DataLand: un espacio para Data Science en México

Por Gabriela Huerta, Head of Marketing Latin America

El pasado 7 de enero se llevó a cabo DataLand, un evento en el que se invitaron a todos los interesados en el manejo de datos y en cómo la tecnología nos puede ayudar a utilizar los datos de manera efectiva.

El lugar de encuentro fue el Auditorio Raúl J. Marsal en la Facultad de Ingeniería en la UNAM, el evento comenzó a las 6:00 p.m. Aunque en estas fechas, los estudiantes están aún de vacaciones, se llenó el auditorio e incluso había gente en las escaleras y en la parte de atrás del auditorio.

La primer plática se realizó sobre Activismo a través de Bots, en donde nos explicaron cómo desarrollaron bots que fomentaban un comportamiento hacia los usuarios. Aprendimos que hay usuarios que aunque estén conscientes del uso de bots, los siguen en redes sociales e incluso comparten el contenido que éstos generan. A esta práctica, se le llamó “Botivism”.

La siguiente presentación fue sobre Visión por computadora. Aquí aprendimos sobre cómo se pueden desarrollar sistemas inteligentes que complementen imágenes y nos permitan un mejor reconocimiento visual y reconstrucción de imágenes.

Después aprendimos sobre visualizaciones de datos para ayudar en colaboraciones entre humanos y bots. Esta charla fue una manera de unificar los conceptos que habíamos visto anteriormente: visualización, bots y activismo en medios digitales.

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Además de patrocinar este evento, Digilant tuvo importante presencia en este evento ya que Kenjy Tominaga y Gabriela Huerta, Heads of Product & Marketing respectivamente, dieron una charla sobre Meaningful Connections quienes nos explicaron sobre la importancia de plantearse objetivos, organizar la información automáticamente de acuerdo con estos objetivos e identificar las necesidades que cubre cada tipo de información.

Ellos también nos mostraron una demo en vivo de un producto exclusivo de Digilant llamado Consumer Persona. En esta demo, observamos cómo se generan clusters en tiempo real en una campaña, agrupando a los usuarios de acuerdo con sus intereses y entendiendo las conexiones entre todos los intereses.

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Al final, tuvimos oportunidad de escuchar rápidamente de qué trata la aplicación desarrollada por Alejandra Monroy: TinDog, una app que conecta a las personas que han rescatado perros de la calle con personas interesadas en cuidarlos de manera real o virtual.

También contamos con la presencia de Jesús Ramos, VP Analytics & Data Science en GBM homebroker y creador de The Data Pub, quien nos hizo una cordial invitación a las actividades de Data Pub. Aquí podemos ver su presentación sobre Big Data, Big Dissapointment.

Al finalizar el evento, realizamos Networking partiendo Rosca de Reyes, la cual se terminó de volada. Sin embargo, hubo una gran convivencia con personas que se dedican a los datos en diferentes sectores y Norma nos compartió varios souvenirs de distintas marcas de tecnología. El evento superó las expectativas de todo tipo: en cuanto a contenido de las presentaciones, cantidad de asistentes y networking. Estamos ansiosos para el siguiente evento.

Personalmente, me siento muy contenta porque la comunidad de personas interesadas en Datos está creciendo mucho en México. En nuestro país hay mucho talento, pero considero que falta comunicar más estas actividades y conocer a más personas con los mismos intereses. Recordemos que México es un país creativo y podemos ser tan inteligentes como nos lo propongamos.

Are You Rinsing and Recycling Your Marketing?

Written by Digilant’s Chief Strategy Officer & Data Scientist: Krishna Boppana.

One of the promises of buying digital media programmatically is scale, unlimited users at a high frequency and low cost of media. Today, when running Direct Response or performance based campaigns, retargeting is still the best performing tactic because programmatic is very efficient at finding and converting users who have already shown intent.  However, retargeting has its limitations, mainly that it doesn’t scale beyond users that have visited your webpage.

So, how can you scale your programmatic advertising?  Is there a better way to improve ROI beyond retargeting? How do I find more consumers that will convert efficiently?

Marketing Data: History

Since the beginning of marketing science, marketers have built their marketing plans and strategies using research to identify ‘personas’ of their consumers. The data that goes into building these personas is often one dimensional (developed through surveys and by analysts). This means that the analysis considers one or fewer moments of aggregated data and doesn’t analyze the consumers holistically. In the digital advertising world, each of us as consumers, sit in more than 100 industry data segments (i.e., living in Boston, male, purchase intent, etc.) on average. Traditional marketing personas only account for a handful of segments like demographics, Geo, household income, etc..  

Marketing Data: Now – Consumer Persona

Through our data science research, we have discovered a way to make marketing personas more accurate, using machine learning and applying data science to available 1st, 2nd and 3rd party data. This is an impossible achievement with human analysts, there are just too many data points for any analyst to process to make a meaningful output in near real time.

How Do I Find New Consumers?

Stop rinsing and recycling your audience! Instead, you want to first identify all of the data associated with your consumers, this means all of the 100 or more segments based on multiple attributes (e.g., surfing behavior, time of day, type content consumption, etc.) Then apply multiple data science models and algorithms to identify a “Persona” that captures these complex user behaviors and places them in a machine generated audience Persona Graph. The audience Persona created will be based on dynamic, real-time consumer behaviors, unlike the static personas or the traditional look-a-like models. Once the users and user behaviors are identified, predictive algorithms can be applied to assess the value of the persona and the value of each user in real time. The end result is the ability to identify potential “new consumers,” not recycled users.  And knowing the value of the user will allow you to target effectively and efficiently, improving performance.

Pictures Matter

Humans are really good understanding and remembering pictures. So, logically, advertisers would want to see consumer behaviors associated with their campaigns. Historically, this has been a  difficult problem in data science – the ability to visually represent an algorithm output. To solve this problem, we created an easy to understand visualization for consumer behaviors that are important for a campaign or advertiser. Below is a  screenshot of our Consumer Persona visualization.
Consumer PersonaConsumer Persona Open

The left image shows all the personas for a campaign. If we expand one of those personas, the “young working class family” in red; the right side image shows all the audiences that comprise to this one persona. You can also see the connections that each persona has with other personas.  In other words, they share behaviors.
We also looked at probability of conversion.  What we found was a machine generated persona captures complex behaviors and responds to data signals in near real time. Thus, increasing performance.

Insight to Action

At Digilant we are transforming the static marketing persona concept into a data science driven ‘Consumer Persona’ using all the data signals available. This is one step further in the direction towards the promise of programmatic — extending audience reach and enhancing campaign effectiveness using what we know best, data.

Digilant Inks Deal With Cross-Device Targeting Firm Crosswise

September 9, 2015 – Tyler Loechner, MediaPost

Programmatic ad tech platform Digilant on Wednesday announced it has partnered with cross-device targeting firm Crosswise.

Crosswise asserts that it’s technology can match disparate devices — including computers, tablets and smartphones — to their individual users.

As a result of the partnership, Digilant will be able to track — and programmatically target — consumers across devices.

“Cross-device targeting is a tool that many brands and agencies, are striving to accomplish,” stated Kim Riedell, SVP of product and marketing at Digilant.

Cross-device targeting is something many in the industry are working on, although some have found it easier said than done.
Crosswise raised $3 million in a Series A round of funding last week.

Digilant Opens 3 Offices In South America

September 8, 2015 – Tyler Loechner, MediaPost

Digilant, a Boston-based programmatic media-buying company, on Tuesday announced it has opened three new offices with a focus on South America.

The company has opened shop in Santiago, Chile; Lima, Peru; and Monterrey, Mexico. The company already had offices in Mexico (in Mexico City), Brazil and Colombia.

To lead the new offices in Chile and Peru, Digilant has tapped Eduardo Arevalo and Alexis Reategui as country managers, respectively, per a release. Additionally, Mary Gonzalez has been named country manager, Colombia.

Arevalo joins Digilant from Headway Digital a programmatic trading desk that focuses on Latin America and U.S. Hispanics.

Gonzalez joins Digilant from Colombian contextual ad network Pautefacil.com. Reategui joins from Hibu, where he most recently served as head of digital.

Boston Marketing, Ad Tech Firms Get Their Very Own LUMA-Inspired Chart

September 3, 2015 MediaPost
It may not be Silicon Valley, but Boston has proven to be a formidable breeding ground for some successful digital marketing companies.

Jebbit, a Boston-based “post-click marketing platform,” decided to round up all of these Boston marketing and advertising technology companies and display them in a Lumascape-like chart.

One of the busiest buckets on the chart is the programmatic ad category. Featured are DataXu, Clypd, Digilant, ChoiceStream, OwnerIQ and BuySellAds. Other companies involved in marketing automation — such as mobile-focused firms Fisku, Adelphic and Celtra — also make the chart.

Boston is also home to VisualIQ, Semcasting and others in the data and analytics space. Jebbit plans to update its chart periodically, and is even open to suggestions or comments if someone believes “a company should be in a different category.” The fact that even needs to be said at all speaks to how intertwined a lot of these marketing and advertising technology companies are.

Not mentioned on the chart are nToggle, a new player in the ad tech space that offers technology that “toggles” bid streams to match programmatic supply and demand more effectively; Visible Measures, a DSP that calls Boston home; and others, including Nexage, which was acquired by Millennial Media.

In addition, some Boston-based venture capitalists and investors have taken an interest in ad tech as well. Last summer, some of the biggest ad tech companies — including AppNexus andMediaMath — raised a substantial amount of money in respective rounds led by Boston-based firms.

A diagram put together by a vendor is not the same as a diagram put together by the actual LUMA partners, so take it all in with a grain of salt. This is not an all-encompassing view of the Boston marketing and advertising technology space — nor should it be considered one — but it’s interesting nonetheless, because it does shine a light on Boston as a burgeoning hub.
Jebbit’s chart can be found here.

Mass. is home to more than 60 marketing and advertising tech firms – here’s why

September 1, 2015 – Boston Business Journal

Companies in the field of marketing and advertising technology have been in the news lately because they’re growing significantly in the Boston area.

In fact, according to marketing technology startup Jebbit, the Bay State is home to more than 60 companies in the marketing and ad-tech space.

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That’s largely because the Boston area breeds the kinds of candidates that companies in this space are looking for: People with analytical and technical skills who are also “great storytellers,” according to Robert Murray, president of Boston-based marketing technology firm Skyword.

“With its publishing and high-tech pedigree, the Bay State is where these two talent pools come together,” Murray said in an email. “Combined with a world class infrastructure and young and vibrant city life, it’s why Skyword and other marketing players are at home here.”

Skyword is moving into a bigger headquarters in Downtown Crossing and looking to open an office in Europe this year and growing total headcount from 125 to 160 by the end of the year. Founded in 2010, the company has raised about $29 million in venture funding and its investors include Cox Media Group andJim Manzi, former head of Lotus.

Public companies in the marketing and advertising technology sector include Cambridge-based sales and marketing software firm HubSpot (NYSE: HUBS) and Waltham-based email marketing firm Constant Contact (Nasdaq: CTCT). Growing Boston-based adtech firm Localytics was recently listed among the fastest-growing companies on Inc. Magazine. Localytics’ annual revenue for 2014 was $9 million.
Investors are also taking bets on startups in the marketing and advertising space.
Jebbit, for example, quietly raised $1.5 million in equity funding recently, out of a $3.5 million target goal, according to a regulatory filing.

Boston-based adtech startup Inmoji has recently raised a $2.5 million seed funding round from some high-profile investors including former PayPal Media Network chief operating officer and startup evangelist David Chang.

And Linkable Networks, a Boston-based loyalty advertising technology company that aims to engage retailers and consumer-packaged goods brands with millennials, raised $11.7 million in investor funding earlier this year.

Jonathan Lacoste, president of Jebbit, said the marketing and advertising industry is changing at an incredibly fast pace with technological innovations — and Boston is leading the way, along with San Francisco, New York City and Los Angeles.

“The way the marketing and advertising landscape continues to shift toward deeper analytics and data across all platforms, the deep pool of technical and university talent we have in the Bay State area will keep us a leader,” Lacoste said in an email.

The Other Cross-Device Guys: Catching up with Crosswise

June 22, 2015 – AdExchanger
What will be the fate of probabilistic data in a world populated by Facebook and Google?
Steve Glanz, CEO of probabilistic cross-device data provider Crosswise, admits that deterministic data is superior to probabilistic connections – but his answer to that question is still yes because of one major factor: the need for scale.

“Obviously, it would be best – not for us, of course, but best for marketers and advertisers – if there were 100% deterministic data solutions available to everyone – but no one has come close to building a deterministic solution with true scale, even Facebook and Google,” he said. “We’re constantly disappointed at the number of users logged in across devices. It’s relatively small, even at the big retailers. Only a small percentage of users do it.”

But that’s not how AOL CTO Seth Demsey sees the future playing out. He anticipates a near-term evolution in the market that will make the line between ad tech and martech “extraordinarily blurry.”

“No matter how high you get your probabilistic scores, the winds I’m feeling with clients, whether direct or agency, is that deterministic matching and scale is what will win here,” Demsey told AdExchanger. “We’re going to see significantly increased instances of sophisticated CRM onboarding and CRM-driven execution, and probabilistic doesn’t play there. There is no such thing as probabilistic onboarding.”

But Yosha Ulrich-Sturmat, VP of product marketing at Neustar – and a client of Crosswise – predicts a world in which deterministic and probabilistic will coexist, if not in harmony, then at least out of necessity.
“Neustar comes from a place where we have the luxury to be able to build predictive linkages,” he said. “But there are limits to what deterministic can do, and I believe you need to augment deterministic data with probabilistic linkages in order to see success.”

That’s what forms the basis of Neustar’s relationship with Crosswise, whose client list of more than 25 DSPs, DMPs, attribution providers and analytics companies also includes The Trade Desk, Undertone, Turn, RadiumOne, Marin Software, Eyeview and Digilant.

Crosswise prefers to be behind the scenes.
“If you’re looking for an end-to-end solution that includes media and reporting, we’re not the company for you,” said Glanz.

Crosswise, which Glanz expects to break even within the year and be profitable “relatively soon,” made its probabilistic data product generally available in the US late in 2014 after firstlaunching a controlled test phase last July in the New York market. It rolled out its UK business in May.

Since then, Crosswise’s staff of 25 – the majority of whom are based in Tel Aviv and focused on tech and data science – has been training and validating the company’s algorithms using a data set of more than 100 million deterministic pairs which it accesses through several partnerships, including a close one with LiveRamp. Crosswise also uses LiveRamp to distribute data to many of its clients.

Tapad has a similar approach with its algorithm, using deterministic data to teach its device graph to create more accurate probabilistic cross-device connections over time.

But unlike Tapad, Crosswise doesn’t sell media, and that’s by design. It’s a neutrality thing, said Glanz. Rather than courting the agencies and advertisers themselves, Crosswise does business with the DSPs those agencies and advertisers work with to execute their campaigns.

Neustar is a good example. As a provider of marketing and information services, Neustar maintains its own deterministic data set based on a foundation of around 120 million US households comprised of 200 million adults tied through anonymized transactional data to 180 million devices.

It’s quite a large repository, but Neustar still needs to augment its deterministic data with probabilistic linkages, said Ulrich-Sturmat.

Neustar onboards data from Crosswise and several other cross-device technology players – Ulrich-Sturmat declined to name which ones – to extend its segmentation capabilities and help build the “identity layer” that fuels the work done inside PlatformOne, Neustar’s workflow, insights and analytics solution.
“We call it the network effect of data,” said Ulrich-Sturmat.

The data that comes on board from Crosswise arrives in the form of a massive file with three columns: one for cookie ID or device ID, another denoting the cross-device connection and a third designating a confidence score. The first row, for example, might say, “desktop cookie, Android ID, 50%,” the next row, “mobile web cookie, iPad, 80%,” the row after that, “Android ID, iPhone IDFA, 90%” and so on down the line.
But the examples above don’t necessarily represent separate people. It’s entirely possible that columns A, B and C correspond to different connections for the same person, someone who owns a Samsung phone, an iPad and an iPhone.

While some clients ask Crosswise to stitch these disparate connections together into a single person before they receive the file, Glanz said Neustar prefers to receive its data “in the raw,” so to speak.
And there’s a reason why. Cross-device is a two-pronged game pitting accuracy against scale. Both of those factors need to win in order for the advertiser to get value. If column A and column C are the same person, but column A is 50% accurate and column C is 90% accurate, the accuracy of the combined connection is weaker than the accuracy of column C on its own.

Once a campaign has been deployed, advertisers also want to track performance and optimize accordingly.
“We need to help advertisers answer the question, ‘How did I do?’” said Ulrich-Sturmat. “And to do that, we need an holistic view of devices combined with our analytics layer.”

Back to the question of accuracy, although Crosswise isn’t yet verified by Nielsen like Tapad and Drawbridge – 91.2% and 97.3%, respectively – Glanz said that the company’s matches are 90%-plus accurate. But Crosswise, Glanz said, also provides “matches with lower confidence scores which allow the customer to choose what works best for them.”

InMobi, Rubicon Expand Mobile Exchange to Include Native, Video

June 2, 2015  – MediaPost
InMobi, a mobile programmatic ad exchange, and Rubicon Project, the ad tech provider that powers the exchange, continue to expand their partnership.

The two companies on Tuesday announced that the InMobi Exchange has officially integrated with 10 demand-side platforms (DSPs) to support programmatic native ad-buying in concordance with the IAB’s OpenRTB 2.3 standards released earlier this year. Additionally, over a dozen DSPs can now buy mobile interstitial video inventory via the InMobi Exchange.

The exchange, launched one year ago, has always been focused on native advertising. Ever since the initial InMobi-Rubicon partnership was announced, the two companies have essentially been putting the pipes in place for programmatic native ad-buying, working closely with the IAB and a handful of other companies to release the OpenRTB 2.3 standards.

InMobi says it began testing programmatic native ad-buying on its exchange with a select group of DSPs during the first quarter of this year, and today’s announcement marks the full development of the offering.
The introduction of video to InMobi’s exchange beefs up the amount of “quality” inventory it houses. The video inventory available on the exchange complies with the IAB’s Video Ad Serving Template (VAST) standards.
InMobi’s ultimate goal is to usher in a “no banner” mobile advertising world, stated Anne Frisbee, SVP of global alliances and programmatic at InMobi. She added that 40% of the inventory available on the exchange is now either native or video, a figure that is expected to rise.

Adelphic, Bidtellect, Bidswift, Bidstalk, Digilant, Stackadapt and others are counted as native DSP partners. The Trade Desk, Tapad, EyeReturn, AdTheorent, Adelphic and more are among the DSPs that have access InMobi’s new mobile video ad inventory.
In addition to marking a large-scale effort to adhere to the IAB’s new programmatic native standards, today’s announcement also represents another win for programmatic mobile video, which has been on a hot streak recently.

According to recent BrightRoll surveys, the majority of agencies in both the U.S. and Canada expect mobile video to be the fastest-growing category in terms of digital media spend this year. It’s no surprise, then, to see that BrightRoll decided to double down on mobile video.

Two other video-focused programmatic ad platforms — Videology and TubeMogul — have recently reported rises in programmatic mobile video as well. Videology recently said the number of programmatic mobile video ad campaigns running on its platform increased 81% from the fourth quarter of 2014 to the first quarter of 2015, while TubeMogul noted that mobile ad spend on its platform has increased 500% year-over-year.

A 360 View of Viewability: We All Have a Stake

June 2, 2015 –  MITX
In the world of digital advertising it is hard to go a day without hearing or reading about the industry’s viewability issue. From new guidelines, to new studies, to announcements from advertisers’ that won’t settle or pay for less than 100 percent viewability. But what does 100 percent viewability mean, how do we get there, and what happens when we do?

These are some of the questions posed at a recent event I participated in, representing the Demand Side Platform (DSP) perspective, along with representatives from the publishing, brand, agency, and media valuation sides of the digital advertising ecosystem.

Our lively discussion may not have revealed definitive answers to all of these questions but we did find common ground across what can seem like opposing objectives. One thing we all agreed on was that there is more to learn, and more to do. So how do we work towards setting and reaching a realistic viewability standard?
Set Reasonable Expectations


In conjunction with the event Digilant conducted a survey to assess advertisers’ perception of viewability. We found that more than 42 percent of respondents expect more than 75 percent viewability from their media buys, with more than 21 percent of respondents expecting viewability greater than 90 percent.

While there is a great deal of variation across ad type and device, viewability reality is somewhere closer to 50 percent. Even the Media Rating Council (MRC) notes an expectation of 100 percent viewability is “unreasonable”and the IAB has called for a goal of 70 percent.

There is certainly merit to demanding that when paying for views, you get those views. But this is not an issue exclusive to digital advertising, and reasonable expectations must be set.

Establish Some Consistency
One of the biggest challenges in reaching 100 percent viewability is measuring it in the first place. MRC has taken an important step by defining a viewable impression. But the technology for measurement is still evolving and not all sites can actually be measured. It is important to recognize, though, that “not measureable” does not mean “not viewable.”

Vendors that provide third party measurement and validation are another key piece to the puzzle. But a consistent standard of measurement has not been established and there is still variation across vendors. While we work towards an industry standard – and the technology to back up that standard – transparency will be key.

Accept that We Are All Accountable
As advertisers begin to make stronger demands for viewability, including contract stipulations that they will only pay for viewable impressions, there has been a lot of finger pointing to who should be held accountable. The reality is, everyone needs to be accountable.

Publishers need to identify ways to make all impressions viewable. Media valuation vendors need to establish a consistent and transparent form of measurement. Ad tech providers and agencies need to work with trusted partners on a consistent basis for streamlined measurement and transparent reporting. These efforts will work to provide advertisers greater viewability standards and accountability. But advertisers have an important role as well.

If brands demand 100 percent viewability, they may need to reevaluate their current KPIs. Ad buys may need to be limited to measurable URLs, which could limit the reach and scale, and create gaps in effective targeting. Further, if publishers have to adjust impressions per page to ensure viewability, they may have to raise prices to account for this higher quality inventory.

The above outlook may look like an insurmountable challenge, but I came out of this industry discussion feeling incredibly optimistic. We all have a stake in ensuring quality inventory and measurable results, however we will all benefit from achieving that goal so must work together to solve it.

Walled Gardens Not as Bad as You Think

December 19, 2014: Krishna Boppana in AdExchanger
With Facebook’s recent Atlas launchApple’s iAd refocus and Google’s restrictions on DMPs’ pixel firing, we’re seeing the rapid emergence of the “walled-garden” model of digital advertising.
As a result, advertisers may feel that they’ll be locked in when choosing a platform to work with. But in reality, they’ll have access to consolidated high-quality inventory, while audience reach, targeting and attribution will be in silos.

The closed environments will give those networks the ability to improve inventory quality, provide in-network attribution and develop different creative ad units and solutions. Industry consolidation will undoubtedly cause some players to exit or pivot in the near future, but ultimately, the walled-garden model will be positive for all elements of the digital ecosystem.

Accurate Audiences
“Walled garden” generally refers negatively to the boundary between two resources that should otherwise be integrated. It’s a positive term in this context. Programmatic vendors have always touted their algorithms as key differentiators, but even the most accurately predictive algorithm won’t produce desired results without separating each advertiser’s data into individual silos.

For example, if an algorithm ingests a massively disproportionate amount of data from one advertiser, results for all customers will be skewed towards the largest advertiser and category. While this may not concern the biggest brand players, smaller ones may be incentivized to turn to Facebook or Google for what they perceive as more accurate audiences.

Impact On Fraud
As 2014 comes to a close, many advertisers still lack true insight into their campaign performance, thanks to opaque buy-side platforms and the persistence of fraud. While one could argue that fraud will always be an issue to some extent, like a typical software virus, advertisers can expect to get a better handle with controlled environments. Facebook is promising the holy grail: fraud-free advertising with walled user data, cross-device tracking and ad serving. With user registration data (Facebook login), controlled inventory, ad units and built-in attribution, it promises to be a fraud-free solution.

Walled gardens help to limit publishers’ data leakage and hold publishers to higher levels of transparency to control fraud at the source of the problem. The presumed default onus of providing higher-quality advertising is shifting from buy-side platforms to publishers and sell-side platforms. This is an important step forward for the programmatic ecosystem and for advertisers.

Reach Across Walled Gardens
The main drawback of a solution like Facebook’s Atlas is that it still only reaches Facebook’s user base and relies on its (albeit enormous) user reach. While Facebook will be a component of most campaigns, it’s not the only channel that can reach an advertiser’s target audience at any given time.

With the success of cross-device identification solutions, it’s more important than ever to reach users at the right time on the right device with the right creative. This simply means advertisers do not have to get “stuck” in a walled garden, but rather leverage them by using their buy-side platform to reach across walled gardens.
The walled-garden phenomena won’t doom the industry. Increased competition and higher-quality inventory will produce a race to the top, where the most successful technology providers are also the most transparent and effective. This will go a long way toward helping digital marketers deliver on the promise of true one-to-one marketing at scale.

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