“Data is central to everything we do in programmatic.”
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How Coca-Cola Found Its Best Customers in Mexico Using the Triumvirate Model and an Integrated DSP + DMP Approach
Coca-Cola, one of the biggest CPG brands in the world, worked towards creating audience segments so the brand could better understand its customers.
With 13 sub-brands active in the market—each with its own goals, segmentation needs and investment capabilities— Coca-Cola wanted to better understand its brand affinity and drive sales in the region. Coca-Cola ultimately wanted to deliver more relevant content and adapt marketing based on what their customers liked, the content they consumed and online and offline locations. At the time, they were not taking advantage of programmatic and instead were doing direct buys.
In March 2015, MediaCom developed the concept of a “Precision with Scale” campaign, in which they partnered with MediaMath to activate the technology company’s integrated demand-side and data-management platforms. In the campaign, MediaCom recommended Coca-Cola shift more budget to programmatic and actively work towards creating audience segments so the brand could better understand its customers. Using a two-phased approach, Coca-Cola was able to achieve buying efficiency of more than 7 million Mexican pesos vs. non-programmatic buying in addition to other impactful results.
To learn more about how this brand, agency and tech provider partnership delivered the right solution for Coca-Cola, watch our video interview and download our full case study here.
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Marketing Wiki: Machine Learning
Machine learning describes the practice of a computer adapting without having to be programmed. The more data that’s fed into the computer program, the smarter it gets. It can make better predictions and continuously evolve without the computer engineer having to make adjustments to the code based on the outputs. Machine learning influences lots of things in our world today, from internet search to voice recognition software.
Machine learning also plays a critical role in marketing!
How does ML learn to improve its performance through practice? As the program gains “practice” with the task, it gets better over time, much like how we humans learn to get better at tasks with experience. For example, an ML program can learn to recognize pictures of cats when shown a sufficiently large number of examples of pictures of “cat” and “not cat.” Or a real-time bidding (RTB) system can learn to predict users’ propensity to convert (i.e. make a purchase) when exposed to an ad, after observing a large number of historical examples of situations where users converted or not.
Why can’t humans do the job? Some things are just outside of our human capabilities, like trying to predict which types of users in what contexts will convert when exposed to ads. Marketing folks might have intuition about what conditions lead to more conversions. But the problem is these intuition-guided rules can be wrong and incomplete. The only way to come up with the right rules is to comb through millions of examples of users converting or not and extract patterns from these, which is precisely what an ML system can do. Such pattern extraction is beyond the capabilities of humans.
So does this mean ML will take our jobs? No. In fact, machine learning is increasing the number of job opportunities in the field of Data Science. Plus, humans will always be needed to understand the goals and motivations of their clients and the nuances between them.
What’s an example of how an ML program works? Say you’re an ad campaign for a new shoe on the New York Times website. Every time a user visits the website, an ad-serving opportunity arises, and given the features of the ad opportunity (such as time, user demographics, location, browser type, etc.). You want to be able to predict the chance of the user clicking on the ad based on previous data about the anonymous user. A ML program can improve its performance at some task after being trained on a sufficiently large amount of data, without explicit instructions given by a human. And with 500 billion ad opportunities every day, the machines are getting really smart, really fast!
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The Bloomberg of Advertising
The following interview was conducted by Jair Lopez for the publication Expansión while our CEO Joe Zawadzki was in Mexico for the IAB Conecta event earlier this year. The interview has been translated from Spanish.
Joe Zawadzki left the world of finance to dedicate his life to advertising and what he achieved was to create something that marketing desired: quantitative analysis, a dynamic market based on data and the use of technology.
His arrival to the marketing industry was almost accidental. The Harvard graduate began his career as an investment director in New York, a role that allowed him to develop his expertise in the world of numbers and calculations.
After a decade of representing agencies and brands at Fortune 500 companies, he visualized that advertisers lacked what other sectors, such as finance, were already adopting: technology, data, analysis and best practices for applying all three.
Zawadzki revolutionized the marketing industry: he created the first DSP platform that integrated an algorithm that allows advertisers to buy impressions in the best places, in order to achieve great conversions. In summary, he gave intelligence to the sector by making better decisions. Among his contributions we can find his TerminalOne DSP, similar to Bloomberg, that leverages advanced machine learning to enable marketers to make the best advertising decisions.
In an interview with Expansión, MediaMath’s CEO discusses how technology has changed the industry and his perspective for the next decade. For Zawadzki, technology will be a benefit for brands or agencies who adopt it, and for those who don’t, it will be a threat.
EXPANSION: How has technology changed advertising?
Joe: Software is changing everything. Ten years ago, the marketing industry began to develop an interest in technology. One of the examples is programmatic advertising, that merged two concepts, technology and marketing, and how we automate processes for having millions of impressions in phones, tablets, screens or audio platforms, like Spotify.
Today, the software allows marketers or agencies to press a button and know on which screens they must be appear to reach target consumers.
E: So, what is the future of advertising?
JZ: The future is programmatic advertising, I am sure about that. I believe that, in 10 years, most cases will be based on content and on the relation between a brand and the customer. The technology is there, consumers are demanding it and so are the brands. It will be the industry’s responsibility to shape it.
E: Why is it the future?
JZ: Because it really serves business goals. In the past, what programmatic and technology can do now wasn’t available. You have metrics about how many visitors, clicks, if someone engaged with the advertisement in real-time. The first step is to set goals and, second, to analyze what is relevant and the key metrics necessary to know if the campaign is working or if we should change it in real-time.
E: Today, is it impacting brands and advertisers?
JZ: We have clients that launch products using programmatic advertising only. (In the future) it will be 10 times more than that. Every piece of advertising will be personalized for the user.
E: Is technology a threat for agencies and brands?
JZ: I believe that all traditional media will move into digital. Think about television; people are moving towards on-demand TV. Think of smart phones that didn’t exist 10 years ago; tablets, six years ago; and social media, such as Snapchat, two years ago. Customers are changing their behavior, and advertisers are thinking about how to deal with it. It will be a threat if you don’t respond well to those changes.
E: What other technologies will be relevant in the future?
JZ: Definitely, artificial intelligence (AI) and machine learning, but I think that we are in early stages in relation to marketing. It’s going to take some time for people to feel comfortable with artificial intelligence and automation.
E: How will these tools be used in advertising?
JZ: If you think about it, the objective of advertisers is to create a connection with the consumer. What he/she cares about and how to identify the product that he/she desires. What is he/she watching? Artificial intelligence will solve the difficulties of decision making. It will be the same as when you go to a store where you bought a blue shirt and the salesperson offers you a tie that makes a match. The user will be amazed, and he/she will buy again.
E: What do you think about the use of technology in the advertising market in Mexico?
JZ: That is something that excites me. A lot of things started in the US and were quickly adopted in other regions, like the UK. But Mexico is doing pretty well, as you are seeing this transformative opportunity. In the last few months, we have seen the beginning of the adoption of new practices and the opportunity to be innovative, not just in advertising, but also in general.
E: How relevant is the region and the Mexican market for MediaMath?
JZ: The market is making some great investments focused on what we are doing, and Mexico, definitely, leads the LATAM market, the fastest-growing region. The market is investing, and we see great adoption of the technology and programmatic advertising.
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Happy Consumers Lead To Successful Marketers: MediaMath CMO
This byline originally appeared on BandT.
Whether you’re an agency looking to constantly create compelling content which won’t force people to switch off, move away, ignore or, even worse, block your clients’ ads, or a publisher looking to maximise the value of your inventory, the role of programmatic—automation of process and decisioning through technology –doesn’t change.
It is to deliver the right content to the right people in a fast and seamless fashion.
Today, consumers are voting with a click of their computer mouse to avoid disruptive, annoying or irrelevant advertising, and advertisers and publishers need to answer their call for a better, more relevant experience. According to industry predictions, $41 billion dollars’ worth of ads will be blocked in 2016[1].
That suggests, loud and clear, that people are not overwhelmingly happy with the way that ads are delivered, or the content that they are being presented with in those ads.
It should be a sharp wake-up call to brands and their agencies that consumers want more—from both the people that are making and distributing ads, and from the media companies through which ads are delivered.
The answer is, on one hand, beguilingly simple: the data and technology needed to deliver great marketing experiences is, today, there for the taking.
But how to take best advantage of it is the real question: how to pull together the right data, analysed in the right way, executed in an integrated fashion across channels, with dynamically optimised messaging and creative as user needs and states change?
Let’s look at the component parts in more detail.
Better consumer insights come with clearer intelligence on your audiences, and that can only be done by better utilising the resources at hand. There is a host of valuable information at our fingertips, spread across all the data touchpoints in a consumer’s journey, from web browsing history, social media, customer databases, to even hyper-local targeting.
The power now lies with marketers to harness that information, and utilise it in a way that delivers a more personal experience to potential customers.
A robust data management platform integrated with an omnichannel media buying platform can help you better onboard, segment, analyse and activate data—whether it be yours (first-party), a partner’s (second-party) or a third-party’s data asset— across channels and devices. The ability to activate data right in media enables you to link audience profile data with media behaviour for smarter, better informed planning and buying.
Now that we have the power to learn more about our target audiences and find them across channels, we need to focus on creating ad experiences that are adaptive to changing consumer needs and states across the purchase lifecycle.
An omnichannel media platform enables holistic frequency management that ensures users aren’t bombarded daily with a high cadence of ads, whether it is the same ad over and over or a host of disconnected messages all from the same advertiser.
It also enables better ad sequencing to help marketers tell a story across channels that evolves as the user does; for example, by creating an emotional connection through a video ad that is followed with a related call to action in a display ad.
Consumers are already voting with a click of their computer mouse to avoid disruptive advertising, and advertisers and publishers need to answer their call for better, more relevant experiences. As marketers, it is essential that we take on the responsibility of delivering a better consumer experience.
If we do, we will be rewarded in the form of happier, more engaged, more loyal customers and, in turn, positive long-term business results. If we don’t, we risk losing consumer loyalty and trust and ceding ground to our savvier competitors.
The capabilities now available through programmatic marketing provide the foundation for making the entire advertising ecosystem a more enjoyable place to be. It’s up to you what you do with them.
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The Reign of Programmatic
“It no longer makes economic sense to send a message to the many in hopes of persuading the few.”—Lawrence Light, former CMO, McDonald’s
Marketers are excited by the opportunities to interact with consumers across channels and devices. Increasingly, they are realizing the power of programmatic—the automation of process and decisions, driven by data and powered through machines, to deliver business outcomes. But in a landscape like Brazil, with economic uncertainties and lack of market maturity, how do marketers start to harness the full power of technology-enabled media buying?
In August, our CMO Joanna O’Connell presented on “The Reign of Programmatic” at the IAB Brazil Adtech and Data Summit. The crux of her speech was that Brazil can open itself up to the same transformation that allowed programmatic to become mainstream in the US. Namely, it was the areas of media, data, intelligence, talent and platforms that opened the door to the buy-side shifting from publisher-driven to marketer-driven, from guesses to true audience targeting and from siloed to unified media execution. To learn more about how O’Connell recommends Brazil take advantage of the programmatic opportunity, watch the full video of her presentation here.
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The Evolution of AdTech: Photographs vs. Novels
With the increasing speed of data processing and the decreasing cost of data storage, the adtech industry is evolving to improve the efficiency and effectiveness of programmatic advertising for all data-driven advertisers. Real-time bidding has led more and more advertisers to leverage DSPs to manage campaigns and deliver media to the right audience right now—with great success—but what’s missing is the context to deliver the right media at the right time.
Imagine a photograph of a woman, between 25-34 years old, enjoying a picnic in Boston Common. We see green grass around her while she sits on a red and white picnic blanket. She’s wearing a blue plaid shirtdress from L.L. Bean, elastic-strap wedges from Talbots, Ray-Ban sunglasses and a necklace from BirchBox.
The photograph shows her with her two friends, and they’re enjoying a bottle of mid-range Cabernet Sauvignon from Seven Hills winery in Walla Walla, Washington, along with fine cheeses from Vermont Shepherd Cheese and Cyprus Grove, all of which she purchased a few hours earlier. Her iPhone is sitting next to her playing background music on Spotify.
Based on this photograph, we know quite a bit about this woman. We can start to tell a story about who she is as a consumer, which kinds of products she might prefer based on her recent purchases, and because we know a few things about her demographics, we can make broader statements about what she might or might not like.
This is the kind of information advertisers have in a demand-side platform, and it is incredibly valuable because it enables targeting in a way that was never previously accessible before RTB. This data unlocks the capability to target the right audience right now.
But behind every person in a photograph there is a much deeper story to be told, a story that can never be captured in a single, point-in-time photograph. The photograph grows stale over time as the woman continues doing more things, changes preferences and learns about new products she loves. Her full story takes up not just a photograph but an entire book, and provides the kind of next-level context that enables much sharper analytics, predictive modeling and more effective digital outreach.
This book is MediaMath’s Audience Platform (think DMP). Because of industry-leading event-level storage, we have more story to tell about an audience. The figurative “book” of MediaMath’s Audience Platform comes with hundreds of new-book-smell pages of behaviors and intentions, and begins with the tools needed to find what you’re looking for, a table of contents.
By searching the table of contents for long-term behaviors, we may learn that our erstwhile picnicker holds a deep appreciation for vintage furniture from Restoration Hardware and, in fact, that’s the only kind of furniture she’s ever purchased. As we continue reading the Audience Platform book, we learn that she uses AirBnB for a trip around Easter every year, that she recently purchased a wedding dress from Maggie Sottero and that she always responds to half-off Labor Day specials from J. Crew.
We may also learn that there are many people who are very similar to her, and many who are not, and we can choose which people to speak to with which message, on which device, at a time relative to her behaviors and intentions. With features like real-time dynamic segmentation, custom attributes, no-spend campaign performance forecasting and the ability to reach customers across devices and by location, advertisers are in control of their digital engagement now more than ever.
In short, MediaMath’s Audience Platform stores and provides access to event-level data that, in aggregate, informs statistical models that will make advertising more effective and more efficient. The DSP “photograph” provides the data to target the right audience right now, while MediaMath’s Audience Platform “book” provides the data to target the right audience at the right time. Advertisers who truly understand the connections between their data, their customers and their brand are already seeing positive outcomes.
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Optimizing Ad-tech And Mar-tech Channels: Near-Term Trends
This byline originally appeared on MediaPost.
The convergence of ad-tech and mar-tech has, in theory, been happening for years. We can now technologically hook together systems powering paid (ad-tech) and owned (mar-tech) channels to deliver more relevant, seamless marketing experiences across these channels.
But just because these integration points now exist doesn’t mean that marketers are taking full advantage of them. To break down the barriers between mar-tech and ad-tech inside their own organizations, marketers need to break through the challenges and misconceptions that are keeping them from taking the steps toward adoption.
Here are a few trends I expect to see as we head into 2017 that will get marketers closer to the future state of true paid and owned convergence.
Consumer demand for more personalized experiences will separate leaders from laggards
The flattening of commerce and long tail—an e-commerce concept where the internet has enabled super-specific and special interest items to be available for sale at scale by pretty much anyone (think Etsy)—has magnified the importance of customer experience. Pre-ecommerce, if you were the only store in town selling collector comic books, for example, it didn’t matter if your customers had a terrible experience because there was nowhere else for them to get their comics. Now, the consumer has a multitude of options and, with that, all the leverage in evaluating everything from on-demand services to products at the right price point.
So, ecommerce has leveled the playing field from a competitive standpoint, highlighting customer experience as a key area to differentiate and a very dangerous area in which to fail.
Mar-tech and ad-tech convergence helps in a number of ways. First, it offers an ability to see and better understand customer behaviors across a broader range of marketing touchpoints through a single, 360-degree view of them. Second, it improves the delivery of more relevant messaging, at scale, to improve business outcomes and better delight these customers—meaning you’ll stand a better chance of reaching, and converting, consumers with your specific offer and value prop.
Bottom’s up and top down will be the next evolutionary steps
Part of the reason more brands aren’t extending, for example, email campaigns (via mar-tech) across paid media (via ad-tech, such as in display or video) is because there is no single role or team inside most marketing organizations to do it. There are still huge organizational challenges—the paid media and owned media teams very often don’t talk to each other, for one—and it’s unclear who owns what.
Change will happen from the bottom up. The paid media team will increasingly realize that spending acquisition dollars on recent purchasers is a waste of money and will want to suppress those purchasers from media campaigns. How to do it? Engage the CRM team, who owns customer data. Gap bridged. And when people like this see little moments of success, like improved conversion rates or better efficiency of media spend, they will use those wins as a springboard to try more stuff.
Marketers pursuing a DMP strategy, for example, will find it necessary to have conversations with their peers across their organization—in CRM, legal, analytics, IT– around where data lives throughout the organization.
It will also come from the top down. Nothing moves an organization faster than executive support for and leadership through change. You’ll see more leaders at large brands pushing customer centricity as a business imperative.
Easier cross-implementation of technologies
Managing email used to be really clunky. Now it’s seamless. As technologies in the advertising ecosystem continue to mature, becoming increasingly smart, user-friendly and expansive in scope, there will be more time and energy devoted to cross-pollination across those worlds. It’s a natural next step. As a live example, we will see more built-in functionality inside of mar-tech platforms that enable email marketers, who don’t naturally live in the world of programmatic, to extend email campaigns to paid media easily through a single UI.
Identity will become a foundation for executing campaigns across mar-tech and ad-tech
If you’re going to have a relationship with a consumer, you have to know that it’s that consumer wherever that consumer is, regardless of channel, ad format or device. This means identity must become the basis from which you build your marketing plans and inform how you interact with your consumers. Identity comes into play with mar-tech and ad-tech because the more you know about a consumer, the smarter your conversations with them will be. You can start a conversation with a user in email, and continue it in display, knowing their shopping and content consumption behavior across all the devices they use. Marketers will see improvements both in their ability to accurately measure their marketing efforts that span channels and devices, and in their ability to effectively target across them. As a practical example, having a unified view of identity eliminates excess frequency against the same users seen across browsers and devices (where, in a traditional cookie-based world, they would not be seen as a single user).
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Talking Cross-Device at Advertising Week
Now that we consume content across channels and devices, marketers have had to re-strategize how they tell their brand stories. What is the future of how we deliver content across these enviornments?
LinkedIn Hub host Maha Awad sat down with our own Philipp Tsipman, VP of our ConnectedID cross-device solution, at Advertising Week in October to learn about how technology has evolved to enable marketers to tell these more connected stories. Tsipman mentioned that 2016 has been exciting as the technology to enable omnichannel storytelling across channels and devices has eventuated after years of hype.
“You have a good story. You needed the solution to execute on it,” he said. Now, Tsipman said, it’s about looking at the data anad the consumer path shoppers are taking to purchase your products to help shape your story.
Watch the full video interview here.
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Improving Programmatic Adoption in Germany with Better Data Transparency Guidelines
Transparency and quality have never been more important in the advertising ecosystem. From ensuring the responsible use of data to providing clear information around the costs and execution of media buying, the industry on the whole is taking a deeper look at how all players can create and adhere to standards that strengthen the programmatic advertising environment.
In Germany, the industry has looked to build trust on the buy side through the newly announced BVDW—an organization that represents the interests of companies in the field of interactive marketing, digital content and interactive added value—Code of Conduct for Programmatic Advertising.
This initiative by the BVDW’s internal working group “Fokusgruppe Programmatic Advertising” came about as the result of a common understanding that the adoption of programmatic in Germany has been slow due to quality and transparency concerns by advertisers and agencies. The Code provides a way for participating companies to help the nascent programmatic German market ensure a healthy and sustainable advertising ecosystem.
MediaMath has been an active participant in Fokusgruppe Programmatic Advertising throughout 2016 and has answered the BVDW’s call for marketers, publishers, sell-side platforms, demand-side platforms and data providers to sign the Code of Conduct. In signing the Code, MediaMath has pledged compliance in all applicable categories: transparency and quality of the advertising environment, supply chain and data; viewability; and appropriate safeguards around ad collision, ad fraud, audience fraud, cookie dropping and data leakage.
MediaMath’s signing of the BVDW Code of Conduct is another way that MediaMath is delivering on its promise to ensure quality, transparency and brand and consumer safety across the marketing landscape. MediaMath has undergone the rigorous technical and procedural scrutiny required to become a certified member of prominent industry organizations, codes and frameworks, including the European Digital Advertising Alliance (EDAA) and its counterparts in the US (DAA) and Canada (DAAC); the Direct Marketing Association in the US and the UK; the Interactive Advertising Bureau (IAB) in Australia, Brazil, Canada, Europe, Germany, Italy, Mexico, Singapore, the US and the UK; and the Network Advertising Initiative (NAI). MediaMath is certified compliant with The Trustworthy Accountability Group (TAG), a distinguishing symbol of MediaMath’s commitment to conducting business in a transparent manner across the digital advertising supply chain.