Author Archives: Eric Picard

Apr 03 2015
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Ad Ecosystem, Ad Technology, Predictions, Publishers

The Fundamental Changes Happening In Programmatic Today (What ever happened to Programmatic Direct – or Automated Guaranteed?)

By Eric Picard (Originally Published on AdExchanger.com – Friday, April 3rd, 2015)

Media buying and selling have been on a slow evolutionary course since the late 1990s. With real-time bidding at the forefront, the industry has evolved rapidly since 2007, but relegated primarily to direct response on the buy side and remnant inventory sales on the sell side.

Most media sales – about 80% of digital dollars – have still been done over the direct channel, with RFPs, negotiations and inventory purchased well in advance of the campaign’s “go live” date. Despite significant growth in programmatic mobile and video, programmatic still represents a tiny fraction of dollars spent in those media channels.

While we’ve heard a lot about “automated guaranteed” over the last few years, the sector hasn’t grown as quickly as many would like. Analysts have been bullish about its growth, with Magna Global estimating that 83% of digital display spending will be “programmatic” by 2017, largely driven by the adoption of automated guaranteed and other types of “programmatic direct.”

We see the kind of growth expected in the RTB space, but not in the automated guaranteed space. Although some were gaining traction, vendors had trouble making money and several leaders were acquired last year for fairly low prices.

The amount of traction has been debated behind closed doors, with the quiet consensus emerging that automated guaranteed isn’t really taking off. The question is: Why not?

Automated Guaranteed’s Biggest Hurdles

Until a few years ago, publishers were a bit squirrelly about RTB. Sales-driven organizations doubted that RTB could provide the value that direct sales have produced for 20 years, and there was a belief that RTB drove prices downward.

Five years ago, new vendors entered the fray to focus on solving an old problem: automating the convoluted process of buying and selling direct ad campaigns. They sold publishers on this idea and created pipelines that allowed publishers to create packages that could be pushed over an API to buying tools, and would automate and streamline the human interactions that take place during a media buy.

This is a very logical path to go down – billions of dollars are spent on these direct media buys and everyone agrees that this space is incredibly inefficient. So why not just build some automation and have the whole thing streamlined and driving growth of the market?

Several factors have limited growth of the automated guaranteed space. One is that publishers have treated it like a new sales channel to shop inventory packages, not as a means to replace the standard RFP-driven direct channel. Publishers use automated guaranteed as an intermediate sales channel between direct buys and remnant sales. They have tried to use it to open up more direct buys – effectively money that was never on the table before – and entice buyers to pick up inventory packages directly instead of using RTB.

But analysts, vendors and many sales executives didn’t envision this for automated guaranteed. The goal was to push direct sales into this automated process for selling and for buyers to adopt buying tools that streamlined the RFP process. While there has been some success with this model – particularly with dedicated buying tools in the direct space – overall it has been sluggish.

To exacerbate the problem, publishers tended to package inventory for this channel in ways they’d never do if they were responding to an RFP. One media buyer I talked to about this debacle laughingly said, “They’re creating media packages and pushing them through this channel that they can’t even sell with their sales force involved. Why do they think anyone will buy it over this channel if they can’t sell it with people?”

The implication is that most buyers aren’t interested in publisher-defined inventory packages that aren’t tailored to the specific campaign goals. And what most publishers have missed is that buyers have complete control over the inventory definition when buying over the RTB channel, which has been as much a growth factor as reducing waste or lowering average CPMs. Control always wins for buyers.

These various problems with the automated guaranteed channel have slowed adoption and growth of the programmatic direct space and produced a chilling effect on investment, leading to some of the vendor exits. But this is only in the automated guaranteed portion of the “programmatic direct” channel. There are many ways the market is beginning to improve and reinvent the media buying and selling process, and automated guaranteed is only one of them.

The final major issue here is that automated guaranteed is solving an old problem without changing the nature of the thing it’s trying to solve. It has made direct buys more efficient, rather than producing radically better direct buys.

As the automated guaranteed space was inventing itself, the RTB channel evolved much faster than anyone expected. Publishers began to begrudgingly admit that RTB wasn’t a “race to the bottom” as many feared and instead was driving significant revenue at a significantly lower cost of sales. As skepticism and suspicion evaporated, publishers have become open to bigger and broader uses of RTB.

RTB Growth

RTB has given us more value than direct buys and helped us find ways to radically improve upon direct buys. The largest vendors in the space, particularly DoubleClick and the closely related AdX exchange, rapidly innovated and released technologies like Enhanced Dynamic Allocation (EDA), leading publishers to experiment with the way they allowed direct and RTB demand to compete with each other over impressions in real time.

The result has been a significant increase in yield and overall rising CPMs in the RTB channel. In many cases, demand coming from RTB yields higher than direct buys. Using tools like EDA has not led to underdelivery or undercutting of direct deals.

And while “standard RTB” has grown rapidly and is now encroaching on inventory that traditionally was reserved for direct deals only, private marketplaces have been a real winner in the RTB space. While Deal ID as a mechanism for instituting a private marketplace buy has been somewhat vilified in the industry trade press, complaints are mostly unfounded. Private marketplace deals over RTB have grown incredibly fast and are poised to accelerate. We’ve also seen buying and selling tools rapidly advance and processes are becoming streamlined.

Buying teams within agency trading desks (ATDs) use various flavors of private marketplaces to enact one-to-one deals with publishers that largely replicate direct buys. They’ve also completed more extensive global deals with publishers that take advantage of the total demand they represent as an agency and share the supply among their clients. They are even using these broader deals as differentiators with their competitors.

Similarly, the demand-side platforms are creating differentiated supply deals with publishers that put them toward the top of the queue within the ad exchanges and, in some cases, help them bypass the exchange infrastructure altogether using RTB-based buying tools.

We’re now seeing that the ATD model itself is fracturing as media agencies pull the resources and capabilities of the ATDs in-house and push their media buyers to incorporate programmatic mechanisms into the standard buying process. Executives at nearly every large media agency and most holding companies are privately or even publicly stating that programmatic – primarily RTB mechanisms – will be incorporated into mainstream buying teams starting this year, if they haven’t done so already.

One major area of investment needed in order for media agencies to begin adopting RTB at large are tools for planning and executing buys that support the needs of a more “standard” media buyer. Specialists will certainly be helpful for the tools of today, but media planning and buying as a discipline is missing a significant window of insight and execution capability that could be coming from this channel. Tools for planning buys across direct and programmatic channels (RTB, private marketplaces, automated guaranteed and across various differentiated vendors) are desperately needed in our space.

As you might expect, vendors connected to the exchange infrastructure get access to data about all impressions defined by all criteria – including publisher, contextual, geographic and first- and third-party data segments. That data has yet to be unlocked for broad media planning and buying but soon will be. You might imagine this is an area where I’m spending a lot of my time.

I believe that success will be driven by broad shifts in the programmatic space, faster adoption of RTB-enabled buying and selling mechanisms, new programmatic offerings beyond RTB and tools to help less specialized buyers to be successful in programmatic.

Feb 18 2015
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3rd Party Data, Ad Ecosystem, Ad Technology, Data Collection, Online Media, Targeting

The real reason advertising isn’t more relevant

By Eric Picard (Originally Published on iMedia – February 18, 2015)

I have been pretty publicly dismissive of the idea that we will see significant consumer value driven by ad targeting’s creation of more relevant advertising in the near future. Despite the frequent claim in the industry, I’d call this a false meme today; we don’t have nearly enough disparate messages from marketers to segment the population well enough. At the very least this future is further out simply because there are not enough advertisers spending enough money on enough distinct messages for enough distinct industry verticals, or enough products, to allow us to have enough relevant messages to show people.

Let me be clear: There are privacy issues with which we must contend. But if we step past them for the purposes of this article and look just at this issue of relevance driving value to the consumer, we have a long way to go. The current trend toward massive use of retargeting clearly isn’t hitting this mark if we just make our judgment based on anecdotal input from friends, family, and ourselves. How many times have you experienced (or been told by someone else about) the situation where you visit an online store, buy a product, and then get targeted with ads for the product you just purchased for several days afterwards on numerous websites?

Are the ads more relevant to you? Maybe. Do they add any value to you? Quite the opposite. You probably find the situation as annoying as I do. If I buy a new grill, show me products related to grilling — not the damn grill I just bought. If I buy a new pair of shoes, show me clothing or accessories related to the shoes. If I buy a new car, stop showing me ads for that car or even its competitors. Instead, show me ads related to the fact that I just bought that specific car, or even just that are relevant to a recent car buyer. But at the very least, stop wasting your money showing me the exact product I just purchased.

Frankly, there are reasons why the scenarios I suggest above aren’t happening. About 10 years ago, I had a conversation with an executive at a major publisher who was complaining about how irrelevant the ads on the website were to him. He hated the fact that he kept seeing a “toenail fungus” ad when he didn’t have toenail fungus. Instead, he would love to have seen ads for rock climbing gear, as that was his passion and he was currently looking for new gear.

I explained to him that the toenail fungus ad was creating both category and brand awareness so that if and when he eventually got toenail fungus, he’d remember that he could fix the problem. I also noted that we currently had literally not one ad from an advertiser that sold rock climbing gear available to target to him, so we could not meet his ad targeting needs in that way. This caused him pause. He finally got the point and was willing to concede that maybe he was a good target for toenail fungus ads — but that he hated the creative of the ad and found it “disgusting.” I explained that we could adjust the creative acceptance policy of the site to deal with that issue editorially and that maybe the ad would be more effective if the images were less graphic.

In those days, before programmatic advertising, the solution to the problem seemed like it was just around the corner. But now, a decade later, we still haven’t solved the issue. For clarity, I do very much believe that there will be a tipping point — that as we add the infrastructure and data needed to micro-segment audiences, we will see major changes. Once we have the ability to show a high-quality ad experience and effectively segment users to put ads in front of them with the same level of segmentation as a niche magazine content experience, advertisers in the myriad niche segments of advertising will flood the digital channels with creative that can be matched to the right user. We should explore this a bit.

Consider this example: We are trying to build an advertising experience that is more relevant, and the profile of the person is a 45-year-old male suburban homeowner who is an avid golfer and sports car enthusiast, with teenagers in the house. We can probably find some number of ads that are relevant. But if we want to really add value to that person, we need to have deeper profile information with a better experience of where he is in the buying cycle for those individual areas and categorization of creative messages to help tailor the ad experience for the individual.

Example: The avid golfer. There’s a whole ecosystem around golf that could be useful in creating value to the user beyond just showing ads for golf equipment in general. For instance, if our golfer was shopping for a new driver, it would be relevant to show him ads for drivers. Or if several new clubs had been purchased recently, maybe the ads should focus on balls, bags, shoes, or clothing.

Targeting our golfer based on specific product matches are pretty obvious, but equally interesting would be if he lived in the northeast, it was winter, and he’d recently showed interest in booking a vacation. In that case, the systems should be tailoring the vacation advertising around golfing destinations. This means ads for all sorts of products and services need to be categorized by the messaging used within them such that this kind of matching could be accomplished. Similarly, tailoring ads for numerous products and services around golf should be possible and make those messages more relevant to our golfer. But obviously to make that experience work well, we’d need lots of products and services that could be tailored around the “concept” of golf. Otherwise, we’d show this poor guy the same five ads all the time.

Our systems are on the cusp of these capabilities today. In fact, some of these scenarios could be activated by specific vendors in the industry. But the capabilities need to be ubiquitous enough that marketers drive those scenarios into their advertising creative and into their media plans. So it’s a bit of a chicken-and-egg conundrum: Marketers aren’t driving these scenarios to their vendors, so the vendors haven’t yet activated the capabilities to fulfill the scenarios.

We will get there. But it could take some time.

Feb 05 2015
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Ad Ecosystem, Economics, Marketers, Media Agencies, Online Media

The New Premium: How Programmatic Changes The Way Advertisers Value Inventory

By Eric Picard (Originally Published on AdExchanger.com Thursday, February 5th, 2015)

Five years ago, if I told anyone in our industry that I wanted to buy or sell “premium” inventory, we’d all picture the same thing: inventory that was bought or sold directly between a media buyer and publisher’s salesperson. Maybe it would be home page inventory or a section front, a page takeover or rich unit. Or perhaps it would just involve a specific publisher that we agreed equated to “premium.”

New programmatic technologies are radically changing how we think of inventory overall, especially the term “premium.” Inventory is no longer one- or two-dimensional – the definition has become much more complex. It is a multidimensionally defined set of attributes that includes traditionally “publisher-controlled” inputs, such as page location, dimensions of the creative, category and content adjacencies. But today there are additional overlaid attributes that flesh out the definition.

Advertisers can bring their own data to the dance, which we’ll hesitantly call “first party,” and overlay additional data sources, which we’ll hesitantly call “third party.” And beneath the surface level attributes are underlying components that can be much more dynamic. These components can help predict how effectively an impression can drive a campaign’s goals or outcomes.

Programmatic buying platforms historically were tied to open exchange inventory, but increasingly, they are used as primary buying platforms across open RTB, private marketplaces, direct publisher integrations and even to support direct buys. This more holistic approach ultimately leads to a “programmatic first” point of view, as the new inventory definitions being rightly demanded by advertisers become their starting point on media buys. While RTB “only” represents 20% to 40% of budgets today, it’s clear that the rapid growth of programmatic will drive these broader inventory definitions across the buyer-seller boundary.

Achieving Symmetry

Publishers are embracing the newly empowered media buyers, allowing them to bring their own data for direct buys. They are also allowing buyers to connect directly to their ad servers for programmatically enabled direct buys and buy-side inventory decisioning in real time. For the past few years, the asymmetry of information in programmatic – publishers had no idea why advertisers bought their inventory on the exchange – has been a sore point.

Publishers point out that if buyers work with them, they can open paths to the inventory, inclusive of audiences, that buyers are looking for on the exchange. As we see more collaboration between buyers and sellers on these points, pockets of highly valuable inventory that were lying dormant inside the publisher’s ad server (dare we say “premium”) will suddenly open up.

To use a mining analogy, publishers previously sold unrefined chunks of ore to media buyers, who found a variety of metals inside, but only some of it was valuable to them. So buyers started buying inventory through other marketplaces that allowed them to use their own tools and data to locate the chunks of ore that contained the metals they cared about. Now publishers are saying, “If you’re willing to pay us what you think that metal is worth, we can find more of it than you’re getting on those secondary marketplaces. But you have to work with us to get access to it.”

This new approach is both exciting and refreshing. The industry is getting over old suspicions and reluctance to share information. The asymmetry is becoming more symmetrical, and everyone involved gets more value. Days are still early, and only the most advanced players are figuring out how to make this work, but it won’t be long before this new way of defining “premium” is the standard.

Evolving Definition

How do we define “premium” in this new programmatically enabled world? Premium inventory matches the advertiser’s holistic goals, inclusive of where the ad will run – publisher, category, page location or format – and the multidimensional profiles of anonymous users behind the impressions, including first- and third-party audience data definitions, as well as geographic, demographic and other data elements provided by publishers and other parties. The advertiser believes the premium inventory will help fulfill their goals and drive outcomes that they desire.

That’s a mouthful, eh? How about this: Premium inventory matches the goals of the advertiser well enough that they’re willing to pay a premium for access.

Dec 13 2014
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Ad Ecosystem, Marketers, Media Agencies, Publishers

How private marketplaces actually work

By Eric Picard (Originally Published on iMedia – December 13, 2014)

Recently Ricardo Bilton wrote an article for Digiday about the difficulties that publishers have had embracing private marketplaces (PMPs). The validity of his article is arguable, and he called out a few of the buy-side platforms as causing some of the difficulty — despite the massive and growing volumes those platforms are actually driving in the PMP world. So instead of rebutting his article, let me define how these things work, and what the scope and difficulties are in making use of private marketplaces, but also what benefits can come from them.

Before we get into it, let’s talk about complex vs. complicated. They actually mean different things. Complex implies that the difficulty of embracing something is unavoidable — some things are just complex, have lots of moving parts and lots of opportunities to implement. Complicated implies that the difficulty is avoidable, and could be designed around. Private marketplaces today are both complex and complicated. We need to remove the complications.

History

Back in the dark ages of the programmatic world, let’s say 2008, publishers were wary of the newly emerging programmatic landscape. In order to convince them to put their inventory into the proto-exchanges that existed, the concept of a private exchange or private marketplace evolved. Keep in mind that up to that point, mostly the inventory that flowed on the exchanges came from ad networks daisy-chaining their inventory together. But as publishers began participating, and SSPs entered the scene, these private marketplace mechanisms were rolled out to support publisher concerns about yield optimization — and especially cherry picking and cream skimming — buying strategies that were major concerns for publishers in those early days.

As a result, the first private marketplaces were fairly simple to understand, and were nice ways for publishers to get their feet (or at least their toes) wet in the programmatic space. The basic concept was simple: Publishers could expose some or their entire inventory to an exchange or SSP. They could hand-pick which advertisers were invited to come into the private marketplace. Only those invited to have access could bid on the inventory.

The problem with this early approach was that it missed out on some very important fundamentals of exchange-based buying and selling. One important fundamental is bid density: For every impression that is exposed to an auction, you need as many bidders (buyers) as possible competing for that inventory in order to have the price reach a reasonable amount — especially in a second price auction.

What is a second price auction?

It’s a pretty simple idea, really — if three people participate in a second price auction for an Apple, all three people put in the highest price they’re willing to pay for that apple. Person A bids $1.00. Person B bids $1.50. Person C bids $0.50. Person B would win the auction, but only pay $1.01 for the Apple. The reason for a second price auction rather than a first price auction (in the example above for a first price auction, person B would still win, but would pay $1.50) is to encourage the bidder to put their true price into the auction. Second price auctions are generally understood to have less “gaming” of the auction — since the high bidder is protected from overpaying.

But in a world where only one or two advertisers are bidding on the same impression, there’s often no second price to use. So private marketplaces by nature are problematic when it comes to bid density — and many early private marketplaces ultimately failed to succeed. There are mechanisms that can be tried — for instance using a first price auction for private marketplaces — but of course this can lead to rampant gaming of the auction — and rarely will a buyer put the actual price they’re willing to pay into a first price auction. Another mechanism is price floors –which protect the publisher from having the impression fall on the floor for close to nothing — but often a PMP price floor in those days became a price, rather than a floor due to the lack of bid density.

As our industry evolved away from the original exchanges and toward real-time bidding, a whole host of new complex issues were uncovered — but also amazing new capabilities. One of the key things that this drove in the PMP world were new innovations like dynamic floor pricing — where the SSP or even the publisher ad server was able to analyze demand across the ad server, the SSP, the PMP, and the open exchange and set the floor on a per-impression basis.

As publishers got over their initial fear of programmatic selling, they began to put their inventory into the open exchange and blend the private and open bids into the same auction. Publishers quickly realized that they needed to give the buyers that had private marketplace access a set of preferences so that they would continue in the PMP rather than bounce out to the exchange. This led to all kinds of mechanisms — across various systems that have brought us to our modern programmatic landscape for private marketplaces.

Private marketplaces today

Private marketplaces today are very confusing. They’re both complex and complicated. There’s no clear and simple definition of a PMP that means exactly the same thing to everyone because there are so many ways to implement one. And depending on your ad server, your choice of SSP and/or exchange, and the buyer’s DSP, it’s fairly impossible to know in advance how the PMP will instantiate itself. Literally if you took five impressions of a PMP and reviewed them, each could be delivered completely differently from the others.

For publishers looking to start using private marketplaces today — without any legacy configurations or expectations, there are some benefits of having waited. Today PMPs are really about giving the publisher control over the way their preferred customers get treated by the auction. As everyone knows, when you have a big customer, who spends a large amount with you annually, you probably want to give them some discounts and benefits for working with you. Private marketplaces today are evolving into sets of controls for protecting the relationship with the buyer, and often for giving them either a discount, or giving them better access and control over the inventory they want to buy. It is the latter scenario — giving the buyer control — that makes some publishers very nervous, but is the real benefit of the PMP in today’s market.

In this scenario, the publisher lets their big spending customers get some additional control over defining the audience and the inventory that they have access to. Sellers frequently will bundle this additional control with a larger overall buy, or with a high minimum CPM, or with a high minimum overall budget. And publishers are finding that this approach makes everyone on all sides of the deal much happier. Everyone wins, as long as the complexity required to pull this off is embraced.

One of the biggest innovations in the programmatic world, and one that causes a lot of the complexity behind the issues this space has been saddled with, is the Deal ID. Deal ID was supposed to solve many problems in the programmatic space, but they have added another layer of complexity. The trick is to embrace the complexity without structuring things in such a way that they become unnecessarily complicated.

What is deal ID?

It became clear that while RTB was a vastly superior way to buy and sell ads than anything else we’d seen as an industry — there were touch-points between the old systems and the new systems that were confusing. Nowhere was this confusion worse than when a buyer wanted to execute a guaranteed deal over the RTB infrastructure.

But that Deal ID mechanism has now been used in much more flexible ways than its original driving intent. Think of a Deal ID as a way to prioritize a buy against supply. And the features for how you prioritize the bid vary by ad server, by exchange, by DSP, and by SSP. Sometimes the combination of each of those things leads to a different set of capabilities.

If you’re feeling confused, you’re getting the picture. This isn’t simple stuff. But that’s okay, because with complexity comes opportunity. Here’s a complex, but powerful scenario that Deal ID opens up:

All of these bids are Deal ID bids — prices are CPM:

  • Advertiser A sets up a dynamic bid that lands at $5 for the impression. Publisher floor prices this advertiser at $7.
  • Advertiser B sets a dynamic bid at $6 for the impression. Publisher floor prices this advertiser at $4.
  • Advertiser C sets up a dynamic bid for $17 for the impression. Publisher floor prices this advertiser at $20.
  • Advertiser D sets up a dynamic bid for $1 for the impression. Publisher floor prices this advertiser at $3.

In the above scenario, Advertiser B would win the auction, and pay $6 CPMs for that impression. Since one of the Deal ID bids won the auction, the impression never makes it to the open exchange. If for some reason the publisher had set the floor price for advertiser B at $7, then this auction would have flowed through to open exchange, and then advertiser C would have likely won the auction (assuming nobody in the open exchange bid higher than $17). Advertiser C would end up paying whatever the next highest bidder was willing to pay, plus $0.01.

How was that for complex? Want it to be more complex?

Some ad platforms can support a Deal ID with a dynamic bid, or a fixed price with a priority cascade. So while price mattered a lot in the example above, if one of those bids (even the low bid) was a fixed price, it would have won the auction at the fixed price. That’s how you give your preferred advertisers ways to find their preferred audience while giving them a fixed price. The trick is to negotiate well on the price on both sides so everyone gets what they want.

So while Deal ID is just one mechanism that may or may-not be part of a private marketplace, the two concepts are becoming somewhat inextricably linked together. What is a private marketplace today? It’s a complex set of interacting tools, systems, mechanisms, and approaches that can be used to give the publisher control over the prioritization of their supply against the demand represented over the exchange. Easy to understand? No. Easy to configure? No. Easy to execute against? Not yet. But worth using? Absolutely!

This complexity means power, but the complexity leads to confusion and complications. So when we have people who aren’t practitioners writing articles about very complex systems and how they are used, and then going to sources for quotes about adoption of these complicated scenarios, the answer is going to either be vague (not quotable) or clear (not accurate.) And these clearer quotes, which aren’t really very accurate in many cases, paint a picture of the space that looks like it isn’t working.

Private marketplaces give publishers control over the prioritization of buys coming from the programmatic channel. As an industry, we’re still figuring private marketplaces out — but vast and growing dollars are being spent over them in the meantime, and those buyers and sellers willing to take the time and effort to understand the complexity are winning. Yes, we need to make the execution of private marketplaces less complicated. It would be nice if we could also make them less complex, but only if we don’t lose the power that comes with the complexity. And in the meantime, the channel is growing and productive.

Dec 01 2014
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Ad Ecosystem, Economics, Online Media

Don’t Believe The Lies About Digital Media

By Eric Picard (Originally published on AdExchanger Monday, December 1st, 2014)

For years, there has been a series of bad memes spreading throughout our industry. Some of the big ones have caused a huge amount of misunderstanding in our space.

Here’s my favorite: “There is infinite supply of ad inventory. With this overabundance of supply, the cost of inventory will be driven to zero.”

This way of thinking caused the publisher side of the industry to fear and block adoption of programmatic buying and selling until the last year or two, when it was proved to be false.

A simple truth: All ad impressions (in a nonfraudulent world) are created by a person seeing an ad. I estimate that there are 5 trillion monthly digital ad impressions in North America. If we divide this against roughly 300 million active Internet users in North America, assuming they spend on average five hours a day consuming content on the Internet, that breaks down to approximately 100 ads per hour.

So we as an industry have 100 chances an hour, or about 500 chances per day, to reach each person in North America with a digital ad. Of the 300 million people we can reach, advertisers only care about a sliver of the total audience.

Once you break down the audience to the desired number of people to reach, with the relevant targeting, the question becomes: Of the 500 daily opportunities, how many times do you want to reach that group of people? It comes down to several factors: what mechanisms you, as a buyer, can use to identify them and deliver an ad to them, the format of the ad and how effective you believe your opportunity to reach them will be.

So, no – the number of impressions is not infinite. And if we believe that some percentage of the ads in that 5 trillion monthly statistic are fake, meaning fraudulent or simply not viewable, then the number of chances to reach consumers could be much smaller, from 100 to as low as 50 ad opportunities per hour.

Suddenly the lie is turned on its head and it becomes more about maximizing the opportunity with your target audience. And for those opportunities, the cost is definitely not heading toward zero.

Not True: Ad Inventory Can Be Defined By The Publisher And Divided Into Pools Of Undifferentiated Impressions

Ad inventory is made up of a group of individual, unique ad impressions. Every impression has hundreds of points of data surrounding it. The problem with this belief is that it assumes limitations that don’t exist. Publishers define inventory in broad, relatively undifferentiated buckets, which are the lowest common denominator from a complex media plan sent with a fairly detailed RFP by the buyer.

For instance, buying a million impressions of “soccer moms” from a publisher creates a very limited view of that inventory. The range of income, interests, product ownership or geography is broad for the individuals behind those impressions. And some “soccer moms” may be worth more than others depending on an advertiser’s campaign goals.

In a world where inventory is publisher-defined, this lowest common denominator approach was the only way to operate a scale media business. But that’s no longer the case. Buy-side decisioning allows the buyer to define the inventory – and that inventory definition by nature can be more complex than ever.

So what is an impression? Ultimately an impression is a human being engaging in a monetizable experience via a computer or digital device, in a certain modality. By modality, we mean that they’re either passively consuming content (such as watching a video), actively consuming content (reading an article or email), actively participating in an interruptible interactive experience (playing a game with breaks between levels) or actively participating in a non-interruptible interactive experience (writing an email or engaged in a video chat).

All the data about the person behind the impression is captured in first-party (buy side and sell side) and third-party data platforms. And all the data about the content being consumed, and the user’s modality, belongs to the publisher. It is by matching both types of data that we can truly unlock the value of inventory. The more open and transparent we make things, the more value we unlock. By giving buyers access to the unfettered truth of inventory and the ability to peruse and pay for their desired inventory, price ultimately tends to go up, not down. The old world of limited, siloed and blocked data is responsible for this lie.

As we’ve opened up inventory sources and unlocked access to audience and modality data, the market responded by equalizing prices. As a result, publishers can make just as much money from programmatic channels as direct sales. Publishers that are allowing demand from programmatic sources to compete directly with guaranteed inventory are becoming pleasantly surprised with the results. Publishers that started early on this path are gaining some significant advantages that could be sustainable over the long haul.

Not True: Publishers Don’t Let Buy-Side Systems Access Inventory Because Of Potential Data Leakage

This is an old misconception. Back around 2005, some publishers invested in technology to enable creation of “publisher first-party” audience targeting data. They tracked individual audience members’ activity on the publishers’ sites and put these content consumption behaviors into behavioral targeting segments. They could then sell these segments as inventory definitions, rather than just selling locations.

This was very useful when publishers had small pools of valuable inventory that would sell out, such as auto-related inventory that would sell out months in advance. So publishers tracked users who read articles in the “auto content” bucket and created a segment called “auto intenders” so they could sell ads targeted to those users when they were browsing other pages of the publisher’s content. If they charged $15 CPMs for auto content ads, they would sell behaviorally targeted “auto intenders” for $10. They’d deliver those ads on pages that were probably selling for $5 CPMs, more than doubling the yield on those impressions.

The problem is that only the largest publishers with big user bases that consumed lots of their content could assemble enough valuable behavioral data. The small window into a person’s web-surfing behavior that any one publisher had access to was not enough to really create sustainable value. However, that data was created, sold and valued by the market, although it was less valuable to buyers because it originated from user activity on just one publisher, rather than data pooled across publishers.

Right around that time, the first behavioral ad networks, typified by Blue Lithium, figured out that they could supercharge their behavioral targeting segmentation by buying guaranteed targeted buys from publishers and stealing segmentation data from the publishers. They maximized reach by keeping the frequency cap as low as the publisher would allow, then dropped their own cookies on those users and added the publisher’s targeting definition to their own.

For instance, say a buy of “auto intenders” from Yahoo had a frequency cap that was set to one. If the ad network bought 1 million impressions for a $10 CPM, they would add 1 million unique users to their own cookie pool of “auto intenders” for just $10,000. They could then find those same users on cheaper sites, and eventually buy the inventory over ad exchanges for less than $1 but sell it for $8, allowing them to arbitrage the market. Since these networks could turn small expensive direct buys into feeders of their behavioral targeting pools, and then extend those buys to cheap inventory sources, publishers obviously became very concerned about this “data leakage.”

Most publishers, other than the very largest, stopped investing in their own first-party behavioral data technologies, leading to the creation of the lie that publishers are deathly afraid of data leakage. But what people missed is that most publishers simply gave up fighting this battle. Instead they partnered with third-party data providers that paid publishers for the rights to collect behavioral data.

They would then push the behavioral segments back into the publisher’s ad server so they could sell the data as part of their direct buys. The data leakage problem led to the creation of the third-party data marketplace and the tracking of users across publishers, which marketers find more valuable.

The real value that publishers can provide is not in turning the behavior of their audiences into targeting data. Instead publishers can give buy-side decisioning systems access to data about the content being consumed (category-level data) and what users are doing on those pages (modality data). They can also enable the buyer to bring their own first-party data, which is far more valuable for buyers than anything the publisher could assemble.

Everybody wins when publishers open up competition between decisions made by a demand-side or buy-side ad platform and direct buys booked through their sales force. When given the opportunity, buyers are willing to pay similar or higher rates for access to this inventory, compared to what they’d pay for publisher-packaged inventory that only offers publisher-based ad decisions. The two methods competing with one another increases the value of the inventory and maximizes the yield for each impression. It’s a “win-win” or a non-zero-sum game – a good thing for everyone.

Dec 01 2014
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3rd Party Data, Marketers, Media Agencies, Targeting

How To Use RTB For Targeted Reach Instead Of Retargeting

By Eric Picard (Originally published on AdExchanger)

I was recently told by an executive in a position to know that 70 to 80% of revenue in the RTB space comes from retargeting. I found that stunning because it basically tells us that the RTB space is incredibly immature. If the vast majority of revenue in the space is retargeting, then nearly all the spending comes from ecommerce companies.

That means we have huge upside in this space because ecommerce companies certainly don’t make up anything near the majority of advertising spending.

Nearly 90% of advertising spend “all-up” is done on a targeted reach basis. In other words, the advertiser has come up with an ideal marketing persona (or series of marketing personas – many brands have five to 10 defined marketing personas) and their media plan is designed to reach people matching that persona. Using old-school methods, such as Nielsen or comScore, they find publishers with audiences matching their marketing personas, and that’s where they’ll buy impressions.

The problem is that this is extremely inaccurate, and wastes budget by spreading it across the whole audience that visits this publisher. On one hand, it’s wasteful because it pushes the message on audiences that don’t match campaign goals. On the other hand, it’s OK if there’s some “waste” in media spending because there’s value in getting the message in front of slight target mismatches.

Case in point: I don’t have cable at home. We watch Hulu, Amazon Prime and Netflix when we consume TV content. But recently, while traveling, I saw a few hours of TV in my hotel each night. I was shocked by the vast number of pharmaceutical ads on broadcast television – especially on the news (which I hardly watch anymore).

Most ads related to conditions I’m not facing today – so in a sense those ads were wasted. But should I ever contract one of those conditions, I’ll likely remember those products exist. Or should one of my close friends or loved ones get stricken with those conditions, I’ll recall that a medication exists and engage in conversation with them.

So yes – this broadcast brand strategy certainly does have some value. As I’ve said before: There’s value in the fact that I know Dodge Ram owners are “RAM Tough.”

On the other hand, we can be much more precise now than in the past — if you can find the data. And if you believe in the methodology that created the data, there are ways to more precisely reach your target personas and target audiences of all flavors.

Find The Right Tools

Using demand-side platforms and social media marketing tools, including the self-service tools within Facebook, it’s now possible to find your target audience in a variety of ways. You can be very narrow or very broad. You can control exactly which sites on which you’ll reach that audience, or you can simply specify on which sites you don’t want to reach your audience.

For brands that are very particular about running ads only on approved content, there is the white list – a specific list of domains matching against publishers that you specifically approve to run ads on. This does limit scale, but there’s no limit on the size of the white list you can create.  And there are vendors like Trust Metrics that you can use to build a custom white list for you, which both hones the targeting to sites that match your brand safety metrics and massively reduces fraud.

Or if you want, you can use private marketplaces to execute buys only on the sites you specifically negotiate with for access to their audiences over RTB. This has a lot of value for pharma and marketers that are extremely sensitive to running ads on sites that match their brand values.

If you want to specify a tightly targeted user base, one that is so targeted that it limits the audience size to only a few thousand users, you can do that using tools like Facebook’s advertising that lets you specify many different elements and tells you how limited the size of your audience is.

Or there are tools like Optim.al, which hones the audience and offers ways to expand or contract it. Or tools that let you find audiences similar to your targeting with less targeting but greater impression volume. (Disclosure: My company Rare Crowds does this.) Or you could use MediaMath’s built-in features to automatically find the right audience that performs best for your campaigns.

Nearly every company playing in the RTB space has functionality designed to meet the needs of advertisers that want to reach specific audiences, not just retarget people who visited your website or who are existing customers. There is the potential to reach people you haven’t reached before, find new customers and prospect for them.

The biggest growth sector for RTB this year is clearly going to be brand advertisers and those that use RTB for targeted reach — just like 90% of all media spending.

Nov 15 2014
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Ad Ecosystem, Ad Technology, Marketers, Media Agencies, Online Media, Publishers

Programmatic buying: The FAQ every marketer needs

By Eric Picard (Originally Published in iMedia – November 15, 2014)

I was at the ad:tech conference in New York last week, and in one of the sessions, three different people asked about programmatic. They didn’t ask any nuanced questions. They effectively asked, “What is programmatic?” They were embarrassed that they didn’t know, but after the first person spoke up, others in the room were emboldened.

For someone so steeped in the programmatic space, this took me by surprise. Certainly, I thought, no one in our industry doesn’t know what programmatic is. Adding to my consternation was that this specific panel was focused on SEO — and I figured that anyone working in search must be in the know on what was happening in programmatic. So I walked around and asked people for the rest of the conference what they knew about programmatic, just so I could see how out of touch I was from the mainstream. While most people were relatively up to date, I was surprised by the lack of general knowledge and the amount of misinformation there was out there.

So I figured it was time to step back and go over the very basics in this classic frequently asked questions (FAQ) format.

What does the term “programmatic” mean?
The term “programmatic,” which I’ve been told I coined back in 2009, really just is the umbrella term for automated buying and selling of media. While this is how I use the term, and what the market generally tries to use it to mean, many people use it to refer just to one part of the “programmatic ecosystem” — real-time bidding (RTB).

What are ad exchanges?
Much like in the finance world where stocks, commodities, and derivatives are sold over “exchanges,” we now have mechanisms to sell advertising over exchanges. Think of this as an auction-based mechanism to sell ads. Most exchanges are second-price auctions, meaning that whoever bids the highest for an ad wins the ad impression but pays the price (sometimes plus one penny) that the second-highest bidder was willing to pay. And nearly all of these exchanges have moved to RTB. Ad exchanges typically perform the function of providing liquidity to the marketplace, letting supply and demand match fluidly. Ad exchanges are not typically where the dollars accumulate; they’re a relatively inexpensive conduit through which demand and supply flow.

What is real-time bidding?
RTB is an auction-based mechanism for media buyers to bid on advertising at the impression level, as the ad impression takes place. When the ad impression takes place, a call is made to the exchange, which submits the impression to all bidders (participants with seats on the exchange). Those bidders have a very short time — usually less than 100 milliseconds — to respond to the auction with their bids. Unlike in the world of paid search, where all the demand for ads sit within the ad system of the search engine, ad exchanges federate out the auction, meaning that each bidder contains its own demand and only submits what it chooses to the exchange. This makes the exchange more of a clearing mechanism, rather than the revenue-generating mechanism that the paid search auction is.

What value does an advertiser or media buyer get by using RTB?
RTB enables a media buyer to specify exactly what their goals or outcomes are and look only for ad inventory that matches against those goals. Sometimes those goals are performance based; sometimes they are audience based. In other words, buyers can specify what audiences they want to reach and buy only those ad impressions that match. This is very different from the experience of buying from publishers directly, where the publisher specifies the inventory definition. Over RTB, the buyers specify the inventory definition and only buy what they want.

Are exchanges only available for banner ads?
RTB and programmatic exchanges are not in any way limited to one inventory type. Pretty much any available media inventory (ironically except for paid search) is available this way. Display, mobile, video, social, and even some traditional media such as television, radio, and print are either already available over exchanges or will be soon.

How do I buy ads on an exchange?
Buying mechanisms for ad exchanges are typically referred to as demand-side platforms, or DSPs. Some ad networks also enable exchange buying but in some cases are not transparent about this (i.e., they might be buying ads on the exchanges and reselling them to their customers). DSPs are available from companies like MediaMath, Turn, DataXu, The Trade Desk, AppNexus, and others.

How do publishers sell ads over exchanges?
Publishers that are quite large can sometimes offer their inventory directly over an ad exchange. Some even have their own. But most publishers use an aggregator of one kind or another — either an ad network or a specialty platform called a supply-side platform (SSP). SSPs are kind of the inverse of a DSP and have specialized software for managing supply on the publisher’s behalf. Some exchanges are incorporating the functionality of SSPs directly such that publishers don’t need a separate vendor to support this need. And some SSPs are beginning to behave as exchanges on their own.

Can I buy directly from publishers programmatically?
Yes, many publishers make their inventory available over the exchange, and most DSPs can specify publishers they wish to include in a buy. Many publishers also have rolled out “private marketplaces” using either ad exchanges or supply-side platforms. These private marketplaces are kind of like private ad exchanges where the publisher makes its inventory available only to specific buyers. These have all the benefits of RTB to the buyer but give the publishers more control over floor prices they want to set — or even fixed rate deals they want to support with specific buyers or advertisers.

Can I execute direct buys, or guaranteed buys, programmatically?
Yes, there’s a whole subset or category of the programmatic ecosystem that is appropriately called programmatic direct. Solutions in this space are less well defined, as it is newer. But the general goal is to provide more automation to the buying and selling of media. These buys can happen over display, mobile, video, social, and even television, radio, and print. The ecosystem has vendors supporting the needs of buyers and sellers independently — and a few that are hybrid solutions. Companies in this space include Bionic Ads, Shiny Ads, Yieldex, iSocket, BuySellAds, and others. Many DSPs are now plugging into the programmatic direct inventory sources as well, allowing one-stop-shop buying of both RTB and direct inventory.

Is programmatic replacing more traditional ways of buying and selling media?
Yes. Interpublic Group, one of the biggest agency holding companies, has stated that it wants to move 50 percent of its media buying to programmatic methodologies by 2015, and ultimately do that across all media types. In public and private conversations across the industry with executives at both marketing and media agencies, the zeitgeist is definitely moving in this direction. Publishers were the holdup until the last few years, when they started to see the benefits of programmatic selling on their own. Many publishers are finding that programmatic selling provides higher yield, either because their cost of sales are lower or because the inventory is being used more efficiently.

Nov 10 2014
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Online Media, Startups

MediaMath Acquires Rare Crowds And Its Founder, Eric Picard

By Zach Rodgers (Originally published on AdExchanger, November 10th, 2014)

MediaMath has snapped up Rare Crowds, a small, 2-year-old startup founded by ad tech trailblazer Eric Picard, AdExchanger has learned.

Under the all-stock transaction, Picard will join MediaMath as VP of strategic partnerships as the media-buying platform builds out products around private marketplaces and “automated guaranteed” inventory (i.e., direct site buys).

The deal has the markings of an acqui-hire. Picard, whose title at MediaMath will be VP of strategic partnerships, is the only exec from Rare Crowds’ small team going over to MediaMath. Co-founder and CTO Scott Tomlin will consult with MediaMath through the transfer of Rare Crowds’ technology.

A well-known figure in the ad tech space, Picard founded Bluestreak, an early ad server and rich media platform. Later he was an architect of Microsoft’s ad platform strategy, and he also held a senior product role at TRAFFIQ before that company exited ad tech and repositioned as an agency.

His responsibilities at MediaMath will include oversight of the company’s relationship with Akamai, from which it acquired Advertising Decision Sciences – along with its pixel-free ad targeting technology – in January 2013.

“MediaMath is making an investment in moving beyond real-time bidding, and taking RTB technologies really far forward into other parts of the ecosystem,” Picard told AdExchanger. “The company is investing in the rest of the media plan that is not currently accessible.”

Rare Crowds was initially focused on helping publishers better package their inventory in a programmatic selling environment, but in the last year pivoted to the buy side.

Here’s how Picard described the Rare Crowds value proposition in an AdExchanger interview two years ago:

“The whole industry has been very focused on prediction. We have to predict how much inventory we are going to have so we can sell it in advance, when you are talking about premium inventory. In RTB, all of the systems that have been developed really allow you to target much better and do not have to worry about prediction.

We’re finding this hypertargeted inventory that has more than four attributes, that’s what we define as a ‘rare crowd,’ all the way out to 12 or 15 or 20 attributes. If it exists, we’ll find it.”

Rare Crowds was backed by angel investors including Hulu’s SVP for ad sales, Peter Naylor, Interactive Advertising Bureau founder Rich LeFurgy and Mediasmith CEO Dave Smith.

Nov 04 2014
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Ad Ecosystem, Ad Technology, Economics, Marketers, Media Agencies, Online Media, Predictions, Publishers, Startups

The Digital Advertising Industry Needs An Open Ecosystem

By Eric Picard (Originally published on AdExchanger Tuesday, November 4th, 2014)

Thanks to amazing new offerings from Facebook, Google, Amazon and others on deeply connected identity and tracking solutions, we are seeing two major developments. For the first time, connected identities across entire populations are available for targeting, tracking, reporting and analytics. But these identity pools exist within walled gardens, siloed to just one provider.

From a tactical and strategic point of view, I completely understand why companies create these walled-garden identity solutions. And to some extent, they will open their walls – metaphorically allowing outside vendors and partners to enter through checkpoints, accompanied by security and wearing clearly labeled badges. Nobody can fault a company like Facebook or Google for being careful about allowing entrée to their walled gardens. The potential for a PR backlash is significant, and that could cause the overall value of their offering to decline. So yes – it’s good to be cautious.

But it does create a significant issue for every publisher outside the top five or so because their first-party data pool is limited to the activity on their own site or apps. They don’t get access to cross-site activity, nor do they have a way to compete with the efforts of the biggest players on their own. It will be hard for publishers – even the large ones – to resist the momentum that will build to plug into these walled gardens, forcing publishers to effectively commoditize themselves in exchange for access to identity, targeting and analytics data.

I’ve long been a proponent of open approaches in the ad-tech space, including open source, open architecture or open APIs. I also am a big fan of well-considered and coordinated industry or consortium efforts. I believe that efforts like OpenRTB, which is pushing for an open API standard for real-time bidding, will be key to helping the industry grow.

Open efforts like this help ensure that the biggest players don’t create huge competitive moats like we saw with paid search, where Google AdWords’ creative, functionality and APIs became the effective industry standard. As a result, any time Google makes any change, all other paid search players must immediately copy Google because of its massive dominance in this area.

Even the biggest players should support these open initiatives because regardless of any disproportionate boost one or two players may get, we’re in a massive growth phase and an open approach has proven a better way to expand industries and sectors. Building significant traction is easier with scale – and by pooling scale, the whole space has the opportunity to accelerate growth.

That said, it’s highly unlikely that Google and Facebook will take a completely open approach on their key initiatives. For one, they have enough scale to catalyze efforts and markets on their own. But more importantly, it’s not in their self-interest to be open. Remaining closed gives them opportunity to maintain control and position in the market while marginalizing smaller players in the ecosystem.

I predict that we will see more industry consortiums created around areas like identity, directly in response to the very large walled gardens that are being built now. It’s really the only way that everyone else in the industry can protect against commodification and ensure a level playing field.

Oct 11 2014
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Ad Ecosystem, Marketers, Media Agencies, Online Media, Predictions, Publishers

Programmatic’s place at the top of the marketing funnel

By Eric Picard (Originally Published in iMedia – October 11, 2014)

For decades, modern marketers have developed significant marketing plans with detailed analysis of target audiences. Often before products are designed, significant amounts of market research have been developed and applied against the product or service development process.

When a brand decides to spend millions of dollars to create a product or service, it typically then spends tens to hundreds of thousands of dollars on market research and product planning to get ready to launch it.  And then hundreds of thousands to millions of dollars to market the product.

Most of that market research and product strategy folds over into the marketing plan. And as part of that process, typically very detailed marketing personas are created — sometimes a handful, sometimes more than a dozen. These marketing personas are decomposed into the marketing plan and drive many of the media mix decisions that are used to divvy up budget among channels. And often these do get distributed to the media agency as part of the marketing plan’s translation into media planning and strategy.

But in my experience, it is fairly common that by the time the media buyer gets the media plan from the planners, the marketing personas have been stripped off. And this is even more true when we bring programmatic media into view. As an example, consider a conversation I had this past year with a media buyer at a major trading desk.

This trading desk handles the media buying for a major home improvement retailer. And when I talked with the trading desk buyer about how the company approaches this customer’s media buys over its DSP partner, the buyer looked a little puzzled. To that person, it was about only two things:

  • Buying the “home improvement” segment
  • Setting the rest of the budget to optimize spend against CPA on its web pages and letting the DSP figure the rest out

The problem with this approach is that it’s extremely one dimensional — and loses much of the value that exists within the systems used. It’s like using an F-16 to commute to work. Or an aircraft carrier to run to the store.

I haven’t seen the marketing plan for the client, but I can imagine (having seen a lot of them over the years) that the retailer has several different ones. I’ll make up a few that probably exist in part, and explain how I’d have approached the campaign using a DSP.

Persona 1: Reggie is a 28-year-old single male who lives in a major metropolitan area in a condo that he owns. He makes more than $50,000 a year and mostly shops at the client’s stores to buy décor items, fans, DIY project materials, and probably will buy things like air conditioners, painting supplies, hand tools, etc.

Personas 2 and 3: Sophie is a 35-year-old stay-at-home mother who lives in the suburbs of a major metropolitan area and is married to Tim, a 35-year-old executive who works in the city and commutes. Together they own a house that is more than 4,000 square feet and has at least half an acre of land. Tim is a weekend DIY warrior, who takes on various home improvement projects. He’s likely to take on light construction projects, buying building materials, painting materials, plumbing and electrical, and lots of landscaping tools such as riding mower, blowers, etc. Sophie is an avid gardener who buys numerous plants and gardening materials, and takes frequent courses on design and gardening at the store.

Persona 4: Arthur is 65 years old. He is retired, lives in a modest home in the suburbs, which he owns outright. He is in the process of getting ready to sell the house as he and his wife are looking to move to a smaller place or a retirement community. But he has three adult children who own homes nearby, and he frequently putters and does projects around their houses. He’s likely to buy building and painting materials.

Although I just made up these personas, they’re fairly typical of the kinds of personas I have seen over my career — if anything, they’re a bit light. Additional information that would typically accompany a persona includes the numbers of each of these personas that exist in each DMA in the U.S., perhaps even broken down by ZIP code within each DMA. And then marketing teams typically will use whatever tools are at their disposal to begin matching against mechanisms like PRISM clusters and do some media mix modeling about how to reach these audiences.

At the handoff to media agency partners for digital media, the planners at that point begin using various tools to determine what sites have traffic that matches their target audiences, and an overall media plan and strategy is devised.

Once the plan is handed off to media buyers and their trading desk partners, the thinking is usually quite distilled. Buyers going directly to publishers will send over an RFP that simplifies the media plan (they may also send the media plan) for sending to publishers. They then wait to hear back regarding what inventory is available. The trading desk partners typically decide what audience attributes align against available data segments for their goals.

Now let’s go back to the example I used above about the trading desk with a major client in the home improvement retail space. Given its customer personas, I’d have recommended a few other ways to engage and find audiences.

Perhaps it could target users who own homes of a certain size or homeowners who have been in their home for a certain number of years. It could target each of these segments by age and geography. It could differentiate both creative and offer by each of these. It could vary what products to highlight in its advertising based on some of the criteria, such as age, gender, and other elements. It could target households with children differently than households with adult children not living in the home. It could even target based on the age of children, assuming parents of college age students might be moving kids into apartments or dorms at the end of summer or fall. Or it could target urban apartment dwellers with fans in the summer and suburban homeowners with leaf blowers in the early fall, snowblowers in the late fall, and lawnmowers in the early spring.

In programmatic, we far too often fall into the trap of only feeding the portion of the purchase funnel that is focused only on CPA at low costs of media plus data. As a market, we need to expand how we see programmatic media and really try to dig into the market for data and the use of sophisticated DSP platforms.

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