Background

The Google Display Network (GDN, formerly referred to as the Google Content Network) has an extremely large inventory pool of sites across the internet. GDN was initially launched on October 23, 2000, and in more than a decade has grown to one of the largest online advertising properties in the world.  It is estimated that this network reaches 89% of the internet in the U.S., with over 1 million publishers and 211 million unique users per week (comScore Networks machine-based panel). Paid search and display media ads can be served across this network, and audiences can be targeted in several different ways. Ads are served alongside content specified by the advertiser. This brief will take a deep dive into the targeting capabilities of the GDN, and the benefits of the GDN for a paid search advertiser.

GDN and Digital Advertising

Paid search advertising and display media advertising both have the opportunity to advertise within the GDN. The main difference between these two mediums is cost structure. Display media is usually bought on a cost-per-thousand (CPM) basis, meaning the advertiser pays each time 1,000 impressions are served. Thus, each advertiser’s display media impression must be a valuable placement.

Paid search advertising is usually purchased on a cost-per-click (CPC) basis. This means that the advertiser only pays when their ad is clicked on. With this cost structure, there is more flexibility in what sites these ads are placed. If the site is not compatible with the ad, then the ad will not get served and no cost is incurred. Paid search advertising using the GDN is an excellent way for an advertiser to reach a greater audience and still maintain efficiencies.

While targeting is critical for both types of digital advertising to reach the right audience at the right time, the implications of highly specific targeting are usually more essential for display media to ensure that impressions are not lost on an extraneous audience. However, all targeting options in the GDN are available for purchase on a CPM or CPC basis for both text and display ads, depending on the advertiser’s goals.

Types of GDN Targeting

Contextual Targeting - selecting specific keywords and/or topics where the advertiser would like an ad to appear. Contextual targeting is done on the page level, not the site level for maximum relevancy.

Keyword Contextual Targeting – advertisers select certain keywords that are relevant to them, and bid to appear alongside this content. This ad may appear on any site across the GDN where there are those keywords on the page. The scale of this method of advertising could be very large, depending on the keywords that are being targeted. It is usually recommended to layer this type of targeting with another method to increase relevancy and minimize waste.

Topic Contextual Targeting – advertisers select certain topics that are relevant to them, and bid for their ad to appear on pages of these sites.  This ad may appear on sites across the GDN that are categorized under that topic. This method is very broad-reaching as well, and is usually recommended in combination with another targeting method for an advertiser interested in reaching a specific audience.

Placement Targeting – advertisers select certain sites and/or sections of sites that are relevant to them, and bid for their ad to appear on pages of these sites. These sites can be selected by the advertiser using Google Tools such as Ad Planner, which uses Nielson data to index sites in the GDN based on:

• Demographics (Household Income, Age, Gender, Education)
• Online Activity (Other Sites Your Audience Visits, Keywords Your Audience Searches For)
• Interest Categories (i.e. Cooking & Recipes, Women’s Interests, Weddings)

In practice, Razorfish usually finds this method to be the most successful approach to the GDN, because sites/sections that index highly against a target market can be cherry-picked for extremely relevant targeting.

Behavior Targeting – Advertisers select certain topics that are relevant to them, and bid for their ad to appear across the GDN to users who match those interests. This method can be used to reach a large audience as well as a more targeted, niche audience. A user’s interests are either declared interests (through the Ad Preferences Manager), or are inferred based on their browsing behavior, specifically their recent and frequent site visits. This method of targeting is usually used for broad-reaching awareness campaigns or advertisers that seek site visitors that abandoned part of an intent funnel.

Inferred Demographic Targeting – advertisers bid on an audience where Google has inferred their demographic based on their GDN history. A user’s demographic is determined by a number of sources, including user registration data, 3^rd Party data and site composition. The registration data that is used in Inferred Demographic Targeting may come from YouTube registration, or other undisclosed sites in the GDN that capture registration information. Specific targeting sources cannot be cherry-picked, and Google takes all into account when inferring a demographic. The composition index of a site determines the inferred demographic. For example, if a person visits a fashion site, and then visits a parenting site, then Google may infer the demographic as a Female 25-54. If an advertiser uses Inferred Demographic Targeting for this target, then Google will serve an ad in the GDN network to that person. Google is constantly improving the dataset used to determine user Demographics and will incorporate new data sources as they become available. Additionally, this feature is currently in Beta and advertisers must request to be whitelisted by Google to participate.

This newer method of targeting may have benefits for an advertiser that has an extremely specific audience they wish to target, and should be tested alongside other GDN methods. However, because demo-inferred targeting is still in beta and takes very little user self-identification into account, it should not be used exclusively as a preferred GDN targeting method without the support of testing and analysis alongside the other methods.

Below is an example of how an advertiser can use a Google tool, Ad Preferences Manager, to target select audiences.

Remarketing – advertisers bid on an audience that visited their site (or a site which will allow them to implement a pixel) and their ad is displayed across the GDN. This method is often used for CRM marketing, or if the visitor was in the middle of a conversion funnel and then left. In the example given below, Special K can remarket those that visited the Special K Challenge Registration page but did not fulfill registration.

Hybrid GDN Targeting - GDN Targeting products can be combined together to reach a very specific, desired audience. As targeting layers increase, an advertiser will be reaching a more specific audience and a smaller percentage of the total population.

GDN Benefits for Paid Search

With the targeting capabilities and mass reach of GDN, there is a greater opportunity to expand paid search marketing campaigns. Expanding an advertiser’s paid search marketing presence will lead to impactful benefits such as:

1. Efficiencies – It has been established with prior campaign history that paid search is one of the most efficient means of advertising. However, paid search on sponsored search (i.e. Google.com) can sometimes be expensive if an advertiser is bidding on keywords where there are many other competitors, which may increase CPC and overall cost significantly. Including GDN and network targeting can be essential for an advertiser with many competitors who is concerned with efficiencies such as CPC and CPA (cost-per-action).

2. Reach – there are a finite number of searches for a set of keywords, and search trends must increase if an advertiser wants to expand their paid search marketing efforts. GDN offers an opportunity to expand reach beyond basic sponsored search results.

3. Relevancies – GDN is an opportunity for an advertiser to appear alongside relevant content or a target audience efficiently.

4. Testing - GDN is a way test sites and targets with minimal cost commitment (budgets can be set as low as $1 a day for only one day)

5. Turn-Key Implementation – ads are the same format as traditional paid search ads (130 characters) and can be created quicker than other advertising creative.

Google has officially announced Google Analytics Premium! Google’s first enterprise analytics product will be available directly from Google and many Google Analytics Premium Certified Resellers. They apply a more simplified pricing approach compared to the confusing contract pricing which is based on server calls and options that the rest of the enterprise industry has established. The especially interesting thing is this flat fee could result in saving money for larger clients switching from Omniture or Webtrends; however, this could also end up being more expensive for medium-sized clients looking to move to Google Analytics Premium. Regardless, it’s important to weigh the Pros and Cons of each product’s features and perform an analysis of whether the investment is worth the price tag. Here are the key features of your Premium investment:

In addition to requiring no code change to upgrade from Standard to Premium, one great aspect of Google Analytics Premium is that the interface look and feel hasn’t changed at all. The only change is the addition of the Unsampled Report export button:

Attribution Modeling (PREMIUM ONLY): Advanced analysis, simplified

Although it’s limited to only Google Analytics Premium customers, this advanced analysis tool provides powerful multi-channel attribution that actually seems easy to use! If your client is a DART For Advertisers customer then this tool will prove even more powerful since media impressions can be weighted in the model as well. There are several different types of attribution models that a user can select or compare based on their needs. Here are the ones that were presented:

• Last Interaction (only the last touchpoint matters)
• Linear (every touchpoint gets equal credit)
• First Click (only the first touchpoint matters)
• Time Decay (more recent touchpoints get more credit)
• U Curve (value early and recent touchpoints)
• Engagement-based (value the touchpoints based on the amount of time on site they drove)
• Custom (you name it, you got it)

This powerful feature may truly put Attribution Modeling on the map, in terms of digital analytics, in the same way that Google Analytics initially put Bounce Rate on the map. Unfortunately, only Premium customers will get to feel the power. The interface looks relatively simple, but will require a truly analytical eye to glean actionable takeaways. One note worth mentioning is that Google demands that privacy policies be updated to include mention that attribution modeling is taking place, yet no PII is being collected.

Google Analytics Right Now: Real-time site-side reporting

Google has a completely new product feature that nobody else in the enterprise site-side analytics space has created: real-time reporting. According to Google and tests we’ve performed, this new report set has a delay of only 1-2 seconds between the tag being called and the report populating. When you view the reports, you can see a live stream of statistics and learn exactly how your website is being used at that very moment. Google has actually decreased the session timeout to just 5 minutes for Right Now. These new reports provide the following report data:

• Medium / Source
• Geo-Location (IP-Based)
• Pages
• Pageviews
• Visitors
• New vs. Returning %

Right Now seems to be one of those features that sounds (and looks) really cool, but probably won’t get used every day. While chatting with colleagues at Razorfish, it sounds like the best use for this data could be during events: new site launches, campaign launches, marketing events, and social media events.

If you’d like to gain early access to Google Analytics Real Time, you can sign up here: https://services.google.com/fb/forms/realtimeanalytics/

In Conclusion: A lot to get excited about

These great features are certainly worth getting excited about! Now that Google Analytics Premium has been officially announced, it will be very interesting to see how the enterprise analytics landscape changes.

What are some reasons clients will prefer to stick with Omniture or Webtrends?

• Improved Pathing Capabilities
• Visitor-based Segmentation Capabilities
• External Data Sources
• Site Optimization and Display Ad Targeting Integration
• Social Data Integration
• Search Management Integration
• Genesis Integration
• Classification Systems
• Familiarity with the System
• Built-in Hierarchy Tracking
• Built-in Video Tracking
• XML Data Insertion API
• Export Capabilities to PDF, HTML Email, Scheduled Reports, and Alerts
• Improved Shopping Cart Tracking
• Option to keep data in-house (Webtrends OnPremise)

Webtrends has already released their opinion on Google Analytics Premium: http://blogs.webtrends.com/blog/2011/09/30/why-enterprise-marketers-should-be-wary-of-google-analytics/

In a previous post, I wrote about Google Hotel Finder – an experimental search tool that allows users to find hotels faster and easier.  I mentioned that Hotel Finder is one piece to the “planning-a-trip” puzzle, not knowing that Google was cooking up more magic in a few weeks to come.  Last week, Google introduced Flight Search.   Similar to Hotel Finder, Flight Search allows users to find flights quick and easy.

In April, Google acquired travel software company ITA for $700 million.  After the acquisition, many speculated and waited to see how Google would make its stance in the travel industry.  On September 13th, Google made its presence by launching Flight Search.  With the launch of Flight Search, Google hopes to “build new travel tools that provide faster, more flexible, and more useful results to online travel searches.”

What does this all mean?

Well, now when you search on Google: “flights to [destination]”, a “Flights” link will appear on the left panel of the Google SERP.  The “Flights” link directs the user to www.google.com/flights.

When I searched “flights to Miami”, a list of flights (my departure automatically defaulted to NYC airports) appeared and I was able to view a variety of carriers’ round-trip fares. A few listings came up as “unknown price” – but more on that later.

Along with convenience of searching for flights right through the Google interface, Google also prides itself as delivering “super-fast results.”  No more waiting for the site to load and “Finding the Best Prices for You!“, nor do you have to deal with 100 different screens opening in different windows so you can “compare” prices.

The user is also able to get a sense of when to travel. When you click on the calendar icon, a graph appears and allows you to compare prices at different times.  Below, I’m comparing prices between my desired travel time of October 6 – 10^th, as well as the weeks ahead and before my desired time.   The dark blue line indicates the week I have chosen, which happens to be the week with the highest price range. The price seems to decrease for the weeks following this time.

Last but not least, Flight Search gives users options and more options!  Now that it is getting cold in NYC, I’ve decided that I need a little more warmth – so maybe I’ll head to Miami.  But, at the same time, Miami is too much like New York, except with palm trees and warmer climate, in my opinion.  So, where else can I go that’s relatively close but warmer?  Flight Search gives the user the ability to explore other destinations by filtering by price, airline carrier and flight time.  So now, since I want to find another warm destination other than Miami, I can choose a filter for, let’s say – Continental Airlines, within 5 hours of NYC and costs less than $500…. The result: Dallas, Texas (amongst other destinations that came up) – not sure if I had Texas in mind, but it’s an option!

Now, for the Good, Bad and Ugly of the new feature:

• The Good:  I did save time in finding flights and I did not have to deal with annoying pop-up windows to compare prices.  I also like the fact that I can customize my searches and filter for different carriers, price points, etc.
• The Bad: For now, the user is only given the option to search for flights within the United States. I originally searched for flights to CDG (Charles de Gualle) and was given an error message (hopefully international flight search is in the near future).
• And The Ugly:  Earlier I mentioned receiving an “unknown price” box appearing when I searched – I have seen this a few times in the feature.  Not sure if this is a glitch in the system or deliberate?  But, not being able to view prices takes away from having a flight search tool in the first place, no?

You can learn more about Flight Search here.  All aboard!

Google recently (officially) announced that Google+ and +1’s are influencing your search results, and given the opportunity for Google+ to augment this even more, expect to see an influx of social applications on your search engine results pages (SERPs) in the next year.

This wish list includes several features that may socially alter search results and the searcher’s experience within them. Some are immediately applicable, while others err on the lofty side. But, if you are going to dream, dream big.

Social Influence Categorization:

As Google+ grows and users are forced to engineer Circles and group greater amounts of connections, search results influenced by shared information across the social network will need categorization. Imagine you’re searching for a particular topic and you have 1000+ connections. If several connections shared the same link that rises to the top of the results, wouldn’t it be beneficial to tell the searcher to categorize certain Circles above others? For instance, if I’m searching for movie reviews and the top result was shared by my Marketers, Friends, Family, and Google Circles, I’d be much more influenced by my Friends and Family Circle than my Marketers Circle – which includes thought leaders I’ve never met. Leveraging this user-provided data will make my results more relevant; therefore, increasing my satisfaction with the search results.

Social Meta Information:

When a connection shares a link on Google+, they rarely share only the link. Usually, they’ll also share a little blurb or opinion on the link. To augment the context of that shared link in search results, wouldn’t it be nice to see an excerpt of that blurb right below the search result? Google introduced more white space and spacing between results with their latest creative refresh, and this increased white space allows them to provide more detailed results when applicable. I’d love to know why my friend shared a link and their opinion on it versus only showing the fact that it was shared. In essence, this creates a dialogue between you and your connections within Google search instead of purely relying on what search marketers provide in the title and description.

Social Paid Search Ads:

Facebook has an offering similar to this idea. However, Google+ and +1’s proximity to Google search make this a winning feature. As paid search marketers, we are constantly striving to provide more relevant results to searchers in hopes of improving our CTR and increasing site traffic, leads, and revenue. In order to connect search marketer’s desires with consumers’, Google should roll out a new product offering within AdWords: Social Paid Ads. This offering would allow paid search marketers to serve special ads that immediately call out that the domain of your landing page was shared by a searcher’s connections.

Social Filters:

As Google’s database of shared information continues to grow, it would be very beneficial to filter by “Results Shared by your Connections”. The slash search engine, Blekko, already enabled this feature, but they are lacking the database to fully pull it off.

Google+ Comment Plugin:

As the +1 Button continues to span across websites, there’s a clear opportunity to allow these sharers the ability to add their voice to the +1 as they browse a website. Similar to Facebook’s Comment plugin, this would immediately post the user’s comment on Google+ and potentially influence the idea of Social Meta Information above.

What are your ideas on how Google can make its core business more social? Sound off in the comments.

On this episode of, “W.W.G.D.?” (What Would Google Do?), we present to you – Google Related.   Google Related is a new Chrome extension/Google toolbar feature that enables users to view content that is related to the site they are browsing.  For instance, if I’m browsing on restaurant XYZ’s webpage, Google Related will appear as a toolbar on the bottom of the screen, suggesting several options related to this site – including reviews of restaurant XYZ, mapping the location, or viewing images etc., all while staying on the restaurant’s web page.

Keeping it all in the Google family, Google also allows you to “Google+” anything that you find interesting in the Related section, allowing you to show your friends topics or things that interest you.

I installed Google Related and navigated to the Michael Jackson official website to test the tool out.  At the bottom of the webpage, the Google Related bar appeared and suggested videos, images and articles on the web that relate to M.J.

• Google suggested web articles from TMZ, Wikipedia, Billboard.com, amongst others. (You can Google+ these articles as you read)

• I also began to watch Thriller, from the Videos section of Related.

I was unable to find the Google Related tool on every site.  It seems like this feature may still be rolling out to additional sites.  Or possibly, the toolbar won’t show on every given site.  For the other sites where the toolbar was present, it was interesting to see that Google would suggest a competing brand on a site that you are already browsing.  For example, I was browsing a specific hotel brand website and Google suggested another hotel brand. I’m sure brands wouldn’t be too pleased with Google suggesting competing brands/sites while users are viewing their page.

Although there are no ads on Google Related, I’m curious if this will have any impact on the way users search.  This seems to fall along the lines of contextual targeting, in that users are not actually searching for your brand/site, but instead are being fed relevant information that relates to what they are interested in.

You can learn more about the Google Related feature here.  Have you used Google Related yet? If so, what are your thoughts?