Winners And Losers In First-Price Auctions

Between ad fraud, brand safety and transparency, the digital advertising industry had a tough 2017. And now that the conversation about fixing these problems and cleaning up the supply chain has hit critical mass, 2018 is sure to bring new developments and approaches to delivering greater visibility into where ad spend is going and whether or not it’s working.

One of the big complaints about programmatic is that it’s difficult to understand the true value of an impression. Historically, exchanges have been based on second-price auctions, where the buyer often pays far less than what they were willing to pay. The publisher “loses” the difference between the high bid and amount paid.

In first-price auctions, on the other hand, the winning bid is the amount paid. The publisher seems to come out on top, and one could view the end cost as the true indicator of an impression’s worth. This added bit of visibility has led some to herald first-price as the route to transparency. It is not, however, a win-win game.

At the outset, publishers look like the winners of the first-price auction game. Over time, however, the forces of auction dynamics come into play. Bidders, who get little visibility into who sets the bid direction or is in control, may dramatically reduce their bids to test price elasticity, and the publisher ultimately loses.

And there’s another potential loser in the first-price model: the ad tech vendors in the middle of the transactions. Because the fees, often referred to as the “tech tax,” are disclosed, they can find themselves in a race-to-the-bottom price war in competition for agency and brand business. So they lose, and so too may the brands and agencies that rely on these vendors, since the lower markup for vendors may lead to corner cutting on quality and expertise, which could leave more exposure to ad fraud.

If matters weren’t complex enough, advertisers don’t always have enough visibility into the process to know for sure whether they’re bidding in a first- or second-price auction. As a result, they can’t properly develop a strategy that will optimize their media spend, and again, they lose.

Now, if everything were a first-price auction, there would be more transparency and a better likelihood of achieving that sweet spot of true value. But that brings up another issue: supply and demand.

If buyers feel like they’re being scammed, paying higher-than-necessary prices in the exchange, they may give up on programmatic and shift their spend to more “walled gardens,” but that is no guarantee of lower prices. Demand in the open market is then reduced, which then makes prices drop, and ultimately pushes publishers demand and prices lower.

Inside the walled gardens, there are some interesting developments, that may be a foundation for the next evolution of bidding. Facebook’s auction mechanism is an iteration of the second-price model that brings the consumer into the equation. An advertiser only wins the placement of an ad if it actually is the most relevant. With this model, the buyer knows the cost and what the ad is worth. Google, which had previously been using the generalized, second-price auction model, has followed suit. If the industry moves in this direction as a whole, it could ultimately be a win, win with an extra win for the consumer, who gets more relevant advertising.

The issues are deep and complex. But if we can make access to transparent, comparable analytics easier and enable buyers to act and react real time, it’s a step in the right direction. In the end, we need to give buyers the opportunity to adjust their strategies to allow for relevant ads to win while publishers get a fair price, based on their ability to meet the performance goals of the client, closing the gap between winners and losers once and for all.

Originally published in The Marketing Insider

AI’s Real Moment On The Advertising Stage Is Tomorrow

One of the hottest storylines in ad tech this year has been artificial intelligence (AI). Proffered as potential panacea for effectiveness, brand safety and transparency, AI has grown from niche discussion to industry obsession, a promised key to smarter digital ad targeting and trading. I’m sure you’ve seen the pronouncements: it can determine the bids most likely to succeed, it can use historical performance data to tailor campaigns and it can even swap out creative based on audience data in real-time.

There’s one issue: a lot of what’s being hyped isn’t actually AI. It’s just tools and technologies being marketed as AI in order to differentiate within a complex and competitive arena. With true AI, a machine imitates intelligent, and maybe even sentient, human behavior. And while much of what we see today looks like the computer is thinking for itself, it’s really just following very specific, pre-programmed paths using simple rule-based actions, and/or predictive analytics or machine learning. While all subsets of AI, even together they don’t add up to real AI. They’re more like “artificial AI.”

It may seem like semantics, but there are important differences. With predictive analytics, patterns in existing data are used to predict probable results and trends in the future, typically using statistical models and methods. Then, there’s machine learning, a branch of artificial intelligence where machines learn and adapt through experience, without the need for predetermined rules and human intervention. With machine learning, models and techniques will change themselves over time as more classifiers enter the system and improve the description of the data to be learned. Examples of machine learning classifiers are K Means Clustering, Linear Regression, Logistic Regression and Decision Trees. These techniques are being used in technologies today for things like facial, voice, music and handwriting recognition.

While not using true AI, the market-available technologies for programmatic advertising that we have today are still sophisticated. They effectively use machine learning and data science-based systems to predict the likelihood of desirable outcomes. They’re certainly valuable for advertisers looking to optimize their media budgets. Further, the automation they allow creates huge efficiencies. They do not, however, fulfill the promise of a set-it-and-forget-it system that gets better or more accurate without any human intervention.

When real AI is finally applied to advertising, it will be transformational. It will intelligently enable desired outcomes to be produced by calling on not one, but a collection of interrelated sciences, techniques and data processing. One day, a truly intelligent AI-based advertising system will enable buyers to seamlessly construct their entire campaign, complete with optimized buys and evolving tactics, just by specifying their goal(s) and budget. Once the algorithms take over, the system will leverage historical data about similar campaigns to make predictions and changes on the fly.

This is all achievable. But supporting it requires highly complex systems to come together, and we still have a long way to go based on today’s fragmented, disconnected assortment of pseudo-systems that look fantastic in isolation, but, in aggregate, don’t add up to the holistic system that buyers need.

Eventually, AI will evolve to where it can improve programmatic media and create a better user experience. And we will eventually get to the point where technology can drive ad campaigns that, without human interaction, achieve campaign KPIs through a virtuous circle of measuring, analyzing and acting on campaign spend, allocation and outcome variables.

In the meantime, platform vendors intent on presenting today’s “artificial AI” will accomplish more by being open about the realistic expectations of their products and the fact that their capabilities are that of early-stage, partial expressions of AI. At the same time, we as an industry should raise our level of thinking and education, so we gain an accurate understanding of AI — not just what it is, but what it can do for us. It is with that knowledge that we can begin to see the true potential of real AI.

Originally in MediaPost – MarketingDaily.

The Case For Connectivity

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ashley Herzog, vice president of product at Visto.

Like a good mass transit system, interconnectivity is the key differentiator for advertising technology these days. But for any brand embarking on a self-serve programmatic strategy – for many an agency, too – it’s not as straightforward as simply plugging services together. Challenges and delays remain in vetting potential programmatic partners, reviewing commercial terms and poring over contracts – time-consuming work that can all be for naught if the systems can’t be integrated.

One big hurdle: vendor vetting friction. Considering the current size of the Lumascape, just assessing hundreds of providers for initial fit could take an eternity. Seemingly every day a new partner enters the ad tech ecosystem, offering new or sometimes duplicative services to brands and agencies. The most persistent or notable often push their way to the front, whether or not their technology truly warrants the recognition.

What is more, marketers need sign-off from multiple people within their organization. A customer wants to assemble a group of diverse and complementary partners with experience and market equity, but putting together the puzzle can be like solving a Rubik’s cube.
Another challenge is the commercial negotiation. There is a steep adoption curve to embracing programmatic platforms’ business terms. Most will require a 12-month upfront contract with minimum spend guarantees, which have now risen to upward of 20%. Some providers require a strict and steep monthly minimum, which for a brand manager can add up to a lot of early pressure. In many cases it may take two to four months to ramp up a team to the kind of understanding or visibility to drive significant results.

Finally, there is the contract review. Legal due diligence is important – and time-consuming. I recently learned of one big publisher that took more than six months trying to get its legal team to review a programmatic ad tech contract. And I heard about one major brand that already had a data management platform and programmatic director in place, but just didn’t know where to start to build out its programmatic stack. Just getting one demand-side platform in place took it more than eight months.

These points of inertia are not just road bumps slowing down brands’ inevitable adoption of programmatic tools – they are actually suppressants discouraging many from jumping in at all. I have seen many advertisers and agencies, put off by these challenges and complexities, actually shy away from the prospect.

Programmatic buying is still a mystery to most marketers, according to the ANA, with only 23% claiming to understand how to effectively leverage programmatic strategies. This simply isn’t good enough – when brands are looking at investing millions of dollars in media spend, any mistakes are costly. It’s on the vendors to add in a layer of product onboarding and training to help alleviate this gap.

When I think about how my peers in engineering can smooth out the disconnection and inefficiencies between the core executional actions of advertising platforms from a technical standpoint, I enviously wish there were an equivalent magic wand we could wave over on the business side, to reduce the friction and uncertainty around vetting, negotiating and clearing supplier contracts.

That is why I think everyone in the industry needs to make a concerted effort to reduce the inertia and increase the simplicity with which customers can onboard themselves to a programmatic stack.

Too often, people leading brand marketing efforts are overwhelmed at the first step on the on-ramp. That can limit spending against tactics that may be extremely valuable to a brand, but are deemed too daunting to explore. So, vendors should take it upon themselves to make the best in programmatic solutions as accessible as possible.

Building the first programmatic stack is about contracts and fine print as much as it is about APIs and data. The industry needs to make these business matters as plug-and-play as the technology in the platforms it sells, reducing the time it takes to assess partners, negotiate terms and review contracts.

Follow Visto (@vistosays) and AdExchanger (@adexchanger) on Twitter.

Originally by AdExchanger

There’s More To Transparency Than Meets The Eye

Concerns over murky industry practices were simmering long before the ANA’s damning report on the lack of transparency across the advertising ecosystem, but it’s hard to overstate how much that bombshell mobilized the conversation when it was released last summer. This year, “transparency” is everywhere as an industry buzzword. Every company is implicated and, in an effort to jump on the transparency bandwagon, many will also tell you that they have a simple solution.

But simple, monolithic solutions are rarely the best ones, and the answer to opacity is not as simple as flicking the switch on a viewing ability vendor alone.

“Transparency” is not a singular checkbox to tick. To a savvy marketer, it consists of several layers of visibility and control, which necessitates adoption of a more diverse definition and approach. There are four areas all marketers should really be talking about when they think about “transparency:”


Few would argue against the idea that, for an ad to be valuable, it first must have the opportunity to be seen. So “transparency” as a synonym for “visibility” often leads marketers here as their first stop.

As the Media Rating Council (MRC) and Interactive Advertising Bureau (IAB) have issued a definition for viewable inventory, there is at least a common metric for measurement. As such, this industry viewability metric has become an important starting point for any buyer’s transparency odyssey.  However, whether or not the metric is stringent enough, or able to be imposed consistently across different screens and formats, is a different story.

With many vendors’ measurements differing, therefore making it difficult to center on a single source of truth, “viewability” is but one piece of the transparency puzzle. The important thing is for buyers to not let this fact deter them from using any metric at all. Starting with industry viewability, at least, provides a baseline against which to measure.


The second piece of the transparency puzzle is ensuring that advertising both appears on legitimate sites and is engaged by an actual human. Imagine if, in the days of face-to-face ad buying, a rogue salesman could have impersonated a premium publisher by simply wearing a fake mustache. As far-fetched as that sounds, it’s exactly what’s happening in some corners of the internet today.

A central contributor to this is called domain spoofing, where falsified websites designed to look like top-tier publishers fool ad buyers into believing they are buying space on a legitimate site when they are in fact buying from a very different, dishonest imitator.  A close cousin also causing consternation for marketers are sites or articles created to lure in visitors with false headlines and content, further escalating concerns over placement quality and brand safety. Rounding out this nefarious fraud squad are designers of software meant to imitate actions of actual web browsers, simulating the viewing and clicking of ads, generating false “bot” — or non-human — traffic and clicks.

Fraud of this kind is very different from the viewability questions raised previously as technically one of these fraudulent ads could meet the industry standard of being viewable while still clearly not delivering a valuable ad interaction. What is clear is that much of this ad scourge can be eliminated by the vigilant shining of the bright lights of transparency and measurement onto performance which, when done at a granular level, provide the information and insights to help avoid these felonious players.

Development of white- and blacklists to target ad placements to known urls, and block those know to be illegitimate, is one commonly used tactic, as is close monitoring or alerts settings around unusually high traffic or clicks, which may signal false players. Additionally, buyers should consider adoption of fraud detection and prevention services, which focus solely on exposing fraudulent actors and can act as a marketer’s sentry in the field as well as demanding more granular level reporting and monitoring from their vendor partners to catch criminal actors in the act.


Do you know how your money was spent last month? One of the major drivers behind transparency concerns is that marketers have precious little visibility as to how partners actually spend the dollars being handed to them.

Both managed service providers and tech platforms have questions to answer. By the time a publisher has put inventory into an exchange, that may be further aggregated into a supply-side platform (SSP) and then a demand-side platform (DSP), with each taking a share of their earnings.  It’s typical for up to 60% of actual media spend to get swallowed up by these intermediaries in what’s called a “tech tax.” Agencies and other service providers also have a variety of fees on top of that and, depending on how transparent those are, it can be difficult for a marketer to understand the true cost of the media bought on their behalf.

A further driving concern for advertisers regarding their vendor and agency fees is uncertainty around any potential conflict of interest around spend decisions which may be driven by discounts, rebates, internal fees and profits, or other incentives which may favor profitability versus performance.

To gain spending transparency from their partners, brands must demand visibility and performance, adopting contract terms that require ongoing reporting to ensure decision making meets the best interest of their business.


Most of the available tools tend to focus on the “what” of transparency, but what about the “why”?

If an agency moved all your video spending from one vendor to another, you would want to know when that happened, as well as the reason why. Are decisions being taken in your best interest or for the agency, and what was the rationale? If you control your company’s marketing budget, you need to have knowledge and confidence around who is making these decisions and what’s driving them to do so.

That’s why marketers must seek out solutions or relations in which partners provide transparency to all campaign changes and actions, together with the motivation. That may be a data feed or software dashboard — but it could also mean writing better evidence into soft-copy reports or regular meetings.

This is not dissimilar from financial services, where fund managers are not allowed to invest large sums for clients on authority and blind trust; they must instead provide regular reporting on their investment activities, what comprises the fund and which ones are performing and which are not as evidence. Now, it’s time advertisers were able to expect the same from their ad partners.

Transparency is one of the key challenges facing the ad industry today. But it’s almost certainly not a single-point problem, and can’t be solved by a single silver bullet.

Taken together, this new lexicon for addressing the challenges of transparency offers marketers and practitioners across the ad tech supply chain a way to create confidence and visibility together to drive the best business decisions and best performance for a marketer’s ad spend.

Originally appeared in MarketingDIVE, August 8, 2017. The article can be found HERE.

Is Consolidation Building New Walled Gardens?

The vendor ecosystem for marketing and advertising has exploded into an overwhelming mess. Just look at the latest Marketing Technology LUMAscape. Can anyone make heads or tails of it? In addition to fragmentation, there’s the issue of big platforms and their “walled gardens.” Brand and agency stakeholders are concerned about their support for third-party verification, agitated about practices for data collection and frustrated by limited understanding of how measurement is done.

Our industry has two big problems. First, there’s the confusion of too many, then the problem of too few. When it comes to the former, most will agree that an eventual segment shake-out will take place and simplify things. With the latter, we can be sure that the battle to open up the likes of Facebook and Google will go on.

Problem solved, right? Not quite. Through all this industry upheaval and uproar, there’s another risk looming on the horizon: a wave of new walled gardens that are being erected right now and right under our noses.

Last year, there were 412 mergers and acquisitions in global ad- and mar-tech, according to advisory group Results International. Each deal reduces the overall size of the industry, meaning there are fewer vendors to choose from. As this trend continues, we risk ushering in a new era of lock-in. Already this year, we’ve seen several big acquisitions, such as the Singtel/Amobee acquisition of Turn, Salesforce of Krux and Oracle of viewability metrics provider Moat.

When Oracle closed the Moat deal this past April, the company issued a fairly typical holding statement, as acquiring giants often do to calm any anxieties of the acquiree’s existing customers. This one said, “Oracle and Moat are committed to keeping Moat an open measurement and analytics platform, with deep integrations and partnerships across the entire digital publisher and ad-tech landscape.” Despite assurances, history has shown that the inevitable drive for post-acquisition synergies requires change, reduction or deprecation of original offerings and services.

Case in point, LiveRail was once a supply-side platform with a rich array of publishers plugging in. When it was acquired by Facebook in 2014, it raised prices and set very strict rules about who it wanted as customers, such as minimum-spending requirements to stay aboard. Then just two years post-purchase, Facebook shut down the last vestiges of the LiveRail service, once so loved by customers like Hulu and A+E Networks.

Now we’re in the midst of another potentially industry-disrupting deal, that between Verizon and Yahoo. We have no idea what will shake out, especially since so many ad-tech acquisitions from Yahoo’s days past remain in integration limbo. Still, it’s our assumption that we’ll see a number of existing technologies and platforms dissolved as a result of consolidation.

No deal like this is intrinsically bad. But, in many situations, the post-acquisition reality can fall far short of what was originally promised whether that’s customer data used in unexpected ways, feature sets pulled out like the proverbial rug or options that were once selling points suddenly rendered invisible or locked down.

The industry’s consolidation situation might look very different if it were being driven by smaller entities teaming up. It’s a bit like the 1980s cult classic cartoon Voltron, with the little players joining forces to fight for the best interests of mankind. But instead, we’re witnessing the creation of the next generation of walled gardens.

We as an industry need to step up to ensure the ongoing survival of a diverse targeting and data ecosystem, one that allows ad buyers and publishers to connect and integrate far and wide while using their data in the ways that best service the consumer. Clients deserve a wide range of integrations, the strongest possible connective tissue and the ability to maintain access to the unique features and benefits of their selected partners with the transparency and control to move freely to whichever combination works best.

Walls aren’t inherently bad; they’re just better when they have doors and windows.

Originally published in MediaPost MarketingDaily, June 30, 2017