Age & Gender Targeting Are Broken

Age & Gender Targeting Are Broken

A version of this article first appeared in Adweek.

Over the last few months, several reports have described major inaccuracies in age and gender targeting. Pinsight Media reported that 60% of age data on mobile exchanges is not only inaccurate—it’s also off by an average of 10 years.

This is a big problem—a massive problem, in fact. According to Videology, 41% of digital video campaigns in the U.S. now request ratings verification such as Nielsen DAR or ComScore vCE. This number is up 115% from 19% of campaigns requesting such verification just three years ago. More campaigns are relying on age and gender targeting, yet accuracy, according to Nielsen, has not improved at all since 2014.

The Root of the Problem

Things get even worse when you overlap age with gender. For instance, Nielsen Digital Ad Ratings show that campaigns (across desktop and mobile) reaching females age 25-54 are just 40% precise!

Imagine that—in a time when you can supposedly target a mother of three kids who owns a Keurig in Denver, why is it so hard to just reach a female within a 30-year age range?

The answer, or the root of the problem, lies in the data from which most ad targeting models are derived. Modeled, third-party data is typically used because it is scalable, easy to activate, and has almost infinite types of segments available. Problem is, it's also generally inaccurate.

Why does this matter? The challenge with data-driven ad targeting is similar to the metaphor in building a house. There are various materials and layers to the process. Each has a place in the end product, but what you put at the center, or the foundation, is most important. It’s not wrong to use third-party data, and it does have a place, but it should not be the main mix in your concrete foundation when building your house.

How to Fix It

2017 is the year for marketers to move beyond third-party, modeled data and move toward licensing first-party data from other companies.

As you navigate through the first-party data world, pay attention to how the data is being sourced, as this will have the biggest impact on quality and accuracy. Companies with registration or single-sign-on processes will generally have much higher match rates across devices, which will in turn deliver better scale.

Also, be sure to think about the value exchange between the publisher and its end user. If the user has something to gain by signing up with accurate information, you can be sure that the quality of the data will be much higher. Publishers that also have high engagement rates can then tie a user’s behavior and profile information together, just as Facebook does. 

These types of first-party data owners can partner with Krux, LiveRamp, or similar businesses to make their data easily accessible to marketers. Data owners are given the controls to determine who can and cannot use their data, and marketers are able to identify the partners that meet their objectives. Platforms like Krux and LiveRamp can also combine similar data sets in order to build more scalable segments.

First-party data is far more accurate than third-party data, but we do need more participants in these marketplaces to improve the accessibility and availability of segments. As publisher participation rates and the matching of buyers and sellers continue to improve, these data exchanges will take off.  

What’s Next

The promise of this strategy is that marketers can use first-party data from other companies to chip away at the wasted impressions they are serving to the wrong audiences. The odds that a 25-year-old is in the market for a baby stroller are considerably lower than those for a 35-year-old. Marketers are pouring hefty resources into defining their target audiences, and their campaigns should deliver ads to those segments they’ve picked.

To begin to close this accuracy gap, I propose nailing down the basics this year with something as simple as improving age and gender targeting. Publishers, marketers, and platforms will need to work closely together to make this happen. Next, with a solid foundation of accurate data, we can focus on harder problems like packaging up insights to help target the people marketers need to reach.

Want to learn more about PCH/Media's approach to accurate audience targeting? Get in touch here!

Understanding the Evolution of KPIs

Understanding the Evolution of KPIs

A version of this article first appeared in Target Marketing.

When I sat down to write about the evolution of key ad metrics, I spent a considerable amount of time thinking about how the definitions of words change over time. It dawned on me that, while oftentimes the definitions don’t necessarily change, they do take on new meaning. Think about words like “sick,” “nice,” “sweet,” and “nasty”—their meanings have changed because people started using them in new ways.

Digital media is not immune to this phenomenon. We live in a world where KPIs change and meanings of those KPIs change depending on who you ask.

Two examples of KPIs facing evolving meanings are viewabilty and video completion rate.

Viewability

When the idea of viewability was introduced about three years ago, it was thought of as a metric—some would even call it a vanity metric. It was seen as something you measured alongside impressions and clicks. The first legitimate definition of viewability came from the IAB in 2014, which stated that “a display ad is viewable if 50% or more of its pixels appear on-screen for at least one second.”

Fast-forward to now. While the IAB’s definition of viewability hasn’t changed, what viewability means to the industry has. 

Last year, when GroupM announced that it would have a strict viewability standard of 100%, they immediately changed how anyone working with the world’s largest media investment group thinks about viewability. The same thing has happened industry-wide: viewability is no longer just a metric but rather a standard—it's a primary campaign KPI and, in some places, a currency. GroupM was like the Vine video using the term “on fleek,” and the rest of us are the industry professionals left trying to figure out how to properly work this phrase into conversation. (For the record, I’m a millennial and I still don’t know.)

Viewability is complex because it proves that while we may not all be speaking the same language, we are essentially saying the same thing: advertisers should only have to pay for ads that are actually viewed by humans.

In some ways, the meaning of viewability is a matter of linguistics and philosophy, and it’s a question of how closely we should link the two disciplines. To be successful agency partners, we must understand that GroupM’s standard is not the same as Cadreon’s which is not the same as Accuen’s. Some campaigns look for 100% viewability, some look for 50%, some for two seconds, and some for one second—but while the meaning may differ, the basic philosophy behind the purpose of viewability remains the same.

Video Completion Rate

Video completion rate might seem to be a more straightforward KPI, but it’s actually another example of a shifting metric that is more complex than originally thought.

Video completion rate is no longer just the ratio of completed views to video views. It has evolved. Some agencies still calculate it based on the full length of the video, some consider three seconds in to be a full video view, and some look at the percent viewed by non-human traffic versus human traffic.

If a publisher boasts that they have “high completion rates,” they must understand that this is no longer a linear metric. How will you stack up when your client is only willing to pay you on a cost-per-completed-view basis? 

Planning for the KPIs of Tomorrow

Today, some campaigns measure “non-human traffic,” but tomorrow could they decide that they’re only willing to pay vendors on this metric? If a campaign measures how “on-target” your demographic targeting truly is, how could this evolve into something bigger? 

To speak the same language, we must listen, think, and only then build. Listen to third-party measurement companies and agency clients. Think about how we, as partners, stack up against varied meanings of the same KPI. And build products and content that support these multiple meanings—which will, in turn, help us better prepare for the KPIs of tomorrow.

Get in touch to learn how PCH/Media can help you hit your KPIs and crush your goals.

 

Debunking the Myths of Programmatic Delivery

Debunking the Myths of Programmatic Delivery

A version of this article first appeared in Ad Age.

Programmatic. Automation. Private Marketplaces. Guaranteed Deals.

These are the buzz words that made us all think that everything was simple, required few resources, and would make us not only a ton of money but—more importantly—more margin. We thought we could pull in stronger yield with leaner teams and less overhead. We were wrong, and we've learned a lot through the process. 

Let’s talk through some of the assumptions that carried us into the growth of programmatic deal channels in 2015 and early 2016—and why they turned out to be not as true as we thought they were. 

Programmatic deals don’t require the same sales cycle as managed service. 

Many thought that as the market moved to programmatic, we’d see sales teams as lean as they’d ever been and margins would skyrocket with the decreased overhead. The reality is, while the means of execution have changed, we’re still talking to the same marketers who want transparency and understanding of the content and the sellers they are working with.

Convincing a retail giant to spend tens of thousands of ad dollars with you through programmatic is no different than asking for an IO of the same amount. The real difference comes into play with the delivery and controls that the marketer can keep in-house—the power to change those budgets at any time.  

Set it and forget it—right? 

Wrong. With viewability and performance metrics as the driving force behind keeping a budget live, there really is no “set it and forget it” when it comes to selling media. We need placement and targeting optimizations in order to continue to exceed client benchmarks, and those happen with tools for reporting, helpful automation from systems, and thoughtful human optimization and planning.

Do we need the same resources on call for a private marketplace campaign as a managed service campaign with the same budget? No—but we do still need significant resources to be able to be successful in this field. 

Viewability is one-size-fits-all.

Measuring for viewability—or any of the vanity metrics we all track—is completely dependent on the measurement company used and the guidelines set by the advertiser. Everyone has their own definition of what is acceptable, and both buyers and sellers need to get on the same page with what that is. Who is going to be the measuring partner? What are factors that determine a successful measurement? These are the questions you need to ask before you end up with the “my-reports-don’t-match-yours” headache.

Programmatic deals are going to scale fast and stay strong.

While this one is certainly possible, you have to understand the vulnerability of this business line. Just because a client says they want to run on your inventory and give you a price, target budget, and deal ID, it doesn’t mean that’s money in the bank.  

One of the biggest benefits to buyers here is the level of control that they keep—which means that they can turn off or decrease spend at any time. The risk is worth the reward, but don’t count your chickens before they’re hatched.

The client said yes. Let’s get it live right now!

There’s a lot of troubleshooting that happens to turn on a deal: do both parties have the right connections in place, are your targeted segments passing in the right bid requests, are they applying targeting on their side that is messing up the bid rate? I’m sure this is one that will taper off with time as tech and buyers get more savvy, but it’s not usually a five-minute turnaround to see the revenue flowing in. Don’t forget to thank your ad ops and solutions engineering teams for their help here!

The moral? If it sounds too good to be true, it probably is.

But that doesn’t mean programmatic isn’t a channel to invest heavily in. It’s where we should all be in order to live in an advertising world with transparency, control, and fair value pricing—but it takes work to make it successful.

Regarding the Methbot Report

Regarding the Methbot Report

Publishers Clearing House is aware that our domains, along with thousands of other premium domains, have been included on the list of publishers impersonated by the Russian botnet Methbot (read the full White Ops report here).

We want you to know that we take fraud very seriously and have anti-fraud partnerships in place to protect our clients in situations like this. Throughout the time that Methbot was running, we were actively monitoring malvertising across our sites via MediaTrust, RiskIQ, and GeoEdge. We also have NHT monitoring in place across all video supply via ComScore and MOAT.

It appears that the impact to PCH traffic has been nonexistent and inventory quality remains stable. We will continue to monitor the situation and will keep you posted here on our blog as we learn more.

As always, please feel free to reach out to your PCH rep if you have any questions or concerns. If you’d like to read more about the Methbot operation, check out these articles on CNBC and AdExchanger.

Will the Real Premium Publishers Please Stand Up?

Will the Real Premium Publishers Please Stand Up?

If you have ever asked for an advertising budget from a digital media planner, you’ve most likely been told, “We only work with premium publishers.”

Working for an ad network early on, I remember carefully choosing publishers for media campaigns that would satisfy a brand’s appetite for premium. These publishers were the usual suspects: the big sports names, the ones with the well-known and well-loved acronyms. No games, no social networks—nothing my mother wouldn’t be familiar with. Premium simply meant that the brand would be proud to have their name next to the logo. 

What Does Premium Really Mean?

One of the definitions of the word “premium” is “of exceptional quality or greater value than others of its kind; superior.” The advertising community determines the superiority of one publisher over another and thus gives the “premium” publisher the ability to charge more.

But what does a premium publisher look like today?

Programmatic facilitated a new premium. And the most obvious first signs of this transformation arrived with the growth of mobile advertising.  

Publishers who celebrated their superiority in the desktop world were unpleasantly surprised when they offered their mobile inventory to advertisers in a programmatic environment. Low CPMs and fill rates were met with much head scratching as publishers struggled to understand why their premium stamps of approval were not translating from desktop into mobile.

Many heated conversations transpired between the powerful premium publishers of desktop and their SSPs. Why were the mobile CPMs not complementary to desktop? Why weren’t top advertisers interested in bidding on their inventory? Mobile must not be that important. How dare these DSPs not see the value?

What these publishers failed to understand was that their name alone would no longer demand a plethora of bidding at a high CPM.

So, which mobile publishers were generating the high CPMs?

Mobile app publishers passing device IDs and actual latitude/longitude data became the new “premium.” DSPs and advertisers were willing to pay more—a lot more—for these publishers. As the traditional premium publishers refused to invest in the most sought-after platform (app) and were unwilling to pass the proper data, they were bypassed in superiority by mobile publishers that were—gasp—gaming publishers, utility publishers, publishers with names that were neither well-recognized nor well-loved. They were names I would never have dared to put on a traditional media plan, yet they were now commanding respect and loftier prices in the open exchange.

Programmatic and the Evolution of Premium

EMarketer recently reported that, in 2016, US programmatic digital display ad spending will reach $22.10 billion, an increase of 39.7% over last year, which represents 67.0% of total digital display ad spending in the US. As more and more managed service budgets pour into programmatic, the list of premium publishers continues to evolve. Agencies have become smarter about how they buy digital media. Advertisers are now investing dollars with publishers that previously would not have been allowed in their reception lobby, let alone on a media plan.

Generally speaking, advertisers today are increasingly less concerned about a publisher’s name (within reason) and more concerned about the following: Was my ad viewable? Did the user watch my entire video? Can the publisher provide me with unique first-party data to target against at scale that I can’t get elsewhere? Is this data very accurate? Does the publisher require their users to log in across multiple screens to access content? Did my inventory perform?

If the answer to all of the above is “YES,” you may be on the road to earning yourself a premium title.  

A well-known publisher may always be welcome on a traditional media plan and within the lobby of a major agency. However, the workflow of an insertion order and its transactional output will eventually succumb to automation. Rich first-party data will only increase in significance. The traditional “premium” publishers have a lot of work to do to defend their title.

As the digital media world shifts to a more intelligent and automated way of buying, and “viewability,” “data,” and “completion rates” become the new sexy, get ready to welcome some new names onto the premium playing field.

And be prepared to show them some respect. 

Let’s Be Honest: A Call to Put KPIs into Perspective

Let’s Be Honest: A Call to Put KPIs into Perspective

We’ve all been guilty of overusing industry speak—of succumbing to the digital advertising jargon or strategies that everyone is talking about at the moment. But the truth is, when we speak only in terms of things like scalability, relevancy, viewability, and CPI, we lose sight of what we’re actually trying to achieve… and what these metrics really mean.

Understanding the implications of measuring by a single metric

All too often, RFPs come our way that say something along the lines of, “Show us how you can get us 80% viewability on $50,000 on mobile and reach an eCPI below $5.” There are a lot of metrics crammed in there, but no indication of what the client is really looking for as the end goal.

Does the client realize that a CPI goal indicates that we’re guaranteeing an install that can only occur after a download, which happens after a click, which means that an impression was seen? At that point, guaranteeing viewability is superfluous, but it’s put on the plan for the sake of comfort.

As Tommy Boy said, “Here's the way I see it, Ted. Guy puts a fancy guarantee on a box 'cause he wants you to feel all warm and toasty inside.” And that’s exactly it. We’ve lost sight of the purpose of a KPI, a key performance indicator

What do you really want?

The problem with looking at any metric in isolation is that you begin to deprioritize your ultimate objective. Marketers need to define their end goal and work with media providers to determine the best stepping stones to get there. But this whole process needs to start with open communication.

Asking for and paying for viewability without identifying the final goal as being a $50 purchase puts both teams in a bind—buyers can’t optimize toward what works and planners don’t get what they’re ultimately looking for.

Sure, impressions are the top of the funnel, and increasing the number of people that see your ad will boost the chances that the next step in the path to purchase will be realized, but simply asking for a metric doesn’t get anyone where they want to be.

Metrics have a purpose, and a key performance indicator should be just that—an indicator that another action should follow. Understanding the path to purchase for every advertiser—and the logic behind that path—is vital to success on both ends. 

Breaking it down

There are so many areas of our lives where we use KPIs to help us understand progress against an ultimate goal. Think about why this article is even relevant to you and how you got where you are right now… it probably started with wanting a job. You worked on your resume and you were super proud that you sent it out to 20 companies – someone has to bite, right?

Well – think of those 20 resume submissions as impressions. You hope all 20 people read your resume, but the only way to know for sure is some sort of validation: an email or call that it was received. You’re realistic though and you understand it would be unlikely to get 20 responses, so you set a goal for yourself – you really want 3 of those 20 to get back you. You found it: your first KPI. In reaching this moment, you haven’t met your goal, but you know you’re that much closer to getting there.

Now for the big moments… call backs, interviews, coffee dates. Each item feels like a win in the moment, but the reality is that they are all subsequent stepping stones to getting you to that paycheck. You wouldn’t submit your resume to 20 companies in hopes of 3 responses without ultimately wanting a job, so why ask for 70% viewability without explaining that you’re really hoping for a 3% conversion rate on your loyalty program sign-up?

The bottom line

Mini goals are important, they break down large tasks into bite-sized chunks that feel achievable, and therefore are achievable. But metrics are only valuable if you take them at face value and understand how they contribute to your ultimate goal. You know what you’re working toward—whether it’s gaining an email sign-up, an Instagram follower who sees your posts daily, a one-time customer who makes a $20 purchase, or a loyal customer who spends $3 every couple of days at the same coffee joint. Whatever the target objective may be, the most important thing is to make sure that it is universally understood.

It’s time to be open and transparent with your agencies, tech providers, and media companies.

Explain your end goal and the path to purchase your users take. Recognize the value in each individual KPI and listen to feedback from your partnerships if they think you’re looking at the wrong KPI – you hired them for their expertise, after all. There isn’t “one metric to rule them all.” Many things contribute to success, but marketers and media teams need to be aligned on where we’re going in order to achieve it.

LIQUID IS NOW PCH/MEDIA!

LIQUID IS NOW PCH/MEDIA!

 

Publishers Clearing House has long been known as a platform offering a chance to win, but over the last few years it has also gained recognition as a key player in the digital advertising space under the name “Liquid.” Now, in an effort to more closely align PCH’s B2B offering with the rest of the company, we are excited to announce that the Liquid arm of the business is rebranding to PCH/Media.

At a time when advertising technology is becoming increasingly complex and confusing, our goal is to make our B2B brand story and products as simple and straightforward as possible. Our story starts with our audience data, and it’s undeniable that that data comes from PCH’s customer registrations, engagement, and purchase activity. Changing our name to PCH/Media communicates upfront—clearly and simply—who we are and what we do: 

We are from PCH. We offer media solutions.

Finally, you’ll notice that the style and imagery of our new brand looks quite a bit different from before. We are moving away from stock photography and instead relying on photos of diverse groups of people who represent the real experiences of life in America and with our brand. Our data comes from real Americans consumers—PCH members—and our goal is to portray the tangible, human element of this data in contrast with the anonymous, cookie-based data that is so prevalent in market today.  

We are from PCH. We offer media solutions. And our data comes from real, American people.

So what does this mean for you? A cleaner, simpler experience—with the same innovative products, reliable data, and consultative service you’ve come to expect.

Contact us to learn how PCH/Media can help you run more effective campaigns.

DATA WILDCATTING

DATA WILDCATTING

A version of this article also appeared in AdExchanger.

“Smuggle $100 million dollars across borders? A list of email addresses and a thumb drive is the easiest way…” 

The self-made entrepreneur leaned back in his chair with a smile as he said these words to me back in 2012. They were part of an early conversation during my study of the emerging trends of trading first-party data.

The market for customer data is particularly deep and growing, and it has remained my focus over the last several years — first as CEO of CommandIQ, a data platform helping large B2C companies, and now as part of Publishers Clearing House, America’s oldest and most successful direct marketing brand.

A “wildcatter” is oil-slang for someone who drills speculative oil wells, often drilled in areas not known to be oil fields. This term also applies particularly well to the current data world, where publishers have the unprecedented chance to go off the beaten path by discovering new ways to unlock tremendous value from their unexplored data. These trailblazing companies and publishers stand to rise above those who stick to the basics —i.e. the well-established (and significantly more competitive and commoditized) data markets.

Wondering where you can drill to strike it big with your data?  Here’s an overview of the top wildcatting activity happening today.

The Data Landscape

Before considering what assets you have sitting latent in your own databases and records, let’s quickly take a look at how data is being turned into value now, in 2016:

1) Mapping

If two parties collect information—say, information about their customers—there’s a simple, very valuable thing they need to be able to transact: the mapping between their users. If they can provide a link between Company A’s User 123 and Company B’s XYZ, that opens up a whole slew of new insights about that customer on both sides of the equation.

Mapping between email addresses and cookies or mobile advertising identifiers is an early sign of success in this area.

2) Ad Targeting

This one is pretty straightforward. If you know something about User 123, chances are someone else may like to know it, too. Ad targeting capabilities can range from the simple to the complex:

  • [Easy] Male? Let’s not target with a Tampax ad, shall we?
  • [Classic] Customer’s location showed them visiting a car dealer? May be in the market for a new car.
  • [Advanced] Customer has both the Netflix and Hulu apps installed. Cell carrier may want to offer him a better-priced data plan!

3) Panel Data

A complete view of a small group, or panel, of users can help show a larger trend for an overall demographic audience.

There are many different implications here: for example, Facebook acquired a VPN firm that had complete access to 5 million users’ complete mobile phone usage behavior patterns. This acquisition opened up a world of possibilities for Facebook—they can now identify and track quickly growing apps, keep an eye on Snapchat’s penetration, and possibly even verify user engagement as part of the WhatsApp acquisition diligence.

Start Drilling

To get started with your wildcatting efforts, I recommend first assessing the value of your data assets in three simple steps:

  1. Compile a list of what you can (responsibly) collect from your user base.
  2. Determine what is already being collected and is easy to access.
  3. Figure out what you can calculate—what data do you already have saved that could lead to new conclusions?

Now what?

There are a number of marketplace offerings that already aggregate and list first-party data—primarily from the data management platforms (DMPs) led by Krux, Lotame, and Oracle’s BlueKai. These all tend to focus explicitly on ad targeting as a method of value creation. Using these platforms, it’s a relatively straightforward process to publish your own first-party segments for sale in the wider marketplace (e.g. a “Video Lovers” segment made up of those who installed Netflix and Hulu apps from the example above).

Unlike oil, however, data has a unique challenge: its marginal cost to sell is zero.  So if you and I provide the same data—we can each undercharge the other to gain market share, until there’s no profit left at all.  At brief moments in history, oil had a similar dynamic—too much supply,  and too few barrels and pipelines to move it all—leaving surplus oil to go to waste, released at the well.

As more data hits the markets, the cheapest data will win—unless your data is particularly unique. Data’s hyperinflation is still new, and its effects have yet to play out in the market.

So, data wildcatters: beauty is in the eye of the beholder. Find what is novel, compelling, and rare about your data—and find the precise set of buyers for whom your data can unlock a unique edge. Or, if you have the appetite—and aren’t looking for more than purely incremental revenue—add your data to the evolving commodity markets and see what happens.

Buckle up: it’s still the Wild West of drilling for data. But it won’t always be.

Learn how to make the most out of your data—or how to use ours to boost your digital advertising returns. Contact us.

5 THINGS YOU DON’T KNOW ABOUT DATA—BUT YOU SHOULD

5 THINGS YOU DON’T KNOW ABOUT DATA—BUT YOU SHOULD

A version of this article first appeared on CMO.com.

As data and targeting have continued to steamroll their way to the top of every marketer’s priority list over the past year, there is more scrutiny than ever around the information being bought, sold, and targeted against.

This is a good sign for improving data quality in the long term, but marketers still need to err on the side of caution when buying and using data—especially if it is not their own. It is important to know the red flags to look out for so you can identify them when they inevitably appear.

With that in mind, here are five things you probably don’t know about data—but you really should:

1. The value of third-party data you’re buying is likely out of whack.

I remember testing a sample of gender data from a leading DMP to find out that it was only 33% accurate when targeting either male or female. With stories like this becoming the rule rather than the exception, marketers are getting increasingly disenfranchised by the third-party data marketplaces that have reigned supreme for so long.

Questionable collection and ownership, inaccurate information, and lack of performance once a data set is targeted have spurred the movement to walled garden environments like Facebook and Google, but something else is happening too: Publishers are offering up their own valuable CRM data as an alternative to the subpar segments available in market—not to mention the additional revenue it puts in their pockets.

Expect this trend to continue in 2016 as more pubs take control and more marketers look elsewhere for data sets.

2. The cross-device data you target against is directionally correct.

The proliferation of smartphones and cross-device interest has finally reached a tipping point. Probabilistic matching across devices is in every ad technology toolbox and, in some cases, can provide great value.

At the same time, advertisers are entrusting millions of dollars to companies that claim to know users based on information that is directionally correct. Companies that are transparent will ultimately prevail— but only if CMOs stay informed about how data sets are collected and modeled in order to make big assumptions in the most accurate manner.

3. Email is more valuable than mobile IDs or cookies.

The right email address can transform the accuracy and impact of targeting in immensely valuable ways. Environments like Google, Yahoo, Facebook, and LiveIntent all target based on email and have garnered significant praise from advertisers due to the quality of their performance.

Also consider that, as the marketplace shifts more toward mobile, the consistency of email provides a baseline for marketers to build upon. For instance, in the past nine years, I’ve had at least five new devices, each with a new device ID, but I’ve carried one, maybe two, email addresses during that time. Device turnover, especially in the US, is not slowing.

Expect the increased use of email-based advertiser CRM data to separate high-value market opportunities dramatically in the next twelve months.

4. More targeting is not always better targeting.

I recently had a client inquire about targeting against females who were ages 35-54, had made a purchase on an iOS device in the past 30 days, identified as mothers, and lived in three separate zip codes.

Remember, just because one-to-one marketing is starting to be possible, it does not mean that is where we should always hang our hat. Look-a-like models, cohort testing, and channel experience can provide marketers with more reach and is an alternative means to finding new converters rather than going really granular on a perceived behavior or demographic set. The most important thing a marketer can do is test, test, and test some more.

5. First-party data is king… but you can’t win the battle with that alone.

In a 2015 study conducted by Winterberry Group in conjunction with the IAB, 41.7% of marketers cited that more first-party data would significantly advance efforts to achieve competitive advantage through the use of data to support media. While that seems obvious, it also clearly denotes that marketers don’t feel they have enough first-party data, even if it is showing success in their current endeavors. Select third-party data providers and recent first-party data co-ops have a real place in this market to ensure the success of advertising performance.

There will never be “enough” data, so advertisers must look to model via external partners or internal investments in talent and tools to increase the scale of their valuable information living in-house.

From AOL’s investment in Taboola and Time’s acquisition of Viant to Media Math’s spinout of Helix and Kochava’s Collective—expect more advertiser and publisher first-party data initiatives, investments, and talent acquisitions to be a key theme as everyone looks to navigate a very rapidly and continuously changing digital advertising ecosystem.

Want to learn how to get the most out of data in your digital advertising efforts? Get in touch!

2016: THE YEAR OF TALENT?

2016: THE YEAR OF TALENT?

In an industry like advertising—specifically advertising technology—where the only constant is change, it’s incredibly difficult to find talent with actual experience. Even if you’ve been in digital marketing for years, it doesn’t necessarily mean that you know the ins and outs of the tech and execution strategies that are hot this quarter, or even month. One of the core challenges currently facing any company in this space is the constant struggle to find, train, and keep real talent. This phenomenon begs the question: is this The Year of Talent?

In the current climate of hyper-changing workplaces and potentially under-qualified candidates, we’re all competing for the same pool. What’s the best strategy to hiring and retaining a team in an ever-evolving, overly competitive, and fragmented market?

Here are some of the most successful recruiting tactics that have worked for me, time and again:

1. Divide your recruiting plan into two parts: seasoned experts and personality rock stars.

  • Seasoned experts: Look for someone with 3+ years in the industry, who understands the concepts and inner workings of combining tech and creative advertising. Three years might not seem like much—but it’s enough in this space to differentiate for this type of role. Don’t anticipate these candidates coming on board with 100% one-to-one knowledge of your business, but do expect them to get up to speed quickly and become leaders within your group as they help to develop new ideas and concepts off of their baseline knowledge.
  • Personality rock stars: Look for go-getters. These are people with personalities that are passionate, interested, curious, organized, excitable, and personable. They will come on board totally green to our industry lingo and concepts, but they’ll work their tails off to learn quickly and bring outside perspective to your team. They’re also typically competitive and are going to give 200% until they feel like they are on a knowledge par with your seasoned experts—and then they’ll keep giving 200% until they get your job.

2. Invest in training.

For this, I don’t mean a four-week classroom program with a test at the end. You need to have a multifaceted approach that teaches hard and soft skills.

  • Assign a buddy. Have new hires shadow another team member on and off during their first few weeks on the job, listening on calls and in meetings. The only way to really learn in this space is to listen and experience.
  • Let them own something right off the bat. They will likely mess up in some way, but they will learn much more quickly than if you hand hold them for too long.
  • Give them training materials for hard skills. Teach them how to calculate impressions off of CPM and revenue—without an internet-sourced impression calculator. If they’re one of your “personality rockstars,” have them do a Google certification or something similar, even if it isn’t exactly what they’ll be doing day-to-day—the baseline knowledge and concepts will be invaluable as they get up to speed.
  • Get them in-market. Talking to other industry folks is the fastest way to have them hit that “aha!” moment where they actually understand what’s going on around them. Bring them along for a vendor meeting or to a low-cost show where they can start to network, but be prepared to help them out with some contacts and meetings.

3. Recognize their value.

You spent valuable resources looking for these people and training them—you need to respect, develop, and appreciate them to keep them around. This market is fickle and it’s easy to lose all that investment to the guy next door who offers a pay bump and a “Senior” at the beginning of their title.

  • Create a growth path. Take the time to sit down with your team members on at least a quarterly basis to set their long-term goals—and create a plan to help them get there. Because there isn’t a one-size-fits-all package for keeping everyone engaged at work, you need to approach each individual’s growth plan differently, based on their unique goals and motivators.
  • Build a culture of accountability. Make sure that everyone knows what they are on the hook for and hold them accountable for it—they will feel motivated to succeed and rewarded when they nail it.
  • Know the difference between office face time and work. Flexibility in work hours and location is table stakes at this point. You need to be willing to be flexible on in-office hours in order to keep top performers, but this only works if you successfully create a culture of accountability first. Your willingness to be flexible also demonstrates trust—an intangible yet invaluable attribute for any team and organization.

4. Stay relevant.

This market is ever-changing, right? Make sure your strategy keeps up.

  • Build short and long term strategies.We all have to keep the lights on, so it’s important to divide focus between short-term gains that maintain cash flow and long-term strategies that require investment now for large future opportunities. Be clear about who is focusing on each area and how they interrelate. Review these strategies regularly to make sure you’re on the right track.
  • Be transparent with the company on what those strategies are. Having a plan doesn’t help in this case unless everyone knows what your plan is. Make sure you clearly communicate the overarching direction and goals to the entire organization—and keep them updated as those plans change (because they will).

Quality & Scale Earn Us a Top Spot in Appsflyer Index

Quality & Scale Earn Us a Top Spot in Appsflyer Index

AppsFlyer just released its most recent Performance Index, offering insights into the performance of mobile media sources for H1 (January to June) 2016. Ranking over 1,000 sources by region and platform, the Index is a highly regarded resource for data-driven marketers looking for the smartest ways to allocate their ad spend.

With a focus on driving quality installs at scale, Liquid (now PCH/Media) is proud to have earned top spots in AppsFlyer’s gaming and non-gaming Power Rankings for North America.

Using retention and scale to determine its rankings, this edition of the index highlights the industry’s shift from acquisition to engagement—and also explains the significant number of newcomers to the list. As market dynamics change, so does the efficacy of media sources. AppsFlyer’s report points out that marketers need to be ever-vigilant about monitoring performance of existing partners and remain open to testing new ones to ensure the best results.

Here’s a quick look at how Liquid stacks up:

  • Gaming in North America: Android: Top 15 / iOS: Top 25
  • Non-Gaming in North America: Android: Top 15 / iOS: Top 20

See the full report here.

Want to learn how to access Liquid’s exclusive inventory of loyal and engaged users? Get in touch!

The Sales Funnel is Dead

The Sales Funnel is Dead

A version of this article first appeared in Ad Age.

A few weeks ago, I was at work when I remembered that my coffeemaker had been making weird noises and doing a less than stellar job of producing a perfect cup. While I was thinking about it, I took a break from checking email to run a quick search on my laptop for “best coffee makers.” I read a couple reviews and browsed a few models before determining that, really, I needed to see them in person to decide which option was best.

On my commute that evening, I was greeted by an ad showcasing a variety of shiny chrome models similar to the ones I had been browsing earlier. By the time I got home, I had vowed to head to the store that weekend to check out my options in person. Ironically, once there, I spent half the time on my phone comparing prices and searching for coupons. While I stood there in the aisle, I decided to order my coffeemaker from a different (less expensive) store when I got home—from the comfort of my couch, on my laptop.

Almost exactly where I had started this whole process.

What Funnel?

You probably recognize this chain of events. My search for a new coffeemaker brought me from laptop, to phone, to store, to phone, and back to laptop before I finally pushed the “Buy” button.

People say the sales funnel is changing—that, in today’s digital world, the way customers buy is no longer a simple path from awareness to prospect to sale.

That’s just not true. The sales funnel isn’t changing – it’s completely and utterly dead. It’s been brutally turned upside down, inside out, with little left to identify it as the clean, straightforward process it once represented.

Today’s shopper jumps in and out of channels, views alternatives to purchases, and searches for better deals—all at the tap of a screen, the click of a button, and oftentimes while standing right in front of the item she’s trying to buy. She doesn’t predictably slide through the funnel, ushered along by our linear marketing messages. Instead, she more closely resembles a ball in a pinball machine, firing off a bunch of different pegs on the way down, sometimes shooting back up to the top of the ramp before ultimately finding her way to a purchase. She continues to move toward a sale, but it’s hard to predict where the bouncing will take her.

If it was difficult to influence a shopper’s buying decision before, today’s landscape makes it nearly impossible.

Making Sense of the Madness

More options around when, where, and how to buy have not only given consumers incredible control—they have also made competition among retailers increasingly brutal. In order to compete in the fragmented ecosystem, marketers need to understand the modified path to purchase and reframe their strategy to make their dollars work harder and smarter.

The first step is to begin thinking in terms of people, rather than platforms. Marketers need to be ready with a holistic message that can be seen by consumers wherever they are, at any given time, agnostic to the platform or device they’re currently using. Centralized marketing teams need to be able to look at campaigns across all touch points, identifying how each peg in the pinball machine contributed (or not) to the sale at the end.

Sound easier said than done? That’s where data comes in.

How Data Holds it All Together

Data is the master campaign unifier, and it’s the best way to maximize marketing spend in the current funnel-less phenomenon. But you can’t just use any data—it needs to be intent-based, and it needs to be good.

Right now, almost everyone is buying data from the exact same places and using it in very similar ways, resulting in oversaturation of ads for the online consumer, with increasingly disparate results. Most of this data comes from third-party companies who track consumers as cookies across an aggregate of websites. For a number of reasons, this type of third-party data is less reliable and less effective than its counterpart, first-party data.

First-party data, collected by a company directly from its own customers, not only provides more accurate ad targeting—it also offers fresh new insights not available from the overused alternatives on the market. First-party data that also gives marketers inside information into what consumers want—what their intentions are, what their future actions will likely be—is the secret to creating unified campaigns that reach shoppers with the right message, at each and every touch point on their pinball path to purchase.

We may have lost the predictability of the sales funnel, but what we’ve gained is much more valuable—more opportunities to connect with future customers than ever before.

Let’s make the most of them.

Spotlight on: Aaron Olmstead, Head of Engineering

Spotlight on: Aaron Olmstead, Head of Engineering

This article first appeared on CTO Corner, a series of interviews with heads of engineering written by Leo Meira, a software engineer at Jebbit.

Leo spoke with Aaron Olmstead, the head of engineering and product at Liquid (now PCH/Media). They discussed the difference between engineering at a large company and a startup, what makes an ad tech leader, and when to build things in-house versus outsourcing.

How did you get into engineering?

I did a couple programming workshops when I was a kid. Those were pretty neat and I got the bug to want my own computer. I got a Commodore 64 when I was a eight or nine, and when I got to high school I took some computer science courses. Then majored in that in college, and here I am.

In the past eight years, I’ve been in ad tech, mostly at startups. Publishers Clearing House (PCH) is a slightly different situation, where I work for Liquid, which is the digital advertising part of PCH. It’s a great opportunity to have a startup culture within the stability a bigger organization gives you.

I’ve been at a bunch of startups and a few larger companies. It’s been useful to see both sides of that. They have very different ways of operating. It’s good to be able to adapt to that change.

Is being head of engineering more difficult at a startup or at a large company?

After Fiksu, I had my own startup that I tried to get off the ground for a couple years. That was a tremendous learning experience, to get exposed to the other parts of business that you don’t get as a engineer. I learned how to write contracts, what an LLC means in the state of Massachusetts, and how to do sales (though not very well!). That’s something I don’t get as much at a company like PCH, where I work more with my team and HR and develop growth plans. But, it’s not like you’re learning more at one than another; you’re just learning different things.

What are the overall challenges of being a department head at a tech company?

There’s stuff that transcends the size of the company. Once you’re more than three or four people, you see tough things like getting the business side to engage with the technology and getting the business aligned with upfront engineering costs. Unless you’re working for someone straight out of engineering, you run into issues like once a platform is built, they think you’re done. But really, once you build a piece of software, you’re married to it.

Then there’s stuff unique to ad tech in particular. This transcends big companies and small companies. This industry is dominated by Google and Apple and Facebook — any one of them can make a decision that completely changes the competitive landscape overnight. As a CTO, you’re always balancing between building out particular business relationships and the technology stack, versus diversifying, to prepare you for these changes.

What would you say are major changes you made to positively impact Liquid?

I’m cynical and experienced enough that I am less excited about writing code for the sake of just writing code. I try to get us to think more deliberately about things like when is it time to build a solution versus buy it off the shelf. When I came on, we were about to build a giant software stack that did all the same stuff as all the other ad stacks I’ve worked on. So I said, what do we do at PCH that’s unique to us? Is this huge initiative worth it, that’s going to eat up a bunch of resources to not build anything truly unique? Or do we want to build something out based on our unique longstanding data capabilities, granting sweepstakes rewards, and things like that that only PCH can offer? We built services to handle the unique PCH business rules, and integrated those with commodity, ad serving and mediation platforms, which means we built out a lot less software, but it’s far more robust and scalable than what we had before, and has far more unique offerings than things we could have gotten just off the shelf.

Was it hard for your team to make the change of stepping back and realizing things didn’t need to be built in-house?

There was friction, but I think it helps to be able to paint decisions like this in a revenue and cost basis. So, you’re saying, “Here’s what it takes the engineering team to maintain this stack we’ve built, here’s what we’d need to hire to build this other thing, and here’s the opportunity cost of it all.” You go around and gather support one person at a time and try to paint the picture that it’s better for the overall business.

As you build new products and features, how do you get feedback from account management, sales, marketing, and other teams back to the engineering department?

That’s a really good question. It can be hard to get engineers to give a damn about anything that’s not code. One thing you can do is to make sure that engineers actually see the results of the changes that they make. Data about campaign performance, revenue, impression volumes, margins and all that stuff. Engineers tend to like games, so when you give them a tight feedback loop with the visualization of this information, and the changes they make to their systems, and how those impact monetization, it becomes a game. You engage the engineers that way, and they tend to like seeing it and pay attention.

One of the other things, just to be clear, is that I don’t think it’s possible to get all the knowledge from Ad Ops teams, from sales, and from marketing to the engineering team. I think sometimes there can be a chip on the shoulder of engineers, in that they think they can know everything, but there’s so much knowledge in the heads of ad ops people and sales people that you could never fit all that, plus all the systems knowledge they already have, in the engineers’ brains! We should work with ad ops and understand that it’s really hard. We’re setting up an ad ops boot camp for new ad ops hires but also for engineers and product so they can sit in the ad ops chair and learn about how people use the tools that my teams build. It’s easy for us to think that we’re the only ones at the company with hard jobs because we have to get up in the middle of the night to fix servers that are melting down, but getting your hands dirty and operating an ad campaign can help. It shows that different teams are all really smart.

To make that communication happen effectively and reliably, everyone needs to have the respect of their peers. You can’t have engineers saying we’re the smartest people and ad ops saying engineers never build the tools we want — that can spiral. That’s why I make sure our teams are all talking to one another.

What would you say makes an innovative leader in mar tech and ad tech?

What I’ve come to learn over my time doing this is that a lot of this is about, as simple as it sounds, paying attention to the market. It’s about using data that’s relevant to your business, tracking it obsessively, and using those data to adjust what you’re doing. A lot of people come in having an ideological agenda and use that to drive decisions in the face of all the evidence, trying to predict where the market will be in three years. Instead, you need to experiment, iterate, and correct your strategies. You’ve got to figure out not just where the opportunities are, but also: what are the kinds of business problems that automation is really effective at solving? What can we build that makes people able to get their work done faster?

We’re coming out of a long period of ad tech where people assumed that hiring lots of CS PhDs and building out these big machine learning systems was going to be the answer to everyone’s problems. Now we see some of those companies crashing because they invested more in the notion of building really exciting software than in offering a useful service to customers that offers good value. There’s a growing understanding that machine learning on its own is not a panacea, especially in a space that changes as quickly as this one. The kinds of things humans are good at—using intuition, and using knowledge aggregated from a ton of different domains to make quick changes without a lot of data—are complementary to a lot of what software can do, but not necessarily the kinds of skills that AI can come close to replacing.

Do you think the rapid increase of new companies is healthy for the ad tech space?

I think competition is always healthy for the space. One thing we’re seeing in ad tech in particular is that venture money has become more reluctant to invest heavily in ad tech because it’s become overcapitalized. You’re seeing some bigger and more longstanding companies refocus from rapid growth to sustained profitability, and some people from those companies go out and do their own thing. The more competition you see, the more innovation you’re going to see, because there are zillions of different ways to solve the challenges in the space, and everyone comes at it with different backgrounds and skillsets. Someone with a background building DSPs is going to approach a problem very differently than someone with a background in choosing ad networks to integrate, versus someone with a background in running campaigns.

Do you have any advice for founders?

That’s the thing that’s hardest about starting a tech company—you need to very quickly figure out all of those things. You need a crash course in different business models, different kinds of contracts, figuring out how to sell if you haven’t before, how to negotiate, and you have to recognize when you know enough about running ad campaigns and when you don’t, and then you need to find people who complement that. You have to get people with really specific skills.

I highly recommend that anybody interested in the business aspect of whatever tech space they’re in try to start their own company at some point. Mine wasn’t successful, but what I learned was invaluable.

Where do you think tech is heading?

That’s kind of the zillion dollar question, right? One of the things I’ve learned in my career is that no one knows. We’re getting better about figuring out the spaces where automation, crowdsourcing, and AI are good at solving problems.

I would have been flabbergasted if five years ago someone had said, we’re going to see proliferation of self-driving cars on the roads way before AI is good at targeting ads. But that’s where I think we are now. Tech innovation can be very hard to predict.

So you see things like the spread of facial recognition in social media, and the potential for leaking PII in ad targeting and big data systems, where people can end up using those tools and techniques to do things that, depending on your point of view, might not make the world a better place. We as technologists have a ton of responsibilities that we tend to wash our hands of, saying, it’s not my decision, I just make my code and don’t tell people what to do with it. But without us, some of these issues couldn’t happen. I’d like to see us try harder to avoid hubris, to be aware of what people could potentially do with our tools, and to ask questions like “can I build my ad targeting system in a way that it’s just not possible to leak PII?” Rather than assuming that if some bad actor uses our tools to do sketchy stuff it’s not our problem, can we bake things into the tech itself to ensure it can only be used on the up-and-up? (PCH does some of this with our audience systems, by the way, which I’m really proud of.) It may be a stretch to think about Asimov’s Three Laws of Robotics in the context of ad targeting, but I think we as engineers can do more than we do, and I’d like to see us, as a profession, think about how our tools might get used a lot more than we do.

If You Build It, They Will Come: A Call for Header Bidding in Video

If You Build It, They Will Come: A Call for Header Bidding in Video

Waterfalls rule. They’re beautiful in nature—so they must be beautiful in ad tech, right? I mean, think about it: you get to put your best supply side platforms (SSPs) and deals on top and let the other partners get the backfill scraps that trickle down to them. Plus, you can use pass-back tags so that each partner passes the impression back to you if they can’t fill it, and then you can offer it to the next partner. This even allows for double ad serving fees too. What’s not to love?!

Just kidding. Death to the waterfall, I declare! At this point, we’ve all heard that sentiment being shouted from the mountaintops, with overtones of Header bidding, header bidding, header bidding. #headerbidding

We get it—header bidding is a big deal and worth your time. What the industry hasn’t discussed much is header bidding in video—and that, my friends, is where we all stand to gain the most by killing the waterfall.

The Inner Workings of the Waterfall in Video

Before I dive in here, let’s first level-set and try to define the waterfall in video. If you’re like me, when it comes to working with SSPs and DSPs (demand side platforms), you always want to have your cake and eat it too. By that, I mean you work with everyone—you look to capture their “unique demand” and let each SSP fight for their right to be your top SSP. The cream (revenue) should rise to the top, right?

Most SSPs will argue that this approach is wrong and that you need to have all of your inventory in one place so that buyers know where to look. While I can see why this was, at one point, a valid argument, I don’t believe it stands anymore. Each SSP is not created equal, and private marketplace (PMP) deals are ultimately reshaping the programmatic environment.

So, ultimately, you’re going to have to mediate all of these SSPs in some way or another. If you’re like most publishers, you’ll probably mediate them through your ad server. You’ll plug each SSP into your ad server and revenue will come in on Day 1. On Day 2, you’ll allocate traffic to the highest SSPs, based on their Day 1 performance: 25% to one, 30% to another, and so on. (I think it’s safe to say that DFP (DoubleClick for Publishers) is the most popular ad server in the market, so let’s just assume that most publishers are using DFP, i.e. Google).

Now, there’s also the possibility of mediating an SSP with another SSP. (“You can’t triple stamp a double stamp!” Dumb and Dumber, anyone?) Surprisingly, many SSPs will act as your mediation partner and run tags from another SSP—all the while, both SSPs are taking their margins. It’s “coopertition,” and any SSP—especially in video—that says they don’t work with their competitors is lying to you. They all backfill each other in some way or another.

Some SSPs will refuse to play nice in this mediation sandbox, just as some SSPs refuse to go in through another SSP’s header wrapper. This is where publishers like us need to stand strong and force them to play nice or not play at all. Because, let’s be honest: if your wrapper is truly just wrapping other header tags, it shouldn’t give preferential treatment to any of the tags, including your own. The highest bidder should always win—assuming they didn’t time out, obviously.

But I digress.

If all SSPs and DSPs were equal, the waterfall probably would make sense. However, all SSPs and DSPs are not equal. As ad tech continues to change, so too does the role of the SSP.

Luckily for publishers, header bidding has leveled the playing field in a lot of ways. If your SSP is telling you there’s no need for header bidding, it’s a clear sign that they’re scared of losing your inventory to other SSPs. My first question when talking to an SSP about their header tag is, “Why is your demand different?” Each SSP is battling to put a stake in the ground as to how and why they’re different from their competitors.

The Time for Header Bidding in Video is Now  

We’re all feeling it. We’re in the doldrums of July’s ad revenue lull. Southern Cali’s June gloom has given way to ad tech’s “July Dry.”

What shall we do to keep ourselves occupied? Plan for Q4, maybe?

If you’re like us, you’ve seen an explosion in PMP sales in 2016, with a large portion of that revenue coming specifically from video. Aye, but therein lies the rub—can PMP growth really explode in video without a video header tag?

Sure, you could just allocate all of your impressions to one SSP so that the PMP deal you just set up with them gets a fighting chance at all your traffic. Put them below the first spot in the waterfall and run the risk of another SSP buying that PMP impression before it even gets to the SSP that needs it—or the one that’s willing to buy it at the highest price.

That’s all fine and dandy, but, as we’ve all discovered, not every agency and DSP wants to work with every SSP. Therefore, you must diversify. We already established that most publishers are mediating SSPs through DFP, so you’re not going to get top dollar for your inventory without every SSP giving you a header tag.

And this, my friends, is the reason for my plea to SSPs to start making header tags for video. As a publisher, if you made money killing the waterfall (i.e. implementing header bidding) in desktop, you’re primed to absolutely crush it when it comes to video.

In the past, video was the last piece of inventory publishers ever thought of sending to the open auction. The “Race to the Bottom” (RTB) mentality kept video inventory close to publishers’ chests, as they always direct-sold it.

Flash forward to the Age of Programmatic. Now, agencies are demanding that you set up PMP deals in order to capture their ad dollars, and they require that it run on their DSP and SSP of choice. As more ad revenue begins to flow into PMP and “always on” deals, the programmatic pipes that were once used strictly for backfill now stand to be the crème de la crème of ad dollars.

The View From the Other Side

“Okay, but what about the advertisers?” you say. Let’s look at this from the DSP side: with header bidding, the world becomes your oyster. You can more accurately forecast inventory, because you see every impression a publisher has to offer. With the waterfall, this type of forecasting was never possible. When the waterfall dies and header bidding takes over, DSPs will have the ability to pay top dollar to win inventory that, before, they might not have even been able to see.

What about the technology behind it all? What needs to be different for header bidding in video to take off? If there’s one thing we’ve learned from VAST and VPAID thus far, it’s that both allow for client-side auctions to happen—which takes us all the way back to our earlier discussion about SSPs arbitraging through other SSPs or backfilling with another SSP partner.

In order for header bidding in video to work, this practice needs to stop. Otherwise, an SSP will win the auction via the header and then auction this unit on their side amongst other SSPs. This means that, even though the header SSP won the opportunity to deliver an ad, they won’t ever serve one, and that ad opportunity will perish—also known as The Timeout. Hence why, with header tags, we will most likely require SSPs to respond with their own demand—otherwise, we’ll run the risk of the same timeouts we currently see in the waterfall.

The Bottom Line

This is my call to arms to all video SSPs in the market: Rise up, create header tags, and let your publishers reap the benefits of a more unified auction.

The time is now, partners. Don’t delay. If you sit back and wait for Q4, you run the risk of being left behind as other video SSPs look at every video impression a publisher has to offer. Watch as their PMP deals skyrocket.

If you build it, they will come. “They” being me. While you’re at it, please integrate your header tag through any and everyone’s wrapper. If you’re good, your demand will work through any wrapper tag.

PCH at Cannes Lions 2016

PCH at Cannes Lions 2016

Last week, Publishers Clearing House shipped off to Cannes Lions, the International Festival of Creativity that attracts more than 15,000 people each summer. While we’ve had our team in attendance over the last couple years and even co-hosted a yacht last year, this was the first time PCH sponsored its very own boat—we were sure to make a splash with a bunch of high-energy events throughout the week.

Here’s a peek at what went down!

Our Home Away from Home

Our boat, the Lady Jersey, was a 36 meter classic yacht. This is where all the fun happened!

La Tonnelle Wine Lunch

On Monday, we hosted an executive lunch at La Tonnelle on Saint Honorat Island for an exclusive group of partners and clients. Home to the Lérins Abbey monks and their eight-acre vineyard, the island produces some of the best wine in the world—which we all got to enjoy, along with the beautiful views!

Yoga on the Yacht

Tuesday through Thursday we hosted early morning yoga on the top deck of our boat. What an amazing way to wake up—and sweat out whatever happened the night before!

Rosé Soirée

Tuesday night was PCH’s Rosé Soirée party, where we served—you guessed it—lots of rosé as well as great tunes from one of the best DJs around. And, of course, some big PCH checks made an appearance!

Waterside Chats

Wednesday afternoon kicked off with our Waterside Chats panel event. Attendees enjoyed cocktails and sunshine on our top deck while agency and ad tech influencers from WPP, Rubicon, AOL, LiveIntent, and more discussed the latest in mobile, data, and programmatic media.

Teads Run DMC Party

On Wednesday night, we were excited to partner up with Teads to co-host a party featuring a performance by Run DMC! What a great way to cap off an amazing week.

The PCH Team

And last but not least, here’s the PCH crew that made it all happen. Looking forward to another awesome event next summer!

The Future of Data: Beyond the DMP

The Future of Data: Beyond the DMP

A version of this post also appeared in AdExchanger

We are currently in a state of “data-hyperinflation.” In other words, the rate of data being generated and used is exploding year over year. This phenomenon goes beyond segments and cookies, and new classes of vendors are popping up to fill the space.

Future iterations of data management systems will take savvy marketers one step closer to understanding every touch point that leads to a valuable new customer. Here are several important data worlds that are emerging—and evolving—fast to get us there:

Location

Location itself is pretty straightforward: now that everything is mobile, we can gather GPS-level data from a device, represented by latitude and longitude coordinates (lat/long) to determine where a user is located. But lat/long data is a lot more raw than a typical “segment,” in that it requires additional steps to provide true insight. Using lat/long, you have to extrapolate 1) what that place is, and then 2) what that location means about the user.

Simply knowing a person’s lat/long doesn’t tell you much about them, other than maybe they are located in downtown San Francisco, for example. If you parse the data log, however, you might be able to see that this person is in a gym—and they stood in another fitness location just last week.

Suddenly, two data points derived from the geo framework tell you that this user is actually an active, fitness conscious person. Applying this insight is the next step.

People You Haven’t Met Yet

The traditional view of a DMP was to store information about your existing customers, readers, etc. in lieu of managing a database. But what about storing information about people you buy ads against? If you buy dozens of ads against a particular cookie—and they never click—maybe they just aren’t worth your time anymore. If someone has already been to your webpage, maybe they should get a new message—an invitation to come back.

Stay tuned for the “Pre-Customer Database”: a central place to store all of the information you are generating, before someone becomes an actual customer with a direct relationship. For CPG companies, this relationship may never turn into a digital one, so data vendors in this space could hold some of those brands’ most important online information—a treasure chest of potential hot leads.

Data Relating to Direct Media Management

How can you remove a non-clicker from campaigns unless you tie your media performance directly into the buying process? Another set of data folks will do just this. This group will drill down on the user level to start answering a lot of important questions about marketing spend and resulting revenue: How much are customers costing me by source? What’s each customer’s lifetime value per channel? What’s the downstream conversion rate for each creative that I run?

Other simple optimizations aren’t far behind. Imagine being able to automatically retarget people who clicked one of your ads in the first place?

When you have assembled all the data across media spend channels, the evergreen question is: what should we look at internally—and how do we make sense of it all? Some of the vendors in this space will offer basic reporting functionality to break down these insights, while others may aggregate data and leave charting and analysis to another integration.

Data Relating to Cross-Vendor Information

So, now that we’ve built out the core questions above, new concerns start to arrive. For instance, how many impressions are people seeing across my different media partners?

One such data vendor did a study for a customer who was seeking to run their media with an impression cap of 2x views per user. To their dismay, they discovered that when they looked across the six different media buying platforms, each user was seeing the same ad six times. Each vendor had stayed at the cap of two impressions, but there was no communication or coordination between them.

A next-gen DMP or DMP alternative will be the one to answer these kinds of questions.

Data Relating to Cross-Device Understanding

All of the above questions run into a further stumbling point: mobile. We’ve done all of this hard work to gather and dissect important data—but now each user has three different browsers (home, work, mobile) and possibly even more devices at large.

Facebook has the luxury of single sign-on data: many people log into the Facebook platform on each of their devices, giving the social giant a complete view into which browsers, devices, and cookies are connected to one person. But what about the rest of us?

A myriad of device-graph / cross-device DMPs have sprung up, either storing this information on behalf of publishers or building their own probabilistic mappings. Independent firms are already getting consolidated into larger marketing platforms, and this will only become more prevalent moving forward.

Case Study: National Toy Retailer

Case Study: National Toy Retailer

The Challenge

A national toy retailer wanted to drive awareness of online products to a core audience of Moms with children between the ages of 0 and 7, within specific geographic locations.

The Strategy

Liquid (now PCH/Media) used PCH’s first-party demographic and behavioral data to implement a strategically targeted campaign across devices and channels.

The Tactics

First, Liquid employed a demographic segment of “Moms with young children,” which included female PCH customers with kids between the ages of 0 to 7 in the household. To further expand the campaign’s reach, Liquid created a custom segment of people who had purchased young children’s products from PCH, helping the retailer reach shoppers who have a high propensity to buy these items again in the future. Liquid also layered on proprietary location data to ensure that the ads displayed toys actually available in each shopper’s local stores.

To amplify the efficacy of the campaign, Liquid contextually targeted these audiences on websites and apps relevant to Moms and Parenting. It also applied daypart targeting to reach them on nights and weekends when they were most likely to engage.

Liquid fully managed the campaign optimization, applying white and black lists of sites and apps at an extremely granular level. Spend was optimized toward the platforms driving the highest engagement rates.

The Results

  • Nearly 2X increase in engagement rate

  • Exceeded impressions goal by over 16%

  • 0.95% CTR – Nearly double that of other publishers

Sources: Retailer’s third-party tracking partner; PCH analytics
 

Learn how we can help you reach your ideal audience. Get in touch!

Why Marketers Should Learn to Love the Login

Why Marketers Should Learn to Love the Login

A revised version of this post appeared on MediaPost last month.

“Another password for yet another site!?” we lament as consumers.

While login details may eat up precious brain capacity (there’s an app for that!), there’s a reason that more and more brands are keeping their products and services behind locked doors. Leveraging single sign-on—that is, a single user log-in that works across desktop, mobile, and tablet—empowers marketers to build a more compelling, more differentiated offering, ultimately improving, not hindering, the customer experience.

Implementing this type of technology, however, doesn’t come without its complications. Let’s take a look at a few of the core challenges ahead for marketers looking to dive into the world of single sign-on… and the opportunities that success will bring.

Challenge #1: Getting customers on board

In order to get a customer—or, more difficult yet, a prospect—to share their information and take extra time to engage with your brand, there’s an element at the heart of this interaction: the customer value exchangeCustomers need to understand what they will get out of opening their time—and personal details—to you.

Let’s take a look at how a few of the most successful companies have used single sign-on to earn their customers’ trust and loyalty:

Groupon, one of the pioneers in the daily deals site phenomenon, attracts people to register by hinting at special offers and a tempting cash incentive. Offers are tailored to registered customers—a must for modern consumers who increasingly demand personalized experiences.

Starbucks has managed to build one of the most widely-adopted mobile payments applications—one that Paypal, Visa, and other payment companies have even tried to replicate.

How? By providing value to the customer:

  • No wallet necessary: easy way to hold your Starbucks gift card
  • Replenish funds: easier way to fill your gift card with ApplePay
  • Order ahead: easiest way to get your daily fix

In addition to the convenience, the ultimate driver of the Starbucks app’s widespread adoption is the loyalty program. Buy 11 drinks and get your 12th free: only available if you engage with the brand and use the application.

eBay offers new would-be buyers more subtle, but still compelling functionality: allowing you to follow auctions that matter to you. You will, of course, have to sign in or create an account for that privilege.

ESPN has figured out how to learn your favorite teams. They offer push notification alerts to keep up with what’s happening in real time… only available upon log-in.

Challenge #2: Implementing single sign-on technology

You’ve built a value proposition for the customer—they’ve created a single sign-on, granted you access to their data. Now what?

Enter the technology challenges.

It’s easy enough to have a customer record of what a logged-in user has done across multiple platforms—e.g., who has made a purchase from both desktop and mobile. But that’s just the start.

Here are a few single sign-on technology roadblocks and the best ways to tackle them:

Joining anonymous and post-login data

The best way to understand the entire path to purchase and customer lifecycle is to have a complete view. But this is only possible if the technical systems are in place to unite all of the online behavior of a customer, prior to them creating an account.

Example: you might have a customer on the web, who always logs in. They eventually download your app as well—but then they don’t log in for months, until they make their first mobile purchase. Since they were not logged in while they shopped, you’ll lose all the vital information that led them to the purchase unless you set out to collect it and tie it back to that customer’s account.

Using data for a differentiated experience

Collecting and understanding data is just the first step. Building the systems to use and deploy this data to delight the customer is where the magic starts to happen.

The personalized shopping app, Wish, which has raised more than $500M in venture capital so far, changes nearly everything about the customer’s shopping experience. It provides tailored emails and offers temporary, personalized sales on products you might like. But far simpler and more attainable is its ability to analyze the products you look at and adjust the app’s navigation categories accordingly.

While there are many uses of personalization, sometimes just the basics can make a huge impact.

Connecting data within all of your company’s systems

Lastly, tying together all the disparate systems within your organization can reap some of the benefits of single sign-on. Have a user who stopped viewing emails? Add them to an at-risk segment. Maybe offer that customer a win-back campaign the next time they open your application.

Perhaps most importantly of all, connecting data across systems will give you, the marketer, a holistic view into which of your efforts are bringing new, profitable customers—and which tactics need to be cut from your plan.

Going Mobile is No Longer Enough: Consumers Demand Relevance

Going Mobile is No Longer Enough: Consumers Demand Relevance

A version of this article first appeared in Mobile Marketer.

We cannot deny that the smartphone is an extension of ourselves, a staple in our daily lives. We spend more time with our phones than any other piece of technology. And yet, less than a decade ago, many doubted that mobile advertising should be a key area of investment (and ad tech players are still playing catch up because of this belief). Most people certainly never believed that the smartphone would be a mechanism to drive purchases or, at the very least, feature ads that could influence purchases at a later date.

More Mobile Choice Means More Competition

But 2016 is here, and the current generation will only continue to demand more out of mobile. They will provide information in exchange for a free market to view pictures, videos, and relationship statuses. They will make purchases, even big ones, on their mobile devices and will choose to share their most intimate moments on their smartphones versus their laptops.

They will bounce from game to news to gossip column to WebMD as fast as you can say Snapchat. They need not be loyal to any one publisher, because their mobile search results produce a wide variety of options to answer their questions.

As this generation has been given the luxury of choice, it is more important than ever for an ad to be relevant, especially on the platform where these users are most engaged. With so much data now available to marketers, it is crucial that they understand the different types of data to create the best and most relevant user experience. Otherwise, these consumers will choose to go elsewhere.

If a marketer understands the buying behavior of a particular user, this not only leads to a more positive user experience—it ultimately may lead to a purchase. Can intent data signaling a potential decision to purchase be an important component of mobile advertising?

How Intent Data Works

Let’s use a real life example.

It’s Thursday night at 7:30pm. I have the TV on and I’m scrolling through a premium news app. Mobile advertising’s initial charm was that the experience was uncluttered—“one ad per page.” This is no longer the case. We’ve seen so many recent examples of publishers that have disregarded the user experience in favor of creating a desktop-like experience masqueraded as a mobile one. This was my experience tonight: political ad, three ads in a row for a fancy keychain, and an “adhesion” unit asking me to download Hotels.com NOW.

But wait…a 300×250 emerges featuring dancing bubbles and a beautiful bouncing baby boy with a prominent Johnson & Johnson logo…

Do Johnson & Johnson know that I have a nine-month old? Do they know how much easier my life has been since introducing a bath with bubbles? Do they know that I searched for “safe baby bath products” several times in the past month? Do they know that I used the last of my Babyganics bottle and just texted myself “buy bubble bath” because my phone was closer to me than a pad of paper? Do they know how much bubble bath I’ve purchased in the last month?

I don’t know the answers to all of these questions. I do know that my behavior on my mobile device may have offered certain “clues” or signals that I am indeed a mother who believes very much in the soothing nature of a baby bubble bath before bedtime. I am not certain if the brand chose to read these signals or if this was a coincidence that ultimately may lead to a purchase.

Let’s Start Here

There is a great deal of data available to marketers today. Some data is more valuable than others. Accurate demographic data, for instance, will soon be table stakes as purchase and intent-based data becomes even more valuable. If I know someone has bought products in my particular category, can I get them to buy more of my products? And, can I use this data to reach users on the platform where they are spending so much of their time?

The answer is yes. Marketers should align themselves with partners that have access to the right type of data to ensure that their ads are relevant, turning over more of their dollars to people-based advertising versus contextual spend and spray and pray type models. This may sound like an obvious statement, but there are still hurdles to understanding customers’ behaviors, especially purchase behaviors, as users jump from device to device.

So while marketers can’t control the aesthetics of a publisher’s page and the number of ads being shown, they can control the type of people they reach based on their past purchase decisions and potential to buy even more of those types of products.

Mobile advertising is still not perfect, but, at the very least, let’s be relevant.

5 Secrets to Maximizing Retail Sales

5 Secrets to Maximizing Retail Sales

With all of the world’s bounty just a few clicks or taps away, the competition for customers is growing fiercer by the day. Figuring out the best way to cut through the noise is a challenge—particularly for the savvy marketer or retailer who is trying to grow and adapt their business, while riding the waves of technical innovation.

For 2016, adopting a more data-centric approach will be the key to successful marketing. The more a brand can use high-quality data to personalize its messaging to consumers, the better its chances of garnering a response and closing a sale. Here are five tips to help you get started:

1. You don’t need much data to start targeting

The results are clear: companies with the best data have a dramatic advantage. However, you don’t need much to start seeing immediate results. Start with these two simple steps to get your data-driven programs going:

  • Do you see higher checkout rates or a higher basket size from female consumers? Split your advertising in two and double down on the more valuable group.
  • Who might be interested in buying? The customer who just clicked one of your advertisements yesterday! Build a separate campaign to retarget recent clickers. They already had one foot in the door, why not invite them back into your shop?

2. Creative matters 

While it’s all good and well to say “test, test, test” and “vary it up to see what works,” that’s like saying the secret to cooking well is to use the stove and the oven. Here are a few specific creative tips proven to maximize conversion:

  • Trying to get customers to come to your website or app? Use concrete numbers to illustrate why they should check it out — e.g., Over 1,000 new items in the collection! 5 million people already shop in our app.
  • Articulate your best feature and clearest value proposition. Consumers are bombarded in every channel; try picking an area and going all in on that one particular differentiator — e.g., The best place to shop for the whole family! 
  • Bringing a customer into a mobile experience? Feature a smartphone in your creative to show your exact use case and how your app will work. It may seem simple, but it boosts conversion.

3. Interactivity sells 

Whether you’re pitching a new customer or re-engaging a shopper who’s looked at an item on your site before, try using a dynamic creative format that displays multiple products. Presenting a mini shopping experience while giving a feel for your offerings has proven to increase clickthrough rates by as much as 180 percent.

For new potential customers, you can use your own first-party data or other reliable data sources to tailor which items you feature. For example, in ads for a large multicategory store, you might show women offerings for shoes, bags and apparel, while men see gifts and home goods.

4. Your best customers keep giving

One of the easiest ways to start unlocking the power of your data is to identify your best customers and find more like them. One big-box retailer we worked with took its branded customer list and had a lookalike model built using those customers as the seed audience. This segment — as well as the subsequent targeting iterations built from these profiles — dropped the retailer’s cost of acquisition to its app by 56 percent.

Speaking of your best customers, they may benefit from a nudge themselves. You can bring your offline data online and target them digitally to stay top of mind.

5. Don’t let ‘perfect’ be the enemy of ‘good’

“We’ll have the perfect campaign for each of our 28 different shopper personas!” one of your colleagues might shout after reviewing analysis. More PowerPoint documents will be created to determine the subtle differences between “Cheryl” and “Martha” personas.

Along with the power of data comes a challenge — it’s easier than ever to make campaigns needlessly complicated.

It goes without saying that a rigorous, data-driven approach can take more time and effort to implement. However, that shouldn’t keep you from staying focused on what you set out to do in the first place: delight more shoppers and bring more of what you offer to the world.