As online retailers gear up for this holiday season, competition on the marketing front is already heating up. Top media-buying executives are readying plans to secure the best keywords for specific products, SKUs and industries.

But the savviest marketers understand that to make the most of their search marketing investments this year, they will need more than just deep pockets or keyword optimization. They’ll need a lot of help from the display advertising world.

Online retailers and marketers have recently come to more fully comprehend the important contributions that different advertising media channels, such as display, video and mobile, make to their search marketing investments. This includes the beneficial role that display advertising plays in boosting holiday search marketing performance. And it makes perfect sense.

Are consumers likely to buy from a retailer they’ve never heard of before? Will they be inspired to make a purchase based on a special offer without seeing a promotional ad? Probably not. But if consumers have seen a series of ads about a retailer when they narrow their search for the perfect holiday gift, they are more likely to select the recognized brand.

How important is display in making search marketing campaigns a success? Recent research has shown that display advertising lifts search conversions by 30% on average.

Retailers and online marketers can leverage the power of display to help make this one of their most successful holiday seasons yet. Here are three actions you can take to get started:

1. Display Re-Marketing – First, it’s important to re-engage with consumers who have purchased from you before. By re-marketing to them via display advertising, retailers can remind buyers they are ready to serve them. It’s also important for retailers to be extra aggressive in their re-marketing efforts. For example, expand your target audience beyond buyers to include past site visitors. Also, increase the frequency of your re-marketing campaigns and don’t forget to be creative. Serving the same ads over and over again will not help a retailer to get noticed. Change it up!

2. Pave the Way for New Customers – The most effective way for retailers to bring new customers through the conversion funnel is to tie together their search and display campaigns. Research has shown that online marketers that take the time to build brand awareness via display advertising are more likely to get clicks on search ads (with a higher conversion rate) than marketers that haven’t.

It’s this double whammy of increased clicks and higher conversions that reinforces the value of display. But it’s equally important to be targeted with your brand-building activities. One way is by combining display ads with audience information from leading data providers like Nielsen and TARGUSinfo.

These data providers offer invaluable demographic and psychographic information about specific online buyer segments. Retailers can use this data to ensure that display advertisements are reaching their ideal audiences. In addition, this rich audience data can be used in conjunction with Real Time Bidding sites to better target customers, while leveraging the cost-savings benefits RTBs provide.

3. Tap Attribution for Holistic Measurement – You also need to understand just how much to invest in display and search to maximize results. For retailers, display and search work together to drive performance. But online marketers have traditionally measured the performance of their display and search campaigns separately.

This outdated, siloed approach to measurement offers no insight into the assist that value display advertising provides in driving search results. In order to accurately understand the complex interactions between search and display and then make proper investment decisions, it’s essential to measure them holistically.

The only way to accomplish this on the scale needed in today’s complex cross-channel marketing world is with attribution analysis. Using a series of sophisticated algorithms, attribution measurement identifies the influence each aspect of a combined display and search campaign has on overall performance. This includes pinpointing exactly what creative works best in each channel to drive optimal performance.

This holiday buying season, the online marketing game is more sophisticated and competitive than ever. But by taking a strategic approach to investing in and accurately measuring the performance of your cross-channel campaigns, your company will be positioned to reap the greatest of rewards.

We all understand we are still not in a sustainable economic recovery since 2008 and it is well documented that consumer spending has only recovered in some categories. Everyone in the digital online advertising industry intimately understands the pressure to spend digital dollars efficiently and measure the right results or face the possibility of losing brands and clients.

With that in mind, the most efficient, effective and demonstrable way digital marketing can be held accountable is through dynamic fractional attribution modeling. As Amy Manus recently wrote in ClickZ Academy: “For the past 10 years, looking at the ‘last click’ model may have worked; today, it paints an inaccurate picture given the decrease in clicks, the increase in display and paid search efforts, the impact of social media, and the need to look at a more integrated cross channel marketing picture.”

Being a digital agency in today’s market; one of the most solid and economic ways to keep clients happy is to maximize their ROAS through real dynamic fractional attribution modeling to maximize ROI. No equation is more balanced right now than Agencies + Fractional Attribution = Happy Brands.

Here’s why:
1. It quantifies the return on marketing spend.
Merely having your agency accept the “last click” and/or “last impression” success tracking is so old school. In comparison to dynamic fractional attribution modeling that should be providing actionable optimization recommendations on where to reallocate those marketing dollars is what gives your agency an edge when it comes to the inevitable status update meeting when the client wants to know “what have you done for us lately to improve our campaign effectiveness, and what are you going to do for us moving forward to continue to get a higher return on our ad spend?”

2. It quantifies the agencies value.
There’s an old saying in corporate America: “Everybody’s happy when the numbers are good.” We’re likely entering an economic cycle where sales numbers won’t be so positive, and media performance will be under intense pressure.

Here’s the light bulb going off moment: Imagine a world where a client can understand all the cross channel media sources that generate incremental revenue versus suspecting the same “last click” reports the client is starting to view as superficial. Real Dynamic Fractional Attribution modeling raises actionable optimization recommendations and analytics up to another level from just cost per click, cost per impression, etc. to attributable performance across all campaigns. See the world where your agency discovers digital media analytics that generates incremental revenue and a much higher return on overall ad spend, spending the same marketing dollars but getting a much higher ROI.

3. It adds data knowledge, and data knowledge is king.
Everyone is busier today then ever in corporate America. Seems today our calendars are back to back to back meetings with no real time for other projects or taking away from personal time. In the past, there were more people to crunch numbers and analyze data. However, today even the highest level positions are expected to do it all: be strategic, be forward thinking, make key decisions, be great leaders of people, manage politics and be very numbers driven. The problem is there just is less time in the day to do it all.

Thus now is the time for agencies to shift and reposition themselves with clients. Instead of being information sources as it wasn’t too long ago where we didn’t have the breadth and wealth of data available today, agencies now have to shift to data knowledge sources. Data knowledge sources (Agencies) must save their clients’ money. Data information sources deliver reports and metrics. Knowledge sources must quantify for every client how much money they saved on overall ad spend and how did that translate into ROI.

For more information on Adometry Ad Analytics Saas Solution Suite that provides better data with better science that equals actionable optimization recommendations that provide a 20-50% ROAS visit www.adometry.com.

Better Data

Built on the strongest verification platform available today

Ad Analytics Analyzes 100% of the display impression data

Adometry’s attribution analysis offering Attribute uses 100% of available data, meaning every display impression, e-mail, search click, or direct navigation. Rather than a sample of data, such as clicks (site visits), conversions, or view-through impressions, Attribute models every single interaction a visitor has with a brand, even if it didn’t result in a click or a conversion. No other attribution offering is similar.

Additionally, Attribute is built on a foundational ad verification platform offered separately as Adometry Validate. As much as 30% of all display impressions fail to reach the target audience due to inappropriate placement (site, geo), unviewable ads (below-the-fold, invalid impressions) or simply poor targeting. Including those invalid impressions in an attribution model would greatly skew the analysis, resulting in inaccurate conclusions and suboptimal decisions. Attribute models are built on better data.

Better Science

Data driven attribution model via the deepest data mining and predictive modeling practices

Dynamic cross-channel digital advertising fractional attribution

Attribute provides a data-driven, scientific attribution model built with predictive modeling and data mining techniques. Adometry’s statistical approach differs from other solutions in that the data determines the proper attribution weights, not a predetermined model or human intuition. Adometry has processed and analyzed billions of clicks and impressions monthly since 2006 for online advertisers, ad networks, and publishers. Adometry has developed algorithms for analyzing massive amounts of data in real time to produce quality metrics and accurate, actionable predictive models.

Actionable Optimization

Specific, actionable campaign-level recommendations to gain a 30-50% return on your ad spend and lift

Automated optimization that projects results for a higher conversion rate

Adometry’s Attribute produces more than just an attribution model with accurate weights for different channels. Attribute produces attribution weights for each and every element of a campaign, or across campaigns. Attribute includes an optimization module that makes specific recommendations, and provides projected results, for improving campaign performance in-flight or to inform future campaigns. No other attribution analysis solution provides specific actionable recommendations at the campaign level.

As online display advertising experiences unprecedented growth, how can brands ensure success in this arena where results are difficult to track and measure? We take a look into why Internet display advertising metrics can be so elusive and what to do about it.

The Internet is more accessible and content-rich than ever before thanks to new online technologies and trends. Whether driven by social media connectivity, content diversity or smart phone accessibility, Americans are spending as much time online as watching television — and advertisers are taking notice.

Online display advertising, once overshadowed by search engine advertising, is making a solid, indisputable comeback. Unlike the search advertising market where growth has slowed and is expected to remain relatively flat for years to come, industry analysts estimate that online display advertising will grow annually by 15 percent. In fact, marketing research company, comScore, reported that U.S. Internet users viewed 1.1 trillion display ads within the first quarter of 2010, a 15 percent increase over the previous year.

The explosive growth of online display advertising is offering brands exciting opportunities to reach precisely targeted audiences. However, this rapid growth has also resulted in a crowded, complex environment that makes it difficult to track online display advertising effectiveness in key areas:

• Reaching the right audience with the right message at the right time
• Achieving goals such as brand awareness and sales conversions
• Optimizing advertising investments

Advertisers in the online space are left with unanswered questions and poorly-spent budgets. Industry analysts estimate that advertisers will spend $25 billion on display advertising by the end of this year, a fraction of television advertising budgets. Now more than ever, there is a need for comprehensive, cross-platform analytics to increase advertisers’ confidence in online display advertising. Advertisers need the right tools to help make the most of this promising opportunity.

Opportunity Breeds Chaos
Over the past several years, hundreds of new companies have entered the market offering solutions to help advertisers and ad inventory providers reach a growing online audience through display advertising.

There are currently thousands of online publishers and websites selling display advertising inventory directly to brands. There are more than 400 different ad networks and over 50 demand side platforms (DSPs) offering different ways to streamline the ad buying process. There are also countless companies delivering real time bidding (RTB) capabilities, data providers providing enhanced targeting technologies and yield optimization platforms promising publishers the best price for their inventory.

The sheer number of options and combinations has created an overwhelming problem for display advertisers and agencies — how to measure success in a marketplace in which advertising campaign data is distributed among many different players.

In the search advertising market, Google, Yahoo! and Microsoft make measurement fairly simple because they own the data throughout the entire ad delivery lifecycle. There are many SEM tools available that will provide an integrated view of campaigns across all search providers. But in the display world, it’s not that easy. There is currently no seamless way to deliver a unified view into how campaigns are performing across different ad networks, publishers, ad providers, DSPs and other middlemen.

The growing number of players in the display advertising delivery chain has created a lack of transparency for brands. It has become impossible to answer even basic questions about online ad campaigns such as:
□ Were the ads I purchased actually served?
□ Where did the ads appear?
□ Did a real person view the ads?
□ Did the ads reach my target audience?
□ How can I allocate my budget more effectively?

The inability to accurately measure results and performance is one of the reasons many brands are hesitant to invest more dollars in the display advertising market.

Few Measurement Options Mean Missed Opportunities for Online Display Advertisers
There are a variety of different companies trying to help solve pieces of the puzzle when it comes to display ad campaign measurement. However, none are able to help brands properly measure campaign effectiveness across the entire value chain.

For example, providers that help advertisers measure audience “reach” are typically only telling brands how many pixels are being fired during a display campaign. They aren’t telling brands if their ads were viewed by the proper demographic or even if they were actually seen by a real person.

Some ad measurement companies equate “engagement” in display with click through rates (CTRs). While CTRs are a great way to gauge ad performance for direct response marketing campaigns or SEM, clicks on a display ad with no call to action doesn’t mean much to an advertiser looking to create brand awareness.

The negative impact of this piecemeal approach to measuring ad campaign success is significant. According to industry statistics, more than 60 percent of advertisers admitted they will not invest more dollars into online display advertising until more comprehensive ways to measure display campaign performance are developed. At a time when Internet use is increasing exponentially, brands are missing a powerful opportunity to reach customers.

Comprehensive Cross-Platform Ad Analytics Cut Through the Chaos
Knowledge is power, and never more so than when trying to make online marketing decisions. For years, online ad campaign analytics have been a pervasive challenge, and a barrier to realizing Internet display advertising’s full potential. But now, as the industry realizes the limit of search engine advertising, it’s time to focus on solving the display advertising measurement issue.

Just as web analytics help companies’ measure website traffic and SEM analytics tools help search advertisers track and measure PPC performance, a unified ad analytics approach can effectively measure display advertising campaign performance.

It’s unlikely that one company or provider will control all the touch points in the display advertising industry as they do in the search world. That’s why it’s crucial that any approach to display ad measurement has the ability to aggregate information from a wide range of platforms, providers, sites and sources.

Unlike web analytics that can be easily captured from a few sources, online ad analytics must pull data from hundreds of platforms, sources and sites.

Ad analytics can take the on-site capabilities of a web analytics system and put them to work measuring views and interactions across multiple sites and platforms where you have an online advertising presence. The resulting breadth and depth of knowledge will offer the guidance necessary to drive a successful display advertising campaign. Armed with this valuable data, advertisers and agencies can identify and remove invalid and low quality impressions from campaigns and optimize ad performance to improve campaign efficiencies and overall return on advertising spending. It can be an extremely powerful tool in cutting through the clutter and honing in on success.

Putting it All Together: A Comprehensive, Yet Precise, Three-Tiered Measurement Approach
A comprehensive approach to ad analytics must go further than pulling information from multiple sources. An ad analytics system must also be able to collect the right kind of data and then intelligently interpret it to form the basis of wise advertising placement and creative decisions. A successful campaign involves many different factors including ad placement compliance, audience verification, attribution analysis, invalid user and fraud detection, reach and frequency and campaign optimization.

The digital marketing business takes a lot of heat for inconsistent measurement. Even the IAB is pushing for more standardized measurement practices, which is a quest of questionable merit. The more ways you can spell digital success, the better. When it comes to reaching affluent customers in digital marketing, there’s a sure way to spell success: i-n-d-e-x.

Here’s why — marketing to affluent customers requires comparisons. Brands that are trying to reach the top tier of the income brackets must do so by comparing their net worth and behavioral segments to a baseline. As examples, the Consumer Confidence Index works only because it is compared to previous months, while the American Consumer Satisfaction Index works because it is compared to a baseline of 100 (for excellence.) When reaching affluent customers via ad platforms, content sites or networks, it’s the index that really matters. It is the basis for showcasing the strength with which that content can properly reach affluent customers.

In short, in the digital marketing audience business, you are what you index. Almost any company can show how it indexes versus the average American or even a baseline customer. But the real power comes when a digital marketing property can index its audience compared not only to the average customer, but to the affluent customer. Here are some examples from a recent data project that’s nearing completion at Adara Media:

• According to Nielsen, affluent customers (100K+) as compared to the average American consumer index at 288 for international travel. The audience segments in our audience platform indexes at 886.

• The average affluent customer segment for recent domestic car rentals indexes at 285; us: 801

• Airline and hotel loyalty programs have a 200 index for the average affluent; us: 639

• For direct marketing purchases, affluents index at 217 vs. the average consumer; us: 610

The list goes on. This is not a claim that our audiences’ indexes are higher than other ad platforms or content owners. Instead, it shows that indexing is an effective predictor of audience success. It’s not enough to know that affluent customers buy more, rent more, travel more and engage more. The questions must be asked with more precision. Do they travel frequently? Domestically? Are they currently traveling? Those questions are answered with their own index and must be delivered with precision.

There are also some index numbers, admittedly lower on our segment list, that approach even indexes. For example, entertainment purchases (movies, music, concert tickets) don’t index much higher for affluent than the average consumer. As a result, our database doesn’t trend as well in that direction for those segments.

It goes to show that comparison means everything in terms of evaluating media and the delivery mechanisms to reach affluent people. Going with the index is going to be a sure-fire approach for advertisers and media planners. Pick the highest-indexing segments for affluent and the media buy is that much more precise and powerful. No matter how you spell it.

Attribute – Attribution Index
Attribute’s dynamic fractional attribution provides the data necessary to calculate a new metric for each campaign dimension. Called the Adometry Attribution Index, this proprietary Adometry metric measures the conversion propensity for every campaign setting or combination of settings. For example, a creative/site combination with an Attribution Index = 3.5 provides three-and-a-half times the normal conversion rate.

Marketers Crave Solutions That Provide Richer Performance and Audience Insights.

Join Adometry and Forrester Research for a fascinating discussion of Forrester’s latest findings for Interactive Marketers. After interviewing hundreds of interactive marketing managers controlling $ millions in online budget, Forrester has identified critical needs currently going unmet that have a dramatic effect on digital spending. Steve O’Brien wil interview Joanna O’Connell to discuss the research and findings in depth and explain how Forrester arrives at the conclusion that the varied needs of marketers – display, search, and cross-channel – are best addressed by a new breed of audience measurement solutions. These new audience measurement solutions will be described and compared to existing alternatives.

In this special report Forrester Research evaluated the attitudes, challenges and needs of display buyers with respect to topics including media and audience verification, measurement and insights (including multi-channel attribution) and the impact these things have on buyers’ investment in display advertising.

Key Findings
Forrester’s study yielded the following key findings:
· Display advertising continues to mature, with adoption and investment on the rise.
· A lack of measurable results and a dearth of media and audience insights hampers further investment.
· Current technology point solutions address these challenges in a limited or disjointed way.
· Marketers would benefit from a robust, flexible suite of technology solutions.

For more information and to download the report click here.

Presenter: Steve O’Brien, VP, Marketing, Adometry, Inc.
Guest Speaker: Joanna O’Connell, Senior Analyst, Interactive Marketing, Forrester Research

Click here to Register Today!

Tasting the Various Flavors of Attribution Analysis by Adotas.

Everyday, marketers search for the right combination of search advertising, social marketing and display advertising that will help them achieve a desired result – whether it be visitors to a web site or actual sales. This has made “attribution” a hot topic among interactive marketers.

Simply put, attribution analysis is a method advertisers use to understand the influence and impact individual advertisements and marketing activities are having on campaign results.

The importance of getting attribution right cannot be overestimated. It helps determine how to adjust campaigns going forward. It also provides tremendous insight into how similar campaigns can be optimized to produce better results.

The biggest problem with attribution analysis today is not all approaches are created equal. Lots of folks are using the term “attribution analysis,” but not everyone is talking about the same thing. It’s important to understand the different flavors of attribution currently available and determine which ones provide the greatest value for advertisers.

1. Last-Click Attribution: The most common attribution model is called “last-click attribution,” and its name pretty much describes the approach. Last-click attribution assigns tremendous value – 100% of the credit for success – to the click (or event) that brought the visitor to the marketer’s web site.

The problem with this approach is it ignores all other interactions and campaigns, or at least assigns them zero value. This clearly incorrect and misleading. It would be like giving credit for the Super Bowl win only to the receiver who made the last touchdown of the game, ignoring all other members of the team and all the plays that occurred before and after.

2. Even Attribution: As an acknowledgement that crediting the last click with 100% of the conversion credit is inherently flawed, early attribution practitioners devised a way to share the credit with other parts of their campaigns. “Even attribution” would apply equal credit to every event that occurred in a visitor’s conversion path. So, if the new customer were exposed to three display ads and then searched and clicked (for a total of four different events), each event would get 25% of the credit for the conversion.

In our previous Super Bowl example, it would be like dividing credit equally amongst all players who were on the field on the final play. This is simple but only a slight improvement over last click. And entirely inaccurate.

3. Predetermined Attribution Models: If the only thing wrong with “even attribution” were that credit was divvied up unfairly, then simply devising a fairer model should solve the problem. Predetermined attribution models attempt to do so by assigning a fixed amount of credit to each event in the conversion path, but those percentages are not equal.

For example, a predetermined attribution model might assign 50% credit to the last click/event, 10% to every e-mail interaction, and divide the remainder amongst any display ads the visitor was exposed to. This is like saying that on every play the quarterback gets 50% of the credit, the receiver 10%, and everyone else shares the remainder.

This would work great if every play was a pass, and every pass was completed. Unfortunately, that’s not realistic. Different plays would likely see the shares for credit divvied up in different ways each play. The same would be true for advertising campaigns.

4. Full-Funnel Attribution: An attempt to be more scientific than the previously discussed models, full-funnel attribution purports to measure all activities that contributed to the purchase, or conversion event, throughout the purchase funnel. By taking into account more marketing interactions beside the last click, such as display, search and social campaigns, full-funnel attribution provides the appearance of a more comprehensive attribution model.

However, one of the problems is full-funnel attribution only looks at a sample of the total interactions. This results in the credit being incorrectly weighted, leading to poor decisions and suboptimal campaign adjustments. For example, most full funnel attribution models look only at the paths of converted visitors, ignoring the other 99.9% of marketing interactions that didn’t result in a visit or conversion.

To see how this would impact measurement attempts, take a look at this example of full-funnel attribution in action. If almost every visitor who converted was exposed to Campaign A at one point, a full funnel attribution model might reasonably conclude that Campaign A was a huge success. The model would assign Campaign A large amounts of credit.

But this entirely misses the most important factor that attribution is trying to address: causality. If most of the unconverted visitors were also exposed to Campaign A, but failed to convert, then it’s impossible to assign any credit at all to Campaign A. A marketer using the full-funnel model would incorrectly allocate more budget to Campaign A, when in fact it had no bearing whatsoever on conversions.

5. Fractional Attribution: By far the most accurate attribution model is called “fractional attribution” or “dynamic fractional attribution,” because the model is calculated dynamically for every customer or campaign. As its name implies, fractional attribution measures the influence each part of a campaign had in contributing to the action (e.g. web site visit, sale, etc.) much like full-funnel attribution does.

But a true fractional attribution model doesn’t ignore any of the available data. Each and every display impression, click, social interaction, and e-mail campaign is incorporated into the fractional attribution model. By considering 100% of all campaign data, true patterns and trends can be identified.

For example, a wireless phone provider might run a mix of display ads, search marketing campaigns, and social media strategies as part of a push to promote a new mobile phone. Fractional attribution analysis can tell the wireless provider how much influence each and every one of those marketing events had on the outcome of the campaign by measuring 100% of the campaign events, not just the converted sample.

Some of the buyers may have been exposed to the display campaign, but by analyzing the complete set of data it may be determined that the display campaign had very little impact on purchase behavior. Wouldn’t a marketer want to know this in order to make campaign adjustments?

Attribution is clearly emerging as one of the most powerful and effective measurement tools for interactive marketers. In an advertising world that’s growing in reach and complexity, using the right kind of attribution measurement techniques will ensure that campaigns succeed no matter what new kind of advertising venue or marketing offering becomes available.

There is a new sophisticated Ad Hijacking attack that encompasses multiple channels within the Online Advertising industry to Commit Fraud.

The Adometry Malware Lab has discovered a new highly sophisticated online fraud scheme called Ad hijacking that targets online video, display and search advertisements. Ad hijacking is a particular kind of advertising fraud that aims to create fees for paid ads (clicks, display impressions, video impressions) where none would have occurred organically.

There are three things that stand out. First, the delivery mechanism. Unlike previous schemes, this one does not require the user to download the malware, it can infect the machine simply through visits to a malicious or infected website. Second, this malware also tries to infect personal home firewalls with DNS poisoning. Third, it’s not a single purpose malware scheme but rather one that is taking into account the various ways money changes hands in online advertising.

After a user’s machine is infected by the malware, the malware instructs the machine to perpetrate different kinds of fraud, including video, display and search advertising fraud. Each works slightly differently:

1. PPC Fraud: Visitor’s click on paid or ORGANIC search result link is redirected to a PPC ad network, through multiple arbitrators, and eventually to some results page or advertiser that may or may not be related to the original search. Cost per click fees are generated at each step along the way, and the advertiser is either deprived of a visitor, or pays for a visitor that would have been organic in the first place.
2. Display Impression Inflation: Auto-clickers visit specific publisher sites in the background unbeknownst to the visitor, generating numerous phantom impressions never seen by a human.
3. Video Impression Inflation: Visitor’s click on paid or ORGANIC search result link is redirected to a video site unrelated to the search in order to generate high paying video CPMs with zero value to the advertiser.

The lab has tracked this scheme across many different publisher sites and ad networks over the past six months. These infected sites can be disguised as blogs or made-for-ad search results pages, but other popular sites can be infected if they run ads that are infected. The only one antivirus program that was capable of preventing the malware from being installed was Kaspersky Anti-Virus 2011. It is impossible for the lab to accurately quantify the extent of the malware’s spread, but the proliferation of the attack signature, combined with the ease with which the malware is distributed, leads the lab to believe that the malware is likely infecting tens or even hundreds of thousands of machines.

The lab has seen many examples where this traffic is being stolen from advertisers and delivered to ad networks that profited from the scheme. We have also seen a number of ad networks who were unaware they were participants in this scheme as well. It is therefore difficult to name specific networks as being perpetrators. We are working with all our customers to make sure they understand the profile of the attacks and how to prevent them. Advertisers, of course, are the ultimate victims and any fees or costs are borne by them.

While Windows is the only operating system we observed to be susceptible to infection, the malware can infect home firewalls and any OS/browser behind the firewall will experience the search hijacking.

Adometry is helping individual advertisers, publishers and ad networks identify if they’re affected. Advertisers should work only with reputable third party ad networks that have stringent quality control measures in place and comprehensive reporting. The best way for all parties to protect themselves is to audit their advertising traffic on an ongoing basis.

Here is a video showing how the Ad Hijacking occurs in real time:
Malware Search Hijacking Video

Imagine you run an online business, or a business that depends on the web in some way. (Ok, that probably wasn’t a stretch.) You would never even consider trying to run your business without Web analytics. Web analytics tells you how many visitors came to your site, how they got there, how long they stayed, what they looked at, whether they bought something, and whether they ever come back. And if so, how often and what else do they buy? Web analytics is an essential part of any business that leverages the power of the Internet and no interactive marketer would consider trying to do without at least one Web analytics tool like Omniture, Coremetrics or Google Analytics.

Yet marketers this year will spend over $25 billion running online ads without comprehensive ad analytics. What’s the difference? A lot.

1. What is the difference between Web Analytics and Ad Analytics? – Web Analytics is primarily useful for on-site measurement of user traffic once it reaches a web site. Ad Analytics looks at the off-site impact of online advertising campaigns, including display, search, e-mail, social, mobile, etc.

Consider that click through rates for online ads hover around 0.1% and then think about the logic of measuring campaign success by discarding 99.9% of the available data. That’s what it means to use Web analytics to try to measure and manage online campaigns. Web analytics deliver deep, insightful data about the behavior of 0.1% of your audience. Ad analytics leverages the other 99.9% to drive improved online results.

An analogy might make it even clearer. For Web Analytics, an equivalent would be a traditional brick and mortar retail store that analyzes visitors and their behavior once they are inside the retail store. Ad Analytics is quite different. In the bricks and mortar example, it’s equivalent to the retailer understanding which radio ads or billboards drew a visitor into the store in the first place. And which TV spots or newspaper ads weren’t working, so the budget should be reallocated elsewhere. Ad Analytics measures the interactions with your advertisements and marketing campaigns run on other web sites and online properties (other than your web site) and which ads/properties are performing best.

2. Do I need to care about Ad Analytics? – Absolutely! Understanding Ad Analytics is the only way to understand how visitors truly find you, and what campaigns or creative need quick corrective action. Ad Analytics is essential to evaluating online media spend across an expanding number of web, digital and mobile platforms and channels.

3. What is the role of attribution measuring campaign effectiveness? – Attribution analysis is a key component of ad analytics – as it tells you what worked and what didn’t in trying to attract new customers. Attribution analysis is the true secret sauce of ad analytics. With attribution metrics one can optimize campaigns, creative, and placements to drive maximum return on ad spend (ROAS).

As online display advertising becomes more popular among brands, ad analytics is becoming more important to helping them understand where to reach new audiences and how to maximize the positive effects of their message. Ad Analytics provides online advertisers with valuable information on multiple facets of online campaigns, including ad verification, attribution and brand safety, all of which combine to determine the influence of ad campaigns on audiences and the impact on business results.

Because digital channels are expanding quickly to more interactive, social and mobile platforms, online marketers need to understand how the combination of web analytics and ad analytics work together to help them fine tune their campaigns and better optimize how they spend online marketing dollars.

Over the past year, online advertisers and their agency counterparts have fretted, privately and publicly, about the growing concern over the issue of data leakage — or who has access to online marketing and advertising campaign data. But the part of the data leakage story most have danced around is how advertisers themselves can put their treasure troves of data to work. With the expansion of advertising networks and mobile and social options, along with advertising optimization, determining how to use this vast new data pool is no easy task.

Third-party ad servers like DoubleClick and data brokers like BlueKai have built their businesses on finding ways to put other people’s ad campaign data to good use. For advertisers, however, it’s a different story. While most are well versed in traditional ad campaign metrics, such as website interactions and click-through rates (CTRs), they’re just scratching the surface when it comes to understanding what happens to ads as they cycle through various ad networks, media properties, and other online publishers.

There seems to be two reasons for this lack of awareness among online advertisers. First, until recently brands really haven’t needed to dig deep into their data to be successful in this initial wave of cost-per-click, video, and banner advertising. Metrics like CTRs and “last ad view conversions” were sufficient for helping advertisers deliver returns on their campaigns. But in the new world of distributed and social advertising, brands are beginning to understand they need to know a lot more to make sound decisions about what contributed to a campaign’s success or failure in order to adjust plans going forward.

Second, brands are facing the fact they may not have the in-house expertise or the technology necessary to mine the salient information they need from the petabytes of complex and rich data collected from ad campaigns. Yes, they may know the value of their data, but putting it to work quickly and effectively is a challenge for even the most experienced advertising team.

As online display and brand advertising enters a new era, advertisers need to take the necessary first steps to better understand how to put their own log file data to work. Here are a few to get you started:

Find the data
If you don’t yet have access to your ad campaign log files, you need to change that. Make sure whoever manages your online campaigns (whether it be an agency or internal resource) knows exactly where the data is, who’s using it, and how to access it.

Hire experts
Make sure you have resources on your team that know how to curate and use complex campaign data. Whether it’s an internal staff member or a consultant from outside the company, you need to assemble a team of people who have a deep understanding of analytics in order to make the most of your ad campaign data.

Leverage technology
While an understanding of analytics is a cornerstone to putting data to work, you also need the right tools to help. A simple spreadsheet won’t cut it. Ad impression data is large and complex. While many brands and advertising professionals are comfortable with simple analytics tools, such as Google analytics or Omniture (which measures interaction with website performance), they realize these tools only tell them part of the story. To properly analyze large amounts of ad campaign data, a deeper dive and more processing power is necessary. New kinds of easy to use and powerful analytics tools are emerging to help.

Pay attention to new metrics
It’s important for advertisers to expand their view of ad performance metrics beyond things like traditional last-click attribution. Most campaign data includes rich information about your campaigns, such as audience type, location, timing, creative, and other factors that contribute to campaign lift and audience response rates. In order to make the right tweaks and adjustment to campaigns going forward, advertisers need to closely examine how this data contributes to its overall success.

While figuring out how to properly use ad campaign data may seem daunting to most online advertisers, it is the necessary foundation for any successful campaign in this new cross-platform advertising era. By taking some simple steps, all online advertises can prepare and make the most of the opportunities proper ad campaign analysis can contribute to their future.

Paul Pellman is CEO of Adometry.