Viktor Zawadzki
Region Manager DACH, Nordics, Central/Eastern Europe
MediaMath

MediaMath is one the pioneers of the programmatic revolution, having been founded by industry veterans Joe Zawadzki, Erich Wasserman, and Greg Williams in 2007. Can you share more on the initial vision of the company, and how has it evolved to where it stands today?

When MediaMath was founded ten years ago, media and Marketing were managed very differently. Most brands relied on intermediaries to trade for them and often lost efficiency, and revenue, trying to unite disparate data across multiple platforms. MediaMath’s aim was to create a more efficient approach that applied the principles of marketing science to media optimization — something that had never been done before.

In 2007, MediaMath built a platform that aligned Programmatic real-time media buying with business goals. This meant that for the first time, brands could instantly analyze all available data and determine which advertising combinations were most likely to achieve their specific goals. MediaMath began with a small team in a shoebox office delivering its promise of transparency, control, and efficiency. Now we continue to deliver on a much bigger scale — with 750 staff around the globe.

Over the years, MediaMath has diversified. Initially focused mostly on display advertising, this rapidly grew to encompass other channels such as mobile, digital out-of-home (DOOH), and TV. Today, our omnichannel method unifies all touchpoints and empowers brands to reach individuals at the ideal moment, and on the right screen, with connected one-to-one stories that tie every activity to measurable business outcomes.

In February 2017, MediaMath announced that it had been recognized by Gartner, Inc. in the latest “Magic Quadrant for Digital Marketing Hubs”. The Magic Quadrant is a market research report prepared by Gartner analysts that evaluates companies in different industries to provide an overview of a market and its trajectory and maturity.

According to eMarketer, programmatic advertising will capture over 75% of all digital display advertising in 2017. To the extent that you can share, is this consistent with the data you are seeing internally? What are some challenges in programmatic that you think we, as an industry, still need to solve before it reaches ubiquity?

Programmatic is widely recognized as the dominant ad trading mechanism for display, but we have also seen its influence stretching to new areas, such as audio, TV, print, and native. However, a siloed mentality persists across the industry, with platforms and channels still viewed as separate entities, which in turn makes it hard for brands to achieve effective omnichannel integration. Addressing this issue will require a change in mentality and approach — the industry needs to push for a new way of doing things in which omnichannel execution, smart media management, and unified data analysis combine to improve marketing strategy.

In Germany, programmatic adoption has also been hindered by transparency and quality concerns — particularly with regard to data usage and media costs — and as a result 67% of ad spend will still be non-automated advertising this year. Steps are, however, being taken to alleviate these anxieties, such as the Code of Conduct for Programmatic Advertising from the recently formed BVDW (a body that represents digital Marketers and content producers). Those who sign up to the code pledge to uphold the highest standards of transparency and quality, as well as take action to protect supply-chains and data from fraud and ad collision. In joining their number, MediaMath hopes to fuel greater use of programmatic by building trust in Germany.

Many platforms and networks claim to use sophisticated technology such as machine learning to train their algorithms, to drive further efficiency and precision for their clients. What is real machine learning, and how many of the ad platforms out there truly do have this capability?

For many brands, programmatic is still regarded as simply the automated version of traditional human media trading. Yet it takes more than that to ensure campaigns produce great results every time. Achieving consistent efficiency and precision takes smart tools with the capacity to assess vast data streams and immediately establish what’s working, what isn’t, and decide where spend should be allocated. And this is what machine learning does. Using intelligent algorithms, machine learning identifies patterns in data that enable brands to adapt spend and messaging according to what their audiences want — and the best part is that over time, machines get better at spotting those patterns and predicting what consumers will want in the future.

At present, only a few platforms are using machine learning to its full potential. IBM’s Watson for example, provides APIs for assessing message resonance and user modeling, while Microsoft’s Azure has APIs for fraud detection and big data analysis. As data-driven targeting becomes more integral to marketing success, we anticipate there will soon come a time when all campaigns are powered by machine learning.

Do you ever see a point where Adtech & Martech will converge fully? What have been some indications of this in the past few years?

Over the last few years, rising audience demand for personal, unified marketing has put increasing pressure on marketers. In the current landscape marketing platforms are still largely isolated — operating in accordance with their own standards and metrics across multiple, disjointed systems — which means it’s near-impossible for brands to run consistent, measurable, omnichannel campaigns. End-to-end platforms are already emerging that blend campaign creation, execution, and reporting; giving brands the means to provide what their audiences demand. And with 89% of companies now competing on customer experience, increased uptake of such tools — and convergence — seems inevitable.

There are clear benefits to utilizing a single, integrated platform for omni-channel marketing: consolidated reporting, optimizations across all channels & users, and frequency capping of ads served to users across devices. What would you say are some of the lesser known benefits for having a unified platform to manage all your media buying? (collaboration amongst colleagues, transparency on placements, media is more accountable, attribution, etc)

With existing, fragmented platforms it’s all too easy for insights to get stuck at various stages of the purchase funnel, making it hard for marketers to achieve effective attribution. Amalgamating all data sources — first, second, and third-party — allows marketers to understand overall performance and see the multi-channel mix as the consumer does: one cohesive whole. Such centralized intelligence enables marketers to improve targeting accuracy, conversions and the quality of the user experience by pinpointing the right moment, and message, for individuals at every touchpoint. They can also identify the activities that produce the best results, which offers a dual benefit: increasing ROI by reducing wastage, and providing a compelling business case for moving spend when dealing with clients or prospects.

What are some ways in which MediaMath clients are using your TerminalOne platform to drive performance, both on desktop and on mobile?

We have many clients who have joined us in working to realize what we like to call ‘the omnichannel vision’ via our TerminalOne platform. For instance, we partnered with Skylads to run a geo-targeting campaign ­– utilizing postal codes – for a car manufacturer with over 250 dealerships in France. We used Skylads for both the set up and performance optimization during the campaign, and the manufacturer achieved more than a 40 per cent uptake in test-drives, compared to a non-Skylad campaign. Last year, we also partnered with Skylads on two US-focused campaigns for a global restaurant chain. It was an ambitious task; the client wanted to serve the campaigns in English and Spanish across 50 states, achieve maximum reach — targeting an array of demographics and contextual segments — and deliver a set number of impressions.

Another good example is our partnership with TruSignal to enhance direct response and retargeting effectiveness for ShopStyle. Accuracy and transparency were vital, so we leveraged the clients’ data (offline and online) to find and reach individuals who were most likely to convert or engage with the brand, and filter out fraud. As a result, ShopStyle experienced an increase in conversions of 200% and reduced the cost per acquisition by 60%.

Many of the trade publications hailed private marketplaces and programmatic direct as a panacea for all marketers, where they could not only purchase their RTB but also premium, guaranteed inventory through a Demand Side Platform. How do you view the adoption of private marketplaces and programmatic direct, for both large, and smaller marketers?

The key issue for large and small marketers with today’s private marketplaces is their complexity. To begin with, they were simple trading environments that offered publishers a ‘taster’ of programmatic with all the safety of conventional direct deals. They could choose a certain portion of inventory to share with an exchange or supply-side platform, select which advertisers were permitted to bid, and set minimum floor process for each impression. It was highly controlled automation.

Nowadays it’s more complicated. There are so many ways of implementing private marketplaces that the industry has no clear definition of what they should be; what counts as good practice for one supply-side partner may be far below the standards of another, or vice versa. And for buyers and sellers that can be confusing. In an ideal world it would be great to build a version of private marketplaces that retains their current control, yet reduces complexity.

From your point of view, what are some of the biggest challenges the digital advertising industry faces today?

Modern marketers face many challenges, but for me the biggest concerns are marketing execution and standardization. Take, for example, audience segmentation; as individual interests and situations alter, so do the categories they fall into and generic segments therefore carry the risk of delivering irrelevant messaging. Marketers need instant access to constantly refreshing data to ensure optimal real-time relevance, which means they must make sure the platforms they choose are interoperable and capable of keeping consumer profiles up-to-date.

Then there’s dynamic creative. Again, the technology required for personalized and agile campaigns is there but a lack of universal standards means marketers are still nervous about embarking on their own dynamic creative strategy. If we see this year as the tenth birthday of programmatic, it’s apparent that up until now we’ve been building and developing. From here on, we need to focus on becoming masters of the tools we have created and setting clear guidelines to keep quality high.

There has been a Cambrian explosion in the sheer amount of options an advertiser or agency now has in terms of partners they can work with, from ad networks, to DSPs, to regular publishers. Do you think that this is sustainable, and how do you see the market evolving over time?

This takes us back to the main drivers behind convergence: with so many platforms and tools all functioning as separate islands, it’s difficult for advertisers and agencies to provide the connected, omnichannel experiences consumers want. Over time, we expect to see more platforms coming together and pooling resources to build bigger, better offerings that enable marketing fluidity and simplicity. It’s not enough to just focus on email marketing or just mobile display; every touchpoint is part of a single journey for consumers, and marketers need technology that can keep up.

Any thoughts on header bidding?

When we talk about header bidding, most conversations emphasize the benefits for sellers: it enables publishers to open up inventory to all demand sources before calling their ad server, thus driving competition and yield optimization. But it’s also important to note that header bidding is transformational for programmatic buyers.

Typically, exchange-based bidding gives buyers access to a small portion of publisher inventory, but header bidding provides access to all available inventory. This means that for the first time, programmatic buyers can see premium placements and those usually offered to exchanges at the same time, rather waiting until after direct sold deals have taken place. Buyers get to see every placement against every user and pick the best inventory for their specific campaign, increasing targeting accuracy engagement. While this increased competition might result in higher prices, it’s also offering valuable impressions that are worth every cent.

What are some ways in which a marketer can use a DSP such as TerminalOne, to target in a hyperlocal fashion, and be able to attribute offline purchases to online influence? 

Hyperlocal targeting is skyrocketing — with location-targeted mobile revenue in the US alone due to hit $18.2 billion by 2019, and there’s one very good reason why: by adapting messages to where consumers are and what they’re doing, marketers can use contextual relevance to capture the interest of the ‘always-on’ mobile consumer. In TerminalOne, we combine the three core areas of location insight: historical, real-time, location measurement. This allows marketers to identify and engage the most appropriate user, at the best time and in the ideal place, as well as quantifying the success of their activities by tracing the links between online and offline activity.

Lastly, what is your take on the future of programmatic advertising? 

Globally, I see programmatic continuing its rise to the top of the digital advertising tree: taking an increasingly large share of marketing budgets, bringing unparalleled efficiency to ad trading and exploring new territories — such as TV and audio. But success brings its own challenges and aside from the issues we have discussed around the need for unified platforms to enable one-to-one marketing, and clearer standards to ensure consistency, there will also be the challenge of availability. With programmatic becoming the norm, competition for inventory will be higher and this will require a redefinition of automated access — perhaps driving greater adoption of more flexible trading methods like header bidding.

MediaMath (mediamath.com) is a global technology company that is leading the movement to revolutionize traditional marketing and drive transformative results for marketers through its TerminalOne Marketing Operating System™. A pioneer in the industry introducing the first Demand-Side Platform (DSP) with the company’s founding in 2007, MediaMath is the only company of its kind to empower marketers with an extensible, open platform to unleash the power of goal-based marketing at scale, transparently across the enterprise.

T1 activates data, automates execution, and optimizes interactions across all addressable media, delivering superior performance, transparency, and control to all marketers and better, more individualized experiences for consumers.

MediaMath, which has experienced triple-digit year-over-year growth since inception, has a seasoned management team leading 15 global locations across five continents. Key clients include every major agency holding company, operating agencies, and top brands across verticals.

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