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Why Marketers Struggle With Cross-Platform Programmatic

brianmikaliseditedThe Sell-Sider” is a column written by the sell side of the digital media community.

Today’s column is written by Brian Mikalis, senior vice president of monetization at Pandora.

In general, I’m a huge fan of making the buying and selling of digital ads more efficient and effective. This desire to continually evolve and improve the buy and sell process is one of the many reasons why the promise of programmatic buying is so compelling. Through automation and machine-based decisioning, programmatic can create efficiencies for marketers not only in terms of operational overhead, but also improved performance and higher return on ad spending.

My excitement is tempered, however, when I talk to marketers about applying programmatic capabilities beyond the desktop and into the world of mobile. While the potential of cross-device programmatic is great, there are still many hurdles that need to be overcome before cross-platform programmatic can achieve its rightful share of the marketing mix.

These hurdles are especially high for advertisers that are racing to supplement programmatic Web buying with mobile programmatic. That’s because I see what many marketers haven’t realized yet when looking at these two types of exchanges: We’re essentially looking at an apple and an orange.


Advertising Fraud: It’s Time For Asymmetrical Warfare

ted"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Ted McConnell, an independent consultant in the digital marketing space.

Many Internet industry players are chiming in about how to fight ad fraud, but the scope, scale and capability of the bad guys demand something more strategic and harder-hitting than the suggestions I’ve seen to date.

With as much as $14 billion a year being stolen from advertisers, we need more than publishers adding controls to their infrastructures or a few advertisers buying antifraud services. Way more. Net neutrality is not a solution and freedom isn’t free.

How Big And How Bad?

For perspective, there were about 5,000 bank robberies in the US in 2011, with an average yield of $7,600, according to the FBI. The estimated size of fraud against advertisers varies, but $14 billion per year is the minimum estimate by Augustine Fou, a digital forensics expert. That would be more than 5,000 bank robberies per day, with a getaway car that travels at the speed of light.


The New Star Of The Shopper Marketing Suite

jasonyoung“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Jason Young, CEO at Crisp Media.

If you work in shopper marketing today, take note: Mobile will do to your business what the Web did to direct response.

To see what I mean, consider the history of direct response. Back in the days before the Internet, direct response and direct marketing (DM) were pretty much the bottom of the marketing barrel. TV was where the big budgets and big brands went. Direct was where big brands spent their below-the-line marketing dollars and where second-tier brands clogged up mailboxes.

Why was DM an afterthought? A lot of it boiled down to a disconnect between content and data. On the one hand, direct mail was universally recognized as the gold standard for customer insight and ROI. If someone called your 1-800 number, it meant your marketing worked. But on an engagement level, direct TV ads, mailers and catalogs were no match for the most engaging channel of all: television. Brands were left with the hard choice between data-driven marketing and engagement-driven advertising. Brand engagement won and direct marketing lost.


Placeability: Key To Measuring The Accuracy And Legitimacy Of Mobile Signals

laurenmoores“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Lauren Moores, vice president of analytics at Dstillery.

The use of location data as a signal for content messaging, user functionality and context targeting continues to grow. At the same time, as we have seen with other emerging data streams, with more signal comes more noise. The likelihood of using inaccurate or even fraudulent location signals is increasing.

As with any of the digital signals we harness, location data, whether it’s from mobile phones, tablets or wearables, is only as good as its origin and classification. Don’t ever forget the importance of placeability, which is the accuracy of the location data we’re receiving.

Think about your own experience using applications that rely on location to provide content or functionality. On a recent road trip, for example, I found that as often as not at least one of my map apps could not accurately determine my current location or reverted back to a location from hours before. Similarly, how many times have you used Uber or Hailo and had to manually adjust the pin to ensure a pickup within a few feet and not blocks away?


Dirty Tricks, Red Flags And Pitfalls You Should Know About ROI

jean-baptiste-rudelle“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Jean-Baptiste Rudelle, CEO and co-founder at Criteo.

Return on investment (ROI) is the only thing that matters for an advertiser: How much return am I really getting for my money?

To calculate ROI, typically you will define a key metric against which you’ll measure the impact of display ads. With a retail or travel website, for example, you would measure direct sales generated from your display ads or, more specifically, visits generated by those ads and the conversion into sales. For other verticals, such as automotive or CPG, conversions can be a test drive, an application submission or other industry-specific business metric. Once the metric is chosen, you need to decide when and how to attribute a conversion to this specific ad campaign.

This is the point where things become slightly more complicated.


Dstillery Chief Data Scientist Talks Data Science And Paid Advertising

Claudia PerlichDstillery's investment in data science dates to 2008, when the company – then known as Media6degrees – first applied big data analysis with a social skew. Since then it has broadened its focus to a wider range of digital media, but has retained its emphasis on the data.

The person in charge of those efforts today is Claudia Perlich. As chief scientist, she oversees the data and algorithms that drive decisioning, targeting and fraud detection for the programmatic ad network.

She started four years ago at Dstillery, where top clients include American Express, AT&T, Time Warner Cable and Neiman Marcus. Previously she worked for IBM Research focusing on predictive modeling and marketing.

Perlich spoke to AdExchanger about data science as it relates to paid advertising, programmatic methodologies and cross-device targeting.

AdExchanger: In what category do you bucket yourself? Any interest in launching a "self serve" business?

CLAUDIA PERLICH: The "bucket" question has always been a challenge for us. Terry Kawaja puts Dstillery in the "Targeted Ad Network" bucket on his LUMAscape, which is probably the most appropriate. But our services encompass the core of a DSP and the core of a DMP. We are a company focused on identifying new customers for our marketing partners, and we provide a full suite of services allowing those partners to execute on that intelligence across any channel. (more…)

Measuring Mobile’s Ability to Make Money

eddiedeguia“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Eddie DeGuia, general manager at Motility Ads.

Mobile is in a funny space. Usage is going through the roof. Mobile accounts for nearly 20% of Web usage while mobile ad revenue grew by 47% between 2012 and 2013, according to Mary Meeker’s latest Internet Trends presentation.

With m-commerce taking off, the sky is the limit. But how does all of this actually work?

Today, m-commerce is generally about shifting shopping behavior from one device to another. There’s nothing wrong with that approach, but it isn’t as exciting as generating brand new revenue. Mobile does create the possibilities for new revenue, but from a marketing perspective there are some challenges to overcome. The first is how to drive incremental sales. The second is accurately attributing those sales from a customer interaction perspective.


Is It Time To Break Up With Your Managed Services Provider?

lanceneuhauser“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Lance Neuhauser, CEO at 4C.

It’s an eternal question in a marketer’s life: Should you choose the path of the agency or a specialized point solution?

At the outset, employing a managed services technology solution can be a savvy choice. Any time a new sphere like social media is created, agencies often fail to adopt and master the required technical skills quickly enough. Point solutions specializing in one specific media provide the speed and know-how brands need to dive into cutting-edge technology and gain a competitive edge.

So if a smart decision carried you into a managed services technology relationship, why would it be a smarter decision to ultimately shift back into one with an agency?

And when you make the move, how do you decide which agency best aligns with your revamped needs?


How Retargeting Can Jeopardize Revenue, Brand Trust And User Satisfaction

timmayerupdated“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Tim Mayer, chief marketing officer at Trueffect.

Retargeting is a great way to engage with consumers who have already demonstrated interest in your product or service and have entered the consideration phase of your purchase funnel.

Many marketers view retargeting as an opportunity to get a user back to their websites where they will move down the funnel, but retargeting is more complex than recapturing a wayward user. Fine-tuning is required. Often, there are cases in retargeting that lead to lost revenue, diminishing customer satisfaction and damaged user trust.

Here are three common use cases where retargeting can lower your potential:

Case No. 1: A user books a rental car directly through the rental car company’s website, then visits Facebook. In the right-hand column of Facebook, the user is retargeted with a promotional ad that offers 20% off their next booking at the same rental car company. The user clicks on the ad, which goes to the website, cancels the existing booking and then books the same car rental with the 20% off certificate code. The result: lost revenue.


The Bartender’s Guide To Blending Better Mobile Audiences

dansilver“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Dan Silver, director of marketing at xAd.

Two parts first-party data, a splash of third-party segmentation, garnished with a slice of real-time consumer behavior. If only building mobile audiences were as easy as mixing your favorite cocktail.

There is a recipe, however, and it’s not as guarded as Coca-Cola’s secret formula. The recipe for an accurate mobile audience starts with location data. Understanding this essential ingredient, along with its components, will allow you to better evaluate its potency.

Step 1: Base Ingredients (Location Data)

Awareness of the forms of location data that are available is the first step to building more accurate mobile audiences. To understand how location is an indicator of audience, the place to start is with the consumer. We have a home (hopefully), we have a job (in most cases) and we have our leisure time (again, hopefully). So there is our mixture – home, work and everywhere else.  Now, what types of data are tied to these locations?