Pandora Debuts Programmatic Audio Ads

February 20, 2018 — by Amarita Bansal0


This article originally appears on AdAge

Pandora said Tuesday that it will now offer its audio inventory programmatically through popular demand-side platforms such as MediaMath, The Trade Desk and AdsWizz.

Pandora is the last of the three major digital music streaming platforms to offer audio ads through automation, but the company says it brings a significantly larger audience to the table. The move also comes at a time when digital audio is capturing more ad dollars compared to previous years.

Through the first six months of 2017, digital audio grew 42 percent year-over-year to $603 million, and of that, $448 million came from mobile, according to the Interactive Advertising Bureau’s latest digital ad revenue report.

Chris Record, VP or revenue operations at Pandora, says about 85 percent of Pandora’s purchased inventory comes from mobile.

Rivals Spotify and iHeartRadio began offering audio ads through programmatic late last year, but Pandora claims it can reach more users than either of its competitors. Pandora has some 92 million monthly active users on its platform, according to ComScore, while Spotify has 89 million. IHeartRadio, meanwhile, has roughly 30 million.

Record says that competitors like Spotify have users that mainly pay for music. ‘We are differentiated through scale,” he says.

Meanwhile, car manufacturer Volkswagen is among “six or 10” launch partners, Pandora says.

“Cars and music both have a way of eliciting an emotional connection,” Jim Zabel, senior VP of marketing at Volkswagen, said in an emailed statement to Ad Age. “We’re always looking to effectively reach driving consumers in ways that move them while maintaining scale in a brand-safe environment.”

The Volkswagen campaign was facilitated by PHD, an Omnicom Media Group agency and Volkswagen’s media agency of record, Pandora says.

Although Pandora already offers its audio inventory “programmatically” through broadcast planning and buying platforms MediaOcean and Strata, those are mainly used by broadcast buyers, the company says. Through its recent integration with outfits like The Trade Desk, though, the company will be able to sell its audio ads in similar fashion to how it sells video or display with agencies.

Still, despite Pandora’s broader reach, marketers appear more interested in advertising on Spotify.

According to a series of studies published by RBC Capital Markets in partnership with Ad Age, marketers were most interested in advertising on Instagram (64 percent), followed by Amazon (43 percent) and then Spotify (40 percent). Pandora was not ranked.


Why I Joined MediaMath

February 16, 2018 — by Carlos Sandrea0


I joined MediaMath in early 2018 after a one-year sabbatical. It was great. The perfect time to decompress, build stronger bonds with my loved ones, and reflect on my life accomplishments. Unfortunately, good things always come in short supply, and a few months in, a question kept creeping in my head: what was my next career move?

Thus, I started looking for a new job. Between the kid’s soccer practice, and the piano recitals, I developed criteria to evaluate job opportunities:

1) I wanted a company on growth mode, global focus, and with a clear and attainable vision.
2) I wanted to be part of a product organization. While I was not necessarily looking to be a product manager, I wanted to leverage my experience in this area.
3) Lastly, I wanted a company with a smart, solid and diverse team of leaders and peers. I wanted a company with people I could have fun with, learn from, and value what I could bring.

Fast forward to late 2017 when I get a call from a recruiter working on behalf of MediaMath. While MediaMath checked most my boxes, one was still unclear: what’s the team like? How did they operate, and what kind of work environment would I expect from them? The answers to these questions came surprisingly fast.

Over the course of several weeks, I interviewed both in person and over the phone with many people at MediaMath. Everyone I met were really friendly but at the same time they didn’t mince words. There was a common trait among them, a drive. They knew what they wanted, and more importantly, they knew what they needed help with. And while they didn’t always have answers to my questions, they were always open and humble. And boy, do they moved fast. Soon enough, and in the midst of the holiday season I had a verbal offer, which I gladly accepted.

So, to answer your question. Why did I join MediaMath? The quick answer: its people.

Looking for a new job is never easy. A friend once told me that finding a job is like buying a car. You research the car you want, you test drive it, you may even get the best deal, and chances are…you’re buying it! But in the end, you’ll never know whether or not you bought a lemon until you have it for a while. To me, it is the people you work and spend so much time with that makes all the difference at work. Five weeks in, I am glad to report that things are going very, very well.

No surprises, no regrets.


What Do You Love About Marketing?

February 14, 2018 — by Lauren Fritsky0


Valentine’s Day. It makes some people go “Aww” and others go “Ugh.” Regardless of how you feel about the holiday, we decided to use it as a force for good by asking some of our MediaMathers what they love about this crazy little thing called marketing—whether it’s the work we do as marketers or the ads we see as consumers—on which we’re hooked.

Our industry is unique in that we get to wake up every day and solve complex problems that will have immediate and long-term impact. We get to design, create, distribute, market and engage with clients who care as deeply as we do about being a part of something bigger than themselves.– Elise James-Decruise, VP, L&D, and Programmatic Education

I love having a part in the creation of a solution which enables personalized messaging to consumers that allows them to discover content and products that they never knew existed or that they didn’t know they needed.– Kyle Turner, Senior Manager, Inventory Quality

I love marketing that is personalized and relevant to me. I want to know when my favorite artist is coming to NY, that my favorite brand is on sale, that a new product was released that I didn’t know I had to have.– Sara Skrmetti, Senior Director, Channel Solutions

I love when a commercial makes me laugh or cry or anything in between.– Avi Spivack, Global VP, Solution Engineering

The industry is diverging from aged classifications such as “consumers,” “targets,” “in-market segments,” to recognize/remember and embrace that we’re people and not pixels or hashed IDs. I love being a part of this shift and helping brands build programs where people are core.– Rebecca Sharpe, Director, Programmatic Strategy & Optimization

Marketing takes many forms. The forms I love are data-driven, smart, predictive and reach many audiences with experience that informs and inspires. As a self-proclaimed Pythagorean, I believe digital engagement in support of business goals or awareness should be rooted in reasonable understanding of interaction between measured audience interests and predicted outcomes. The fun part of marketing is creating the tools that deliver moving experiences to the people who find them moving.– John Slocum, VP, DMP

Make sure to head over to our Twitter feed today, where our CMO/CSO Dan Rosenberg is talking about “Making Marketing People Love” with the #lovemarketing hashtag.


Inside the System: Humans in the AI Loop

February 13, 2018 — by Amarita Bansal0


This article originally appeared in DMN News. 

If the future was perfect, every digital marketer would install an AI system, flip a switch, and have it operate on auto-pilot. It would manage every step in the customer journey, from the first web site visit to the final mouse click to buy.

Well, we’re living in that future, and it ain’t perfect. AI is just starting to progress from buzz word to mainstream. Consultants and practitioners agree that you need to keep a human in the loop. The question is where in the loop do you place the human: the beginning, the middle, the end, or throughout?

The human needs to touch the system
Salesforce’s Einstein has been around since 2016, focused on delivering AI for customer resource management, offering predictive and recommended advice to its human users who want to convert prospects into customers.

Users “are coming to us with a business problem,” said Allison Witherspoon, director of product marketing for Salesforce Einstein. They need to augment their decision making, using tools like lead scoring and engagement scoring to rate prospects. Only that work is automated by the AI, which can be adjusted to suit user need. Witherspoon referred to this as “augmented” rather than “artificial” intelligence.

So where is the human? At the end, as the user, but also in front, as the customer. The AI is “watching the customer interact” — say with an e-mail message, explained Meghann York, director of product marketing at Salesforce. Customers provide input into Einstein as they interact with web pages and pitched messages, which the system analyzes. This should yield a recommendation the marketer to take an action, but more importantly, telling the user why a particular recommendation is best, Witherspoon added.

“Humans are a bit unpredictable,” York added. “The model will learn and follow it.”
The human needs to tap the system

Still the system can make mistakes.

AI depends on machine learning, but there comes point where the system “tapers off” for lack of new data to learn from.  Cosmas Wong is founder and CEO at Grey Jean Technologies: “Once it tapers off, you see if there is a need for it be returned [to its functioning state],” he said. “You look at it once very two weeks,” he said, tracking the process of how the system continues to learn.

Sometimes errors occur for lack of data. Wong offered one example of an affinity engine powered by AI that would pick articles for people to read, based on reader profiles and past preferences. The system tried to approximate a selection by trying pick an article for a person whose profile mostly resembled that of another person. “It looped back to itself,” he said. The solution was to fix the algorithm to filter out the false choice. “A human being has to do it.”

“AI is intelligent, but it is still going to be artificial,” Wong pointed out. A human must always be kept in the AI loop “to determine if the output is what we want.”

The human needs to teach the system

An AI system is only as good as the data you use to teach it. “People often overlook this step,” noted Marius Kierski, CEO  for Sigmoidal, an AI consulting firm. Even when an AI system starts out with a good, curated data set, it will acquire more uncurated data as it “learns”, but that extra data dilutes the quality of that starter set, leading to “catastrophic forgetting,” Kierski explained. “If you just let it go, you will lose the added value of a person looking at the data.”

Which leads to another concept: confidence. Once AI is trained on a data set, how confident will that system be that it is making the correct decision? The system should flag a decision where it is unsure and “alert the human to help make the decision,” he said. “The system refuses to make a decision where its confidence is low.”

Next: Doubting the system

The human needs to doubt the system

AI learns from data compiled by humans. So won’t the data be as flawed as the people who compile it?

“Artificial intelligence is a tool…It is not intended to stand on its own.” said Risto Miikkulainen, VP for research at Sentient Technologies and professor of computer science at University of Texas, Austin. “The data determines what the behavior will be. The big challenge is that sometimes there are hidden biases in the data you don’t want there.” he said.

“You don’t want the AI to propagate a bias…[but] if you are conscious about it. You can fix it,” Miikkulainen added.  Humans can mitigate any instances of bias once detected, to avoid offending users, or worse, customers. The outcome should be a system that changes over time with adjustments. The commercial example Miikkulainen gave is a web site that self-adjusts to suit the users accessing it. That, of course, is a personalization approach — which would hopefully increase the likelihood of conversions or other desired outcome.

The human needs to “be” the system

So where in the loop do you put the human? Everywhere.

“[I]t is always prudent to set up an ongoing performance-monitoring system that shows how predictive performance metrics are evolving over time.” said Prasad Chalasani, Chief Scientist at MediaMath. “Unusual changes in these metrics do require a human to intervene and see whether there are any data anomalies, or unforeseen edge cases. Depending on the domain, such human intervention can occur daily or weekly.”

A true AI system learns as it goes, self-adjusting as it receives new data. That also raises the risk that data and operations can interact in unexpected ways, producing unexpected results. “Usually it is easy to figure out why, but occasionally figuring out the root cause can take a day or more.” Chalasani said.

Thankfully, online marketing is a realm where AI mistakes can be obnoxious, but not fatal. “In some areas such as speech recognition, we are already seeing nearly fully autonomous AI.” Chalasani said. “In other areas, especially where life-and- death decisions are involved (e.g. in military or medical domains), it is doubtful we can completely eliminate humans from the loop.”


Why Marketers Need to Fear Zombie Sites

October 31, 2017 — by Kyle Turner0


This Halloween, there’s a new threat that will send a chill up every marketer’s spine. In a scary year, a new threat has emerged to claim unsuspecting victims: zombie sites.

As detailed in a recent BuzzFeed story, a new type of ad fraud may have bilked as much as $20 million from more than 100 brands. The scam employed a redirect code that worked without the input of a human or bot. “Once caught in this web of redirects, the sites show a constant stream of video ads that are often barely interrupted by actual editorial content,” the article stated.

Marketers should be concerned, but such fraud is hardly unexpected. Kristin Lemkau, CMO for JPMorgan Chase, recently predicted that ad fraud losses would hit $16.4 billion this year, up from $7.2 billion last year. (Other estimates say things are actually improving. The ANA and WhiteOps predict that ad fraud could fall to $6.5 billion this year.) Such losses illustrate that digital advertising is prey for thieves. Marketers that hope to successfully navigate this environment need to work with a trusted partner.

A closer look at zombie sites

Zombie sites are made possible by a long-tail approach to digital media buying. There’s nothing wrong in theory to taking this approach. In practice though it’s rife for tampering.

In this case, fraudsters drew programmatic ad buys by snagging domains like and and then filling the sites with plagiarized and loosely rewritten content.

Fraud protection firm Pixalate dubbed those “zombie sites” because they were unlikely to draw an actual human audience on their own. BuzzFeed traced the sites to a publisher in Nashville who denied he was engaging in fraudulent activity.

More to come?

Unfortunately, it’s unlikely that we have seen the last of zombie sites. As long as there is money to be made by tricking auction sites into buying garbage sites, advertisers will continue to find that what seems to be a good CPM rate is bolstered by junky sites that do nothing for the brand but waste money. Solving the problem means accepting a higher CPM with the knowledge that ads will actually be placed in front of real customers in brand-safe environments.

That’s where firms like MediaMath come in. Legitimate ad tech firms realize that the industry is in the grips of a fraud crisis. While law enforcement agencies can curtail some fraudulent activity, they often find that they’re playing Whac-A-Mole — as soon as they get one publisher to cease and desist, another one or two spring up.

“For advertisers then the only way forward is to work with trusted partners that offer placement with A-list publishers and can identify more brand-safe and legitimate long-tail content. At MediaMath, we take our role as a trusted partner seriously. That’s why we started offering proactive credits for brand safety issues this year.

That’s why marketers don’t need to tremble at the thought of wasting money on zombie sites this year. If you work with solid vendors then you can expect more treats and fewer tricks as well.



Even in the Programmatic Business, Face-to-Face Meetings are Essential

October 10, 2017 — by Lewis Rothkopf0


During the ad industry’s busy “events season” when there’s a flurry of industry events all over the globe, I had a thought: Why are we all traveling at great expense when we could have stayed home?

After all, programmatic advertising was designed to automate aspects of buying and selling media that used to be carried out by humans. Why is the human touch so important to our business of all businesses?

The answer is that there’s something intangible about face-to-face contact that’s essential to forming the deep relationships required to execute this business effectively. While that’s hard to quantify on a spreadsheet, it’s a necessary component of business, which means the ROI on these types of events is considerable.

Why face-to-face matters

For most of human existence, face-to-face was the only means of carrying out a meeting or conversation. This explains why our brains feel unsatisfied by videoconferencing or other forms of digital communication. A new book, iGen, about teens and young adults, posits that the lack of face-to-face communication in this group is leading to higher rates of depression and “the worst mental-health crisis in decades.”

Other recent research has shown that a face-to-face request is 34X more effective than email. The researchers found that nonverbal cues during the request made a huge difference in how the respondents viewed the legitimacy of the requests.

This research jibes with my personal experience. When you’re all attending the same event, there’s a spirit of comradery that comes from dealing with the same lines, inconveniences and stress of being away from home. Blame evolutionary conditioning, but you’re more apt to view the other person as an ally and look for ways to work with them. You inevitably see the person as more than a name behind an email. You can look them in the eye and gauge whether what they’re saying is trustworthy and whether they believe in what they’re saying.

Then there’s the convenience aspect. I suppose you could arrange dozens of back-to-back meetings from your home office, in-person or via video, but it would be a logistical nightmare compared to the ease of coordinating such meetings at an event where everyone is centralized.

So what’s the ROI?

Such concerns of course fall under the heading of “squishy humanity.” Programmatic is all about data and it’s all but impossible to quantify the value of a face-to-face meeting against the expense of travel and the opportunity cost of not being in the office.

Speaking of opportunity cost, the best way to quantify the ROI of attending an event is to consider the cost of not going. Inevitably, you will lose control of the narrative about your brand as others attempt to fill in the gaps because you’re not there to tell your story. You will miss out on connections that may save your company money or provide new business down the road. You’ll miss out on the gossip and strong opinions that offer a reality check against whatever execs are saying onstage.

Viewed that way, the intangible costs of flying halfway around the world to sit in a conference center for two or three days seems more tangible. Even a decade from now when we’ll be able to meet in VR, I think that dynamic won’t change. We’re wired to get personal. So let’s accept that as part of the cost of doing business effectively.



IBM, MediaMath Craft Partnership For Futuristic Infrastructure And Cognitive Bidding

September 25, 2017 — by Amarita Bansal0


This article originally appears on Beet.TV. 

COLOGNE – Despite the many innovations birthed by the advent of digital marketing, there’s still much to be done to deliver ads to people that don’t annoy them. This is why IBM and its Watson artificial intelligence assets are teaming up with demand-side platform pioneer MediaMath to create an infrastructure that supports cognitive bidding.

The partnership is designed to provide marketers with a neutral, security-rich computing environment along with the ability to maintain ownership of their data through the IBM Cloud.

“It’s about bringing the power of Watson AI into the bidding process, essentially creating real, cognitive bidding in an advertising environment,” MediaMath Chief Marketing Officer Joanna O’Connell explains in this interview with Beet.TV at the 2017 DMEXCO advertising and trade show.

A longtime veteran of the digital space, O’Connell ticks off the many attributes of digital marketing—from omni-channel touch points to real-time decisioning, machine learning from ad impressions to changing the way that siloed organizations can be customer-centric.

“But we have to be honest about the fact that there’s still so much more to do and it’s still not really what we want it to be,” O’Connell says. “It hasn’t fully realized the promise.”

Shortcomings include such infrastructure features as “pixels, header tags, waterfalls” and the like. “Would we have built it that way if we knew how big this industry was going to become, how material, how important? Probably not,” O’Connell says.

IBM and MediaMath say they have a shared worldview and the desire to take the next evolutionary steps together. Under the partnership, those steps are:

  • Develop infrastructure that connects brands, consumers and all of the companies in between in a way that is enterprise-class, open and smart.
  • Infuse AI into real-time marketing decisions across all channels, arming the marketer to do her job better with insights as opposed to reports.
  • Delight the human behind the screen with advertising people don’t just tolerate, but appreciate as entertaining, informative and meaningful.

O’Connell talks about an infrastructure that’s open and extensible, totally secure and safe. And one that provides ad experiences that don’t alienate consumers.

“Imagine if a consumer didn’t only tolerate it but actually loved it. We want to be able to do that. So that’s really what we’re working on.”

This video was produced as part of Beet.TV leadership series from DMEXCO, presented by NBCUniversal. For more videos from the series, please visit this page.


Focus Your Brand Marketing on Problem-Solving, Not Demographics

July 31, 2017 — by Parker Noren0


This post originally appeared on MarTech Advisor

Marketers and the digital ecosystem have fine-tuned activation methods that best leverage digital platforms and programmatic technology for direct-response campaigns (i.e., those focused on driving immediate ROI as the primary goal). At the same time, they’ve largely replicated what worked in linear channels, like TV, for branding campaigns. This approach commonly includes focusing activation on maximizing reach against a demographic, executing an unsophisticated supply strategy and failing to leverage measurement against real marketer outcomes to adjust in-flight.

It’s time to move past an approach for branding campaigns that in many cases embrace the lowest common denominator – a holdover from a time when the limitations of traditional channel targeting and execution constrained such campaigns. Every shopper has a problem. The purpose of our branding campaigns is to demonstrate how we solve that problem – reaching consumers who are likely to experience it and maximizing internalization of the message via tactical execution. We will better accomplish this by fully embracing the technological capabilities of programmatic for branding campaigns.

Overhauling Approach to Audience Targeting
The most notable example of replicating practices of traditional branding campaigns in digital is buying audiences and measuring success based on demographics. In traditional channels, this focus was rooted more in history than utility—demographics were the universal mechanism for buying media.

The emphasis on demographics is misplaced. When trying to build perceptions, marketers should target consumers who have a struggle that their product can uniquely solve. That is rarely something bound by demographics. Instead of aligning targeting to the constraints of linear buying, marketers should leverage the full suite of programmatic targeting capabilities to reach consumers likely to experience the struggle they solve for. This includes understanding of consumer interests, where they’ve been, who they are and what they’ve previously browsed/purchased.

Developing a Strong Supply Strategy
There is a belief that branding equals video in digital. As a result, many campaigns are executed in channel silos. For all campaign types, supply selection should be driven by the alignment between inventory type characteristics and the requirements of the brand-consumer interaction.

In most cases, this means video has a primary role in branding campaign execution because of its characteristics as a supply source. Video provides the opportunity to story tell and dramatize the brand’s solution to a consumer frustration or struggle. However, other inventory still has a role under a sophisticated supply strategy. For example, display inventory can play a vital role in fighting message recall decay when sequenced off a video touchpoint.

Better Measurement for In-Flight Optimization

What a marketer selects as the measurement criteria for a campaign has a profound effect on how the campaign is optimized. Common branding campaign measurement has no relationship to the marketer’s strategic intent, including click, completion and demographic metrics. Especially in the case of brand-building campaigns, interim reads from brand-lift research should be the primary criteria by which the campaign manager makes decisions and a marketer judges success. Those audiences and tactic structures that are producing the biggest perception change should prompt bigger bets over time. Percent on demographic target as a success criteria, meanwhile, should be used sparingly or relegated to the past.


The Year of the Sophisticated Marketer

December 30, 2016 — by Joe Zawadzki0


If 2015 was the year of adolescence for MediaMath, 2016 was accelerated maturity into the responsibilities of young adulthood.

This year, we evolved from an adtech company to an enterprise software and services provider, because the latter is what the market is demanding. Marketers are more sophisticated than ever. We are entering a “post-channel era” where CEOs, CMOs and CFOs are as obsessed as we are with data and outcomes.

With technology at their fingertips to enable 1:1 marketing at scale, with real-time execution, direct connection to consumers and the ability to measure business results over publisher inputs, marketers are increasingly motivated to “make it so.”

Those are our clients. MediaMath’s customers index toward the more sophisticated, and we’ve built our business to cater to them. This drive to move programmatic out of test budgets or a portion of their media investments sometimes requires new business models or team configurations to do so— our work with Coke and MediaCom out of Mexico is a great example of how this can be done with success. Marketers like the folks at MediaCrossing have moved from siloed channel approaches to true single platform allowing omnichannel execution. And with the pipes to hook together paid and owned media systems through great partners like IBM and Oracle, marketers are extending conversations they start with known customers in email across channels and the marketing funnel. From our founding, MediaMath has partnered with these most sophisticated marketers to push the boundaries of programmatic marketing. We want to continue to be seen as a leading “Visionary,” the category in which we were recognized in Gartner’s Magic Quadrant for Digital Marketing Hubs in January.

In the context of this growing client and market maturity, we made some changes internally that were both exciting and daunting.

Early in the year, we unveiled a new product business unit structure around our data, media and intelligence products, bringing our product teams closer to the client. Our data team, which successfully launched our proprietary data business, formerly known as Adroit, then Helix and now as part of MediaMath Audiences, in January and released into general availability our real-time DMP capabilities Adaptive Segments and IQ in November, is helping marketers leverage more of their first-, second- and third-party data sources (including deepened and new partnerships with data providers like Acxiom, PushSpring and Cuebiq) and shape the analytics around them.

Over top these new product business units, we’ve ramped up our professional services capabilities to enable clients to unlock the full potential of programmatic with talent and expertise.  Our New Marketing Institute, which is now officially in all regions with its expansion into APAC earlier this year, continues to help clients close education and talent gaps through their certification and training offerings and the Marketing Engineer Program. We also revamped our technology organization, appointing Wilfried Schobeiri as Chief Technology Officer (CTO) and Steve Steir as our new SVP of Engineering. Wil will drive our technical vision, ensure scalable growth of our systems and push the productization of our API and technology platform while evangelizing our technology both inside the company and externally to the market. Steve will make sure our global engineering team is aligned on the goal of continuously improving people and products.

Coming out of this new product structure, we have the right people in key roles across teams to move the company and mission forward. And there’s a renewed commitment to ongoing evolution and mobility that should smooth the migration of people and resources to the focused set of initiatives that need them at various time periods, varied as needed across geographies. We continue to strive to be a place where people at all stages of their careers want to work, and also encourage those individuals to give back in meaningful ways through the launch of our philanthropic arm

From a financial health perspective, our enterprise business grew just over 20 percent in our most mature market of North America and to over 100 percent in LATAM, along with (a return to) overall profitability. And we did that while taking something really good—a fast-growing and high-contribution business unit in Adroit—and blowing it up to free up the amazing talent and differentiated data assets inside to accrue to the benefit of all of our clients, globally, to become something great. Even more intestinal fortitude was required to shift our buy strategy for “batch supply”—Upcast—to build, in order to position it to grow by triple digits in 2017 as mobile and video did this year.


What else is to come in 2017? Here’s what I know: the market for what we are doing is getting bigger and the number of credible competitors is getting smaller. Smaller point solutions—from channels like video to standalone DMPs—are getting bought, validating the need for the integrated, transparent enterprise solution that we have been building for close to a decade. Audiences addressable through all forms of media, the centrality of machine learning—these ideas are being embraced after 10+ years to move from fringe notion to “obvious.” We are in the business of transforming marketing through tech and math, and we know where the market is going and are increasingly able to shape its direction.

And yet we will do more. The need for supply chain hygiene will cause some to call for a return to the halcyon days of advertiser, agency and publisher in the same way that the challenge of attribution had many retrench to engagement or reach metrics alone. Thankfully, we have truth on our side. In 2017, we as a company and as a catalyst for the cause must focus on belief and proof, and show it in the data and the results.

To do that, we will continue to invest in innovation and even more in scaled operations and infrastructure, partnering with the most sophisticated marketers and the diverse ecosystem that supports them.  We have an amazing team and the industry’s most powerful platform—the table is set. Now it’s up to us.


Lessons we Learned from Data-driven Marketing in 2016

December 28, 2016 — by Zachary King0


This byline originally appeared on

In 2016, the power and importance of “big data” finally started to pay off—everywhere around the globe, across all markets and industries.

For businesses, the role of information in supporting marketing and advertising is no longer just about providing learnings. Organisations now look to data for actionable insights and to drive better business outcomes. Increasingly, they are moving towards a smarter and more consumer-centric approach, which can only be done by deriving meaning from data. In a 2016 MediaMath-commissioned research study undertaken by Forrester Consulting, almost 41% of marketers in Asia Pacific said that they have adopted programmatic buying, with 82% of them either satisfied or highly satisfied with their investment in the technology.

As we approach the end of the year, it’s clear that data, and programmatic, is now a central pillar of customer experience, and therefore marketing. As businesses look to jump on board, here are some lessons we’ve learned over the past year that marketers around the world can take with them into 2017.

It’s still all about the consumer

Consumers increasingly expect a more personalised experience. This is perhaps why consumers are voting with a click of their mouse in order to avoid disruptive, annoying or irrelevant advertising. The increased usage of ad blocking technology is a consequence of irrelevant and unwanted advertisements.

To address this issue, marketers are enthusiastically embracing the “customer-centric” approach. Marketers are increasingly turning to data-driven marketing, including the management of customer databases, deployment of predictive analytics, and segmentation to learn more about addressable audiences, and implementation of omni-channel campaigns to have a more holistic view of their audiences. With platforms that recognise individuals across multiple devices, address changing behaviour of consumers, and enable omni-channel execution, marketers can deliver experiences that transcend channels, formats, and devices.

Digital is where it’s at

Web content, social media, search, and online display advertising increasingly make up a greater proportion of the marketer’s arsenal to reach their target audience—and it’s easy to see why.

Consumers from all demographics are now spending more time online. Digital consumers are spending an average of over six hours daily on the internet—which is equivalent to more than half of a consumer’s daily media time. With Asia home to more than half of the world’s internet users, marketers here can take full advantage of this huge opportunity by bridging the gap between traditional and digital in their media mix.

As such, marketers are reporting that digital media is now delivering the greatest return on investment, with the performance of their display advertising, web content, and social media investments making the most strides in the past year. With better performance, cost effectiveness, and operational efficiency, marketers are choosing programmatic to help them boost contextual targeting, reduce waste, and provide timely and relevant content to their audience across multiple devices. Marketing has gone digital, because that is where the consumers are—and are likely to stay.

Untapped potential

While close to three-quarters of marketers globally said that they remain confident in the practice of data-driven marketing and its potential for future growth, going digital requires expertise that can unlock and generate more value from data-driven marketing efforts. In addition, marketers today also generally believe that the optimisation of campaign measurement would be most valuable if it provides deeper insights to inform future campaign planning, media mix modelling, and other optimisation efforts. This is where programmatic comes in, with APAC marketers citing better contextual targeting, faster and more efficient execution and real-time optimisation as the most important benefits of programmatic.

The lesson is that marketers need to not only know the data at their disposal, but also be able to smartly analyse and activate it to get the best return.

The task of navigating more complex data from different media channels, with increasing customer requirements and higher expectations, is a challenge. With digital marketing technology, marketers can derive meaningful insights, enabling marketers to execute better targeted campaigns. The more intelligent the technology, the better the consumer insights, and the more targeted the marketing approach—eventually leading to happier consumers and better business results.