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The "Dynamic Allocation" Feature Within DFP / DART Is Not Yield Optimization

Google wrote a whitepaper a couple months ago called Profiting from Non-Guaranteed
Advertising: The Value of Dynamic Allocation & Auction Pricing for Online Publishers, which describes the benefits of the "Dynamic Allocation" feature built within DART/DFP. Dynamic Allocation is a mechanism for (a) opening a publisher's non-guaranteed ad inventory to the DoubleClick Ad Exchange (Ad Ex), and (b) giving Ad Ex the right of first refusal on that inventory.

I understand Dynamic Allocation works like this. When publishers book a non-guaranteed campaign into DFP (meaning they have not guaranteed a fixed number of impressions), they can check the Dynamic Allocation box. Then, any time that campaign is selected by DFP for display to an end-user, DFP will first check with Ad Ex to see if it can beat the CPM value entered for that campaign -- if Ad Ex can beat it, then the Ad Ex campaign will trump the campaign that the publisher booked.

The problem is that DFP uses a random selection algorithm. DFP, like all other ad servers, is designed to deliver guaranteed campaigns (meaning a fixed number of impressions to be delivered within a set timeframe, at a set CPM rate), not non-guaranteed campaigns. DFP's decision-making process with regard to which non-guaranteed campaign to serve, is random -- not based on yield (revenue to the publisher).

"Ad servers like DFP have some variability in how they meet impression delivery goals, rotating other ads sold by the direct sales force on a non-guaranteed basis into a particular ad slot in order to maintain a steady rate of delivery for the guaranteed ads. Instead of randomly rotating other ads into an ad slot, DoubleClick Ad Exchange uses Dynamic Allocation, rotating in higher-paying ads from ad networks and other third-party media buyers when the net CPM they provide to the publisher is higher than what has been booked directly into the ad server."

Why is this important? Because without yield optimization in the ad server itself, Ad Ex doesn't have to offer the most competitive price every time in order to win the impression. Which means that Dynamic Allocation often costs the publisher revenue instead of making it more.

I'll back this up with an example. Let's say Publisher.com has 4 non-guaranteed campaigns booked within their DFP ad server in the same tier, and the expected CPM rates for those campaigns are:

Campaign	Expected CPM
Campaign 1	$.50
Campaign 2	$.60
Campaign 3	$.85
Campaign 4	$1.20

In its effort to deliver guaranteed campaigns on an even basis, DFP will draw randomly from these 4 non-guaranteed campaigns. 25% of the time it will select Campaign 1, at which point Ad Ex only needs a $.51 bid to win the impression, even though Campaign 2, 3 or 4 would have made Publisher.com more money. If Publisher.com's ad server optimized for yield, then that would mean the highest paying campaign would serve every time. (For simplicity sake, I'm ignoring other campaign attributes that may limit delivery -- such as geo-targeting, frequency caps, etc.)

Google's whitepaper is clever and convincing, but don't be fooled. While Ad Ex (or any auction for that matter) allows the highest bidder to win, the fact that DFP isn't selecting the highest-paying campaign every time means that publishers utilizing Dynamic Allocation are leaving money on the table. They need true yield optimization instead.

(The above observations/opinions are my own, and do not necessarily reflect  those of my employer.)

How Effective are Groupon Promotions for Businesses?

Just read How Effective Are Groupon Promotions for Businesses, which was a survey-based study of 150 businesses that ran and completed Groupon promotions between June 2009 and August 2010. (If you don't know what Groupon is, skip to the end.) Below are my key takeaways:

1. The key factor contributing to whether Groupon worked for the small businesses (as measured by profitability of the promotion) was employee satisfaction within the small business. (Happy employees is good businesses ... whoda thunk?!)
2. Restaurants appear particularly susceptible to negative outcomes; spas appear particularly susceptible to positive outcomes.
3. 42% of the business would not run Groupon promotions again, even though 66% of them thought it to be a profitable promotion.  ("There is widespread recognition among many business owners that social promotion users are not the relational customers that they had hoped for or the ones that are necessary for their business’ long-term success.")
4. Groupon competition will be tough. "Based on our study’s responses, the news for Groupon’s competitors appears to be decidedly bleak ... few respondents had positive things to say about other social promotion sites."
5. Social couponing is in its early days yet, with innovation likely necessary. "Although the majority of Groupon users are satisfied and intend to run another Groupon promotion, an industry in which two in five customers are hesitant after a first purchase, and where the customer base is a relatively limited pool of small businesses with strongly interconnected social networks that could quickly spread news of dissatisfactory results, may need to modify its overall strategy."

For those unfamiliar with the Groupon model, the study describes it succinctly:

Marketing circles have been abuzz in recent months with the sky-rocketing popularity of social promotion sites. At present, Groupon is perhaps the best known and certainly the largest one of these sites. It features a daily deal for each city it operates in, offering consumers a significant discount for a local business or event, such as $40 worth of sushi for $20, or a $175 facial at a spa for $59. Consumers buying the Groupon must pay its price upfront, and then have a certain amount of time, up to a year, to redeem it at the business. Groupon promotions have a social aspect. Each promotion is valid only if a certain minimum number of consumers – pre-specified by the business – purchase the deal.

Google's 7 Predictions for Display Advertising Market by 2015

Google'sVP of Product Mgmt (Neal Mohan) and Managing Director of Media/Platforms (Barry Salzman) presented at IAB's MIXX conference in NY this week, laying out 7 of their predictions for how the display advertising market will look by 2015. I caught it all via Twitter in real-time but MediaPost summarizes it best:

Google's Seven Predictions By 2015:

1) 50% of online ads will have video in them and be bought on a cost-per-view basis. Today, 24 hours of video content are uploaded to YouTube each minute. Google Tuesday officially launched two YouTube video formats, TrueView, based on a cost-per-view advertising model after dabbling in it for nearly a year. This means advertisers only pay when consumers chose to watch the advertisement. TrueView will roll out later this year.

2) 50% of all display advertising targeted to a specific audience will rely on real-time bidding.

3) Mobile will become the No. 1 screen for advertising. The mobile screen will become the first screen that consumers go to on a variety of mobile devices.

4) Five new metrics will emerge to measure the success of ad campaigns. They will become more successful and important. Some exist already: engagement and interaction rates in rich media, video view, and impact on Web search results. Others might include sentiment analysis to measure the viral influence and the tone of consumer chatter about the brand across the Internet. Or, measure foot traffic into the store through geo-based technology.

5) 75% of ads will become socially enabled. In the long term, all ads will become social as the industry moves to an always-on communication.

6) 50% of brand campaigns will run rich media in the ads, up from 6% during the last year.

7) Display advertising will become a $50 billion industry. Google advertisers have increased the amount they spend annually with the technology company about 75% during the last year.

Some perspective on the CDD's recent complaint to the FTC

Yesterday I received a very interesting and amusing set of slides from Bennet Kelley, Internet Law Center, which he labeled as quick facts regarding the recent complaint sent to the Federal Trade Commission (FTC) from Jeff Chester and the Center for Digital Democracy (CDD), urging the FTC to investigate the threat to online consumer privacy within the real-time data-targeting auction and exchange marketplace.

Quick Facts Re: CDD's FTC Complaint

Video of me being interviewed by WebProNews on FTC regulation

Immediately following the panel I participated in at SXSW this year (titled "Smackdown: Consumer Privacy vs. Advertiser Revenue"), I was interviewed by WebProNews on the subject of FTC's consideration of regulating the online advertising industry. Here's the interview ...

NAI Research Study Validates Effectiveness of AudienceTargeted Advertising

The Network Advertising Initiative (NAI) released a study today called "The Value of Behavioral Targeting" -- derived from explicit data from 12 ad networks, including nine of the top 15 ad networks by total unique visitors according to comScore's December 2009 rankings. These ad networks shared their average CPM rates and conversion rates for run-of-network, behaviorally targeted and basic retargeted advertising. Click the image below to view a larger image ....

They reach 3 important conclusions:

• average CPM for behaviorally targeted advertising is just over twice the average CPM for run of network (RON) advertising.
• behaviorally targeted advertising converts better -- more than twice the rate for RON advertising.
• since ad networks get their inventory from Web content and services providers, this makes BT an important source of revenue for publishers as well as ad networks.

Not sure I'd fully agree with that last point -- it's depends entirely on how ad networks are working with publishers. Most of these ad networks are buying as cheaply as they can still, through auction-based ad exchanges and such where they benefit from the fact that supply is greater than demand. This results in an imbalance in the online advertising marketplace, where publishers are actually at a disadvantage. The publishers working with the Rubicon Project though are in fact seeing higher CPMs as a result of audience targeting.

See the full study here.

Online Publishers: Fire Your Ad Sales Team, or Google – You Can’t Have Both

This is a wake-up call for online publishers – if you work with Google in any capacity, just go ahead and fire your ad sales team – your team is selling against Google and guess who’s winning? You might as well just bend over and give Google 100% control over your inventory and revenue generation. If however you want to support your ad sales team, and not put the fate of your business in Google’s hands, then fire Google … immediately and completely. You can’t have both.

I was just looking at Google's new DoubleClick Ad Planner – which provides end-to-end planning, buying, serving and measurement of display ads across the Web. The stated mission of DoubleClick Ad Planner is to provide the deepest, most accurate insight into online audiences possible, helping display advertisers select the best sites for their media plans, and buy those placements through the Google Content Network and Ad Exchange.

So here's the problem. If you’re a publisher with any ad inventory available to Google, then that advertiser or agency you’re trying to close now at a $10 CPM rate can access your inventory for less through Google – and you’ll get some unknown % of that (recall that Google does not disclose their take). Even if you’re working with Google on a “blind” basis, Google is helping advertisers and agencies reach your audience – all they need to do is type in your site and Google will provide them with a media plan to reach that same audience, based on a “Comp Index”. Google knows more about your audience than you do, and is using that knowledge to sell against you.

And the worst part is that it’s you the online publisher that continues to feed the Google beast, and put yourself at a disadvantage in the marketplace! You optimize your content for their index, place their numerous tracking tags (AdSense, Analytics, AdManager, DoubleClick, FriendConnect, YouTube, etc.) over 88.4% of the Web, and grant Google 100% of the information rights. This has allowed them to build a massive set of data on your site and your audience, and use it to fuel their direct sales efforts.  Not only are you NOT being remunerated for all this valuable audience data you're giving to them, NONE of it is available to you for your own direct sales efforts!

If you’re working with Google today, you’ve helped to improve their position in the market to the detriment of your own. So either fire your direct sales team and suckle at the teet of Google … or fire Google, join the REVVolution, and give your direct sales team the support they deserve. But you can't do both.

Power to the publishers.

UW Guest Lecture Deck - MKTG 555

Here is the deck I used for the University of Washington School of Business class  (MKTG 555 - Entrepreneurial Marketing and Management) I guest lectured at yesterday. It's part of their Center for Innovation and Entrepreneurship program, and I spoke about "marketing your small business across the new landscape of the Web -- Online Marketing v2.0".

UW Biz School Lecture - Fall 2009

View more presentations from Jordan Mitchell.

New Challenges for Web Publishers, Reminiscent of Adware/Spyware Market 5 Years Ago

The market for 3rd party audience data continues to grow, but I'm seeing evidence of illicit activities that are somewhat reminiscent of the adware/spyware activities of 2003-2005. It's disconcerting, because the 3rd party data market has developed the right way so far -- for ALL parties involved, and especially for publishers. But we are now at a point where a few bad apples could spoil the whole bunch, and are causing new challenges for premium publishers.

In the last two weeks, I've been in San Francisco and New York, taking part in 3 different online advertising conferences, and meeting with top 3rd party data companies (such as eXelate, BlueKai, AlmondNet, TargusInfo, Rapleaf, etc.), ad networks, and publishers. A few observations ...

First, I'm starting to see more evidence of illicit data collection from publishers. Just as we saw advertising-based applications illicitly installed on consumer's computers 5 years ago, collecting consumer browsing behavior (without knowledge of the publisher or consumer), valuable audience data is being taken from premium publishers and used by 3rd parties without the knowledge nor the remuneration of the publisher. It's being done via ad tags, which if not properly reviewed/screened, may contain Web beacons that pass audience data to ad networks, advertisers and 3rd party data partners for re-targeting, re-use, etc.

As a result, premium publishers need to be on the lookout for unscrupulous ad networks and advertisers that bring short-term revenue lift but then leave with valuable audience data. And as the market for data expands and $ start to really flow, 3rd party data partners will need to be extra careful to control their data sources/channels. When publishers see these 3rd party Web beacons showing up on their pages via ad tags, it casts a negative light on otherwise reputable data companies -- not the advertiser or ad network who passed the data to the data company in exchange for payment.

Secondly, I noticed some 3rd party data providers are offering an API into their data store. Basically, it's a small snippet of JavaScript that, when placed in the ad tag, pings the data service for any user-specific information which is then appended to the ad server request. This is a fine model and service for publishers when they are using it on their pages, but publishers need to look out for 3rd party ad tags that contain these API calls -- every request out to a 3rd party from their site represents potential "audience data leakage".

Lastly, I was discouraged to hear that some unscrupulous advertisers are buying cheap run-of-network inventory via ad exchanges and running the NAI "opt-out" scripts within ad tags. Just as 5 years ago when spyware companies were detecting/uninstalling competing applications as an offensive maneuver, seems now we're seeing companies attempting to reduce the targetable population for their competition, increase their data acquisition costs, etc.

In the online advertising market where "audience" has emerged as king, safeguarding audience data is quickly becoming a core challenge/risk for premium publishers. This makes it doubly important for publishers to control their sales channels, work with trusted partners only, and leverage technology approaches to ad quality -- all hard things to do for publishers already burdened with increasing ad sales and operations challenges. Yet another reason why premium publishers will increasingly turn to sell-side technology platforms like REVV for Publishers. And for those publishers that don't, they not only risk their own brand and core data assets, they also impede the proper development of the market as a whole.

What is the definition of "Audience"?

So much talk this year in the online advertising market about "audience" -- audience insight, audience-centric planning and buying, audience targeting, audience optimization, etc.

But what is "audience"?

Of course there are multiple definitions, but in the context of online advertising I define it as a "self-selected group of people sharing similar attributes". It's not content. It's not context. It's about people, their self-identified attributes, and their attention. Can we agree?