Others Online Blog

Others Online Acquired by the Rubicon Project

On September 15, 2009, the Rubicon Project announced the acquisition of Others Online.

Others Online was founded on the vision of advertisers being able to reach people, not pages. When I had looked at the revenue growth of Internet advertising revenues from 1997-2007, I noticed two clear growth trends. The first growth trend, from 1997 through 2000 (v1.0), was primarily fueled by content targeting -- Web sites and content were the proxy by which advertisers reached people.

The second growth trend, starting in roughly 2002 (v2.0) was primarily fueled by keyword targeting -- search and context keywords were the proxy by which advertisers reached people.

My belief, and the bet we made with Others Online, was that the evolution of the Web would result in a third growth trend (v3.0) -- the ability for advertisers to reach specific audiences directly, thereby supplanting the use of proxies. Indeed, the industry is seeing tremendous growth in the area of audience targeting. However, the ability to correctly identify specific audiences is dependent on two things:

1. Lots of audience attention data, representing what we're devoting our precious attention span to online.
2. Technology to aggregate, process, score and summarize the audience attention data.

Audience attention data is everywhere. Every online media company has a fragment of attention data, and we've seen a number of companies form in the data space, each offering valuable data for sale to advertisers. Not just "behavioral" data either -- contextual, demographic, purchase intent, location, search keywords, etc. But that's the problem; no one has a complete picture, merely fragments. The true market growth opportunity can't be realized unless/until there's an aggregation point for audience data, coupled with media inventory, and the mechanism by which advertisements can be targeted based on the multiple facets that define us as people, at scale.

Others Online built a powerful technology platform to aggregate, process, score and summarize audience attention data, with services that helped publishers better understand, segment and target audiences. In our discussions with the Rubicon Project, we quickly realized the power of combining their global reach and scale (45B monthly impressions to 500M users, across 30K Web sites) with our technology to not only provide incremental value to everyone connected to the Rubicon Project platform, but also to fuel the next growth trend in audience-targeted online advertising.

As with all announcements though, there are bound to be misconceptions. Though future press releases will certainly add clarification, I thought I'd at least try to dispel a few potential misconceptions upfront!

• This acquisition does NOT make the Rubicon Project a "data exchange". We do not resell publisher or 3rd party data, nor will we. We provide a platform through which 3rd party data providers are developing an incremental distribution and sales channel.
• The Rubicon Project (still) does NOT sell media directly to advertisers. We remain 100% focused on providing value to premium Web publishers, helping them make more money, protect their brand and save time.

The Others Online team couldn't be more excited to be a part of the Rubicon Project. But mostly, we look forward to adding value to their publisher partners and in doing so, hopefully realize the market opportunity at hand.

If you have any questions, please leave a comment below -- we'd welcome the opportunity to answer them in a public setting!

 - Jordan Mitchell, founder and CEO of Others Online, and now VP of Data Intelligence at the Rubicon Project.

Behavioral Data: Category vs Affinity vs Intent Data

Your audience tells you a lot about themselves in their actions and what they pay attention to online. As an ad network or online media company, how you gather and use that behavioral data is critical to your business. But given the sea of data available, what is the right behavioral data to gather and use for targeting?

There are three different types of behavioral data along the "behavioral targeting continuum": category, affinity/interest, and intent data. This post will define and explain the value of each.

Since this is not a short post, let me just start with the key takeaways:

• As with all targeting, reach/scale becomes more limited as you apply narrower targeting.
• Category data provides the shallowest targeting, least ROI yet broadest reach.
• Intent data provides narrow targeting and strong ROI but it's one-dimensional targeting with very limited reach. 
• Affinity (interest) data provides the best balance of breadth of reach and depth of targeting. Think about yourself: of all the Web pages you browse to, only a small portion exhibits purchase intent whereas all of it reflects your interests!
• Affinity data offers greatest ability to tune (via the affinity score), multidimensional utility, most flexibility, and therefore the greatest lift across the largest % of your inventory.

Not All Behavioral Data is Created Equal

By definition, category means "a collection sharing a common attribute". Category data allows you to put users into conventional and broadly-defined behavioral "buckets", with labels such as travel, business, entertainment, etc. A user is attributed to a behavioral category if they've been to a site that falls within the particular category, perhaps within some sort of time frame. The value of this approach is breadth in reach and impression volume, but the targeting is quite shallow and definitions can be blind AND arbitrary -- what does an Urban category really mean and what are the sites contributing to that definition? As a result, category-based behavioral targeting (or retargeting) may not perform any better for advertisers than site-based (contextual) category targeting.

By definition, intent means "the planning or desire to perform an act". Intent data results from an explicit indication of purchase intent -- these users are in the market for specific goods/services. A user is indicating "intent" if for example they've added goods to a shopping cart, calculated a mortgage loan, checked airfare prices, etc. Clearly there's value to targeting based on intent data, but the challenge is the limited reach and scale. As a simple demonstration of that point, what % of your online time or page views are YOU indicating purchase intent for big ticket goods and services?

By definition, affinity means "attraction or kinship to something". Affinity/interest data allows you to understand what your audience is interested in -- brands, activities, products, hobbies, places, etc. A user is said to have a high affinity to "iPhone applications" if they've explicitly indicated it (typed-in within a search field, social profile or blog comment) or gone to a number of Web pages about iPhone applications within a short period of time.

There are several attributes to affinity data that differentiate it from category and intent data:

• Affinity data is comprised of keywords and phrases, the lingua franca of SEM and SEO. There isn't a marketer on the Web who doesn't "speak keyword" or know what keywords work best for them, and those definitions are not abritrary. With keywords/phrases at the core, affinity data is then rolled into categories, personas, or custom channels/clusters.
• Each affinity attribute is coupled to an affinity strength score which allows you to target based on a user's level of interest. This score evolves continually based on time and intensity, much like the attention span of users, allowing you to achieve the right balance of scale/reach and ROI.
• Affinity profiling is deeper, since it involves the ongoing collection/analysis of what users are searching for, reading about, and publishing (through their blog, social media, etc.).
• Affinity data therefore has much broader utility, since you may use category ("travel") AND keyword specificity ("aspen, skiing"). Affinity data can also supplement other forms of targeting.

Achieving eCPM Lift and Volume

The average US broadband internet user views 138.1 pages per day, and is online at least 24 days each month. Say each page has 3 ads on it -- that's almost 10K ad impressions for each Web user each month! That's a lot of inventory per unique, especially if your company is a top 50 US ad network.

Let's say you are an ad network. How do you offer better targeting, and optimize both advertiser ROI and your own eCPM rates? Assuming the cost isn't overly prohibitive, leveraging intent data will work but at low volume -- resulting in maybe 100% lift across less than 5% of your reach. You're already offering category targeting (site-based), so it's not a big step to also offer category retargeting across your network. If you do, you'll achieve maybe 5% lift across less than 50% of your reach (you'd only offer category retargeting for your best categories, after all). Both of these approaches are one dimensional approaches however -- targeting single, binary, behavioral attributes.

To get the most lift across the greatest % of your audience, you're best off to layer in affinity data across your entire audience. This provides you with most targetable attributes per user, the greatest flexibility in how you use it (narrow vs. broad targeting, single or multifaceted targeting, etc.), and the ability to tune until you've achieved the right balance of ROI and volume.

Here are a few "for examples" highlighting what you can do with affinity data:

• Tighten your current category targeting ("consumer electronics", for example) with affinity targeting, by filtering to only those who have searched for "iPhone applications" (very narrow), or have shown any interest whatsoever to "iPhone" (broader).
• Reinforce the value of contextual targeting by targeting both current context and previous affinity to the same category. This method of "context disambiguation" can dramatically increase the value of your contextual categories.
• Further segment intent data (such as "in-market auto buyer") with affinity data, narrowing the targeting to hobbies ("skiiing", "climbing") or personas ("young professional").

Of course, the strength of your affinity targeting depends on the breadth and depth of affinity data collection. That's why Others Online offers a shared data model, allowing all participants to pool affinity data collection and scoring so that every participant achieves a wider footprint of touch points than they have access to themselves.

Affinity Data Offers Depth, Breadth and Multifaceted Targeting

Your audience tells you a lot about themselves in their actions and what they pay attention to online. If you're not collecting and using that valuable information, you're leaving money on the table -- especially these days when every advertiser is focused on eliminating wasted impressions.

Category and intent data offer single dimensions that allow you to expand your targeting capabilities at varying levels of resulting eCPM lift and volume. To really move the needle though, both for your advertisers and your business, supplement your targeting with multi-dimensional affinity data to offer the broadest AND deepest level of targeting across your network. You'll be glad you did.

Audience Affinity: Obama vs. McCain

It's fun sometimes to look at our Affinity Analytics and see what people care about. For instance, Obama vs. McCain.

To the right is a chart from our analytics UI that shows the affinity of an audience (one of our partners, actually) to Obama for the past week. 31.6% of this audience has shown an affinity to Obama, with an average affinity score of 60 (scale of 0-100).

For McCain, while his popularity is trending up, clearly he is less popular among this particular audience. About 14.6% of this audience has shown an affinity to McCain, with an average affinity score of 54..

Online Advertising 101 - For Web Sites

This post was cross-posted from MetaMuse.

There are a large number of Web startups relying on an advertising revenue model, many of whom may not understand the landscape. For them, I think I have a fairly sound and business-oriented way to describe the online ad space, which consists of Web sites and advertisers, and of course the myriad ad networks and companies connecting the two. This isn't a "how the online ad industry works" primer, but rather a simple analysis of how your Web site fits into the online advertising ecosystem. Let's think in terms of the following two axes and follow with an explanation.

All Advertisers (horizontal line) are  interested in reaching the right people. Simply speaking, there are big $ advertisers -- the folks that have huge online ad budgets -- and many many more long-tail advertisers who might only spend $50/month. For all advertisers, the more targeted their campaigns the better their ROI (regardless to how you define "targeting"). Advertisers often use online agencies to buy on their behalf, but for this post let's assume "advertisers" and "agencies" are interchangeable.

Web sites (vertical line) are the proxy by which advertisers reach people. Advertisers evaluate Web sites (among other ways) on the basis of their content, since it's the easiest way for advertisers to understand the audience/people.  Vertically-oriented sites are those with narrowly focused content, which offers advertisers more straightforward targeting. Advertisers in the auto market, for example, buy campaigns on sites about cars.  Edmunds.com is an example. Horizontally-oriented sites are those with widely diverse content/focus. It's much more difficult (and often inefficient) for these sites to sell advertising on a targeted basis, because they have content about anything/everything.  MySpace.com is an example.

For big $ advertisers, volume/scale is the 2nd most important consideration. If you don't have a sufficient audience size, it doesn't matter how good your targeting is as a Web site -- it's more efficient for them to allocate each $100K they spend across 1-5 sites instead of 50-100. And of course, Web users visit all kinds of different sites so it's hard for any one site to offer a ton of volume.  Ad networks therefore serve the necessary purpose of aggregating many sites together, organizing them by content type, and offering advertisers scale at some level of targeting.

While some advertisers certainly buy direct from Web sites, the majority of advertisers buy through ad networks of some sort (roughly defining an ad network as any company connecting the buyers and sellers of ad inventory). Let's mark them as red below, and explain further from the perspective of the Web site publisher.

Vertical Content Sites Make More Money

If you have a vertically-focused Web site then you'll have a much easier time selling your online ad inventory AND earn the best eCPM rates (defined: the value per thousand impressions, regardless of rate type -- CPC, CPM, CPA, etc.).  Medium/large Web sites (more than 1M unique users per month) fit in the lower left quadrant. Since they offer both targeting and scale, they're able to sell direct to advertisers (making the most money), and they have their pick of ad networks to monetize whatever they can't sell directly (which is called remnant inventory). This quadrant is where most traditional ad networks hang out -- since they primarily consist of a direct ad sales force, they make the most money as a business by focusing on big $ advertisers and vertically-focused sites that can deliver volume.

If you have a vertically-focused Web site with a small audience then you most likely won't gain any traction with big $ advertisers or traditional ad networks; you are in the lower right quadrant.  Google AdSense is your best option, and you may even earn better eCPM rates than medium/large publishers. Google and a variety of others created this market by inventing a self-service advertising model which provides you as a Web site with a ready supply of advertisers and revenue. By eliminating the need for a direct ad sales force and automating campaign targeting, sales and delivery, they're aggregating and matching long-tail advertisers with long-tail publishers.

Horizontal Content Sites Make Less Money

If you have a horizontally-focused site (content about "anything/everything"), as is often the case with social media and user-generated content, then you'll have a tough time monetizing your ad inventory. Average eCPM rates on social media sites are low and decreasing.

If you offer a massive audience -- as in many millions -- then you're in the upper left quadrant and will have some luck selling directly to advertisers, but only if you can segment your audience in some way. Advertisers require some understanding of WHO their campaign reaches. Even traditional ad networks with experienced sales teams and solid advertiser relationships shy away from horizontally-focused content sites, especially social media and user-generated content.

There are several startup ad networks attacking this upper left quadrant however, given the massive eyeballs/volume and extremely low eCPM rates. These networks, such as Media6° and Lotame, aggregate and package social media behaviors for the benefit of large advertisers. Unless you have a massive audience, they won't work with you. There's nothing long-tail about them. Like all other  ad networks,  they can only support their direct sales efforts by focusing on big $ advertisers and large-volume sites.

So what do you do if your horizontal Web site attracts an audience of <5-10M unique users per month. You have two options: Google AdSense and ad exchanges. The problem with Google Adsense is that it often doesn't work on these pages -- the ads are targeted only to page content/context, and many social media pages (pictures, videos, social networks, etc.) are contextually poor.  You're better off targeting each visitor based on THEIR MySpace profile, instead of the MySpace profile they're looking at!

As a result, I believe the vast majority of this ad inventory is being monetized by arbitrageurs via ad exchanges. Ad exchanges such as Right Media differ from ad networks primarily in their pricing model, which works like a stock exchange. This facilitates an arbitrage model where those who know something about your audience will buy your ad inventory at very low rates and resell at higher rates. Of course, this doesn't always work well for you the publisher -- they don't share what they know about your audience with anyone, because the lower their price the more money they make.

In my opinion, this upper-right quadrant represents the biggest opportunity in online advertising today, given the massive volume and extremely low eCPM rates being earned by publishers today. Just as Google AdSense grew the entire online ad market by matching long-tail advertisers with long-tail vertical content, there exists the opportunity to match long-tail advertisers with people instead of pages.

Enter Others Online ...

In closing, I'll simply point out that Others Online is focused on the upper-right quadrant. We develop a summary of what each visitor cares about across multiple page views (what they're searching for, publishing, reading, etc.) and use that affinity profile to drive  Google AdSense (or any other long-tail ad source you prefer) on any other page.  It's targeting people based on their interests rather than just the page they're on. The result is better targeted advertising and revenues across all your horizontal content pages.

Affinity Analytics Beta Launch

We're pleased to announce the beta launch of our Affinity Analytics service for publishers and networks. This is not like any other Web site analytics you've seen.

Traditional web site analytics tell you about visits, page views, sources, etc. but nothing about your visitors. Our free Affinity Analytics service tell you about your audience and the topics/interests they care most about, based on how they browse not only your site but our whole network.

It takes seconds to sign up. Once you're approved, we'll provide you with simple HTML (Javascript) to copy and paste within your Web pages. That's it -- we then provide you with web-based reports (we also offer a data feed and API service) which show you the topics that your audience cares most about, and for each topic your audience's level of interest (average affinity strength score of 0-100), the commercial value of that topic in the advertising world, and how much of your audience cares about that topic. Here's a screen shot ...

You can also click on any of the topics to see trending data/graphs over the past 7 or 30 days. This helps you understand total unique visitors and page views for any given audience segment, allowing you to target them by their interests and affinity strength.

Affinity vs. Engagement in Advertising

Others Online has been working on some interesting reports for our partners to summarize in aggregate form what their users care about. As a matter of labeling, we've discussed the term "affinity" vs "engagement". The latter has been thrown around the online advertising space quite a bit recently, so I did some poking around the Web to get a better feel for how it's being used. Usually, going with some convention in labeling in more advantageous, rather than creating your own definitions (which markets get annoyed with IMO).

Stumbled upon an interesting and intelligent blog post on How the New Engagement Metrics Can Impact Advertising Decisions. In it, "engagement" was defined as the nature of visitors’ relationship with a site and how that is expressed in the full range of user interaction, involvement and connection. Kevin then went on to describe categories of engagement that effectively describe the kinds of engagement illuminating and differentiating Web sites for advertisers: loyalty, recency, click depth, interactivity, duration, and subscription. I should also point out that Kevin's work leveraged the work of Eric Peterson. Kevin then wrote:

How  can publishers collaborate with advertisers to yield actionable intelligence?

“We’ve developed Web technology to the point where we have an astounding wealth of data about audiences. Publishers can tell us what content audiences are consuming and the share of content downloads among competing advertisers. All this has been great. But what does it all mean? How can we turn that information into something we can act on?”

Brandon Starkoff, Vice President/Global Director at Starcom Worldwide

Starkoff’s point is critical to the whole point of seeking to establish a definition and a set of metrics for engagement. What does it matter if, as far as media companies are concerned, it doesn’t produce better insights into what will make advertisers successful with even the most “engaged” audiences? The kind of audience knowledge Starkoff says he is seeking is “predictive intelligence-advice on what kinds of advertising will work with a particular audience or audience segment.”

Advertisers right now think about engagement as a way to distinguish sites from each other.

It was in the last sentence that I realized what I felt was wrong with their line of thinking. It's not that advertisers need to distinguish sites from each other, but rather people from each other. Engagement is a term being applied as an attribute of a site, not a person. That's just wrong IMO. That's online advertising 1.0, not 2.0. As long as the industry continues to think in terms of targeting sites and not people, there will only be small incremental improvements to online advertising performance.

Affinity is a term which we feel best describes attributes of people, and what we actually care about. Since Others Online is all about targeting people and not sites/pages (based on our understanding of what they care about), that's clearly the label we need to use.