can enrich the demos so that women are 50% of impressions in a segment. Suddenly advertising on espn is worth 5 times as much for the advertiser and hence espn can charge 5 times as much. This is the value of data optimization. It's performed many ways, from things as simple as geo targeting and day part to more sophisticated demographic estimation, retargeting, and varieties of behavioral retargeting.

Re-Targeters 

Re-targeting is a simple idea. Say that I see cookies going to a site like a bmw forum. I might reasonably intuit that these users are interested in bmws and choose to show bmw display ads to them as they browse the internet.

Behavioral retargeting is the next step of retargeting. Plain retargeting is nice, but it suffers from a couple flaws. First, it has limited reach, ie there are only so many cookies that go to a bmw forum. BMW probably wants to reach more purchasers than just those. Second, it doesn’t really help generate intent. If you’re going to a bmw forum, you’re probably already pretty interested in bmws, so that may not be the best person for bmw to advertise to. Behavioral retargeting means any of a variety of ways of trying to figure out cookies to advertise to to get broader reach or cheaper acquisitions than retargeting.

The other big movement going on in the display world is the evolution of how people buy ads. In the early days — 90s — people tended to buy online ads in a high touch process with salespeople. Ad networks started which brought more buyers and fewer salespeople. Companies like Right Media — which Yahoo bought — started and allowed you to create bidding rules that run on their servers so advertisers can buy ads. So I can say that I want to, across many websites, target cookies that have visited a site or set of sites (retargeting), or show them so many ads per day, etc, and based on a variety of characteristics of a cookie and the site which that cookie is visiting and the web page they are viewing, $X is my bid for that cookie. 

RTB or real time bidding 

This is the new - now, instead of giving limited rules to someone like RMX, you register with Google (the largest RTB platform) or Yahoo’s RTB, and their servers, for each impression, send you a bid request. Your computers located in a server farm near their servers are given typically 100ms to respond with a per impression bid for that cookie on that page and that impression. See. Also, this is obviously an enormous tech investment. DSPs also help with this; most companies aren’t capable nor is it worthwhile to build this out in house.
Source: blog.earlh.com