Adelphic Is Proud to Announce a New Approach to Cross-Channel Advertising

August 17, 2016 in Blog

Adelphic’s VP of Product, Yael Avidan, provides an overview of Adelphic’s new cross-channel solution. 

Understanding consumers’ device usage is beneficial, but understanding consumers’ behaviors across multiple channels, in addition to the devices used, provides much richer data to power campaigns. This is what comprises our proprietary data set, which we refer to as our Behavior Graph™–which powers real-time optimization based on a complete, cross-channel user profile.

Having the Behavior Graph™ integrated into Adelphic’s decisioning layer enables marketers to transition to a real user-centric approach to campaign planning, management, optimization and reporting–and drive superior performance and efficiencies for campaigns targeting consumers on the move.

Cross-channel sits at the heart of Adelphic’s platform.

cross-channel-at-heart-of-Adelphic

 

Adelphic’s cross-channel solution is comprised of:

  • Adelphic’s Device Graph:  Adelphic’s proprietary device graph leverages non-PII behavioral signals in addition to contextual and location signals in order to identify and link devices.  The device graph includes intra-device as well as cross-device, cross-channel links and makes use of deterministic data when possible, but scales using a probabilistic algorithm.   Over trillion data points serve as starting point and then filtered.  Between 50-100 features are used to identify user pairs. The graph is based on roughly 40% in-app requests and 60% web requests and is continuously updated based on real-time data collection.   Adelphic holds a patent for audience recognition across multiple devices.
  • Adelphic’s Behavior Graph™: Behavioral signals, captured in real-time, are mapped back to the device graph to form a richer dataset that joins identity and behavior.  Behavioral signals range from performance (e.g. clicks and conversions) to behavior patterns (e.g. time of day, location, browsing behavior).
  • Adelphic’s  ^tag (“a-tag”):  A persistent identifier that overcomes the lack of a standard user identifier for mobile and desktop (and future channels).  Using Adelphic’s Behavior Graph™,  multiple devices and their associated behaviors can be assigned to single ^tag, creating user profiles that incorporate data from multiple channels
  • Adelphic’s Predictive Performance Engine:  User behavior and ad performance history across devices and channels are used in real-time to predict the value of a user for a specific ad  (e.g. did this user see this ad on a different channel? Does this user convert more on mobile or desktop?).  The engine leverages cross-device user models as well as contextual models (combined via a combination model) to drive bidding decisions and superior performance.

Our solution enables flexible onboarding of audience segments (1st party, 3rd party, campaign data, pixel-based), forecasting available inventory pools and targeting them across channels.  Adelphic’s Predictive Performance Engine sits at the heart of the solution by leveraging users’ complete profile to drive performance and efficiency.   

Key strategies that are supported via Adelphic’s solution:

  • Cross channel targeting across Display, Mobile,  Video and cTV.
  • Extending the reach of advertiser’s retargeting audiences
  • Extending the reach of lookalike segments
  • Extending the reach of behavior-based segments
  • Creative sequencing across multiple channels
  • Frequency management across channels 

More information:

  • How Cross-device identity matching works – Here
  • Looking for a Cross-Device Solution? 3 Questions Ad Buyers Should Ask – Here
  • Adelphic Launches First Behavior-Centric Cross-Channel Programmatic Ad Solution – Here

Central to our cross-channel solution is, of course, privacy.  Adelphic is fiercely focused on consumer privacy and takes specific steps to ensure that our user profiles are anonymous. Neither we nor the clients who partner with us can glean personally identifiable information from the consumers we engage, even by accident. Adelphic is a member of the Digital Advertising Alliance and complies fully with the DAA’s Self-Regulatory Principles for Online Behavioral Advertising and Self-Regulatory Principles to the Mobile Environment. Adelphic also allows opt out from behavioral tracking through Ghostery.

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Looking for a Cross-Device Solution? 3 Questions Ad Buyers Should Ask

August 17, 2016 in Blog

Adelphic’s Director of Product, Dr. Justin Pniower, lends his perspective on 3 questions media buyers should ask about cross-device advertising.  

Ad buyers have grown accustomed to siloed campaign strategies – separate budgets for mobile, desktop and television. But an audience-based approach executed across the devices of a consumer can be a powerful tool, allowing you to interact with and follow users as they move between devices and channels. But it can be hard, even for experts, to evaluate the quality and scale of these solutions, and industry standards do not yet exist. To determine whether the promise of cross-device solutions can deliver, here are some questions you need to ask.

How is quality measured?

Precision, the percentage of links that are correct with respect to a test dataset, is typically the key metric for assessing the quality of a cross-device solution. But, as is the case with other forms of measurement, values can differ substantially based on the details, like what counts as a correct or incorrect link with respect to the test dataset, or how a link is counted if one device is outside the test dataset.

The test dataset itself also has an effect on the precision measurement. You should inquire about the source and quality of the test data, but you should also inquire about the size of the dataset. By shrinking the size of the test dataset, vendors can inflate precision measurements.

How many connections?

When it comes to cross-device measurement, precision does not indicate anything about scale.  You can have perfect precision with just one link. Generally people consider the central metric for scale to be recall, the percentage of links in the test dataset that the solution was able to identify. But you can still have good recall without good scale, and vice versa. For that reason, you also want to know the total number of connections associated with a given level of precision in order to get a better sense of scale.

But the number of connections alone won’t provide all of the information you need. It’s important to understand the number of each type of connection – intra-device, cross-device and cross-channel – as well.

Not all connections are between different devices. While “device graph” is the common term for a map that links individual consumers to each of their own devices, it’s actually a bit of a misnomer. At the most granular level, the nodes on the device graph are unique device identifiers, not unique devices, and there can be multiple identifiers for a single device. When vendors characterize the size of their graphs, they may be sharing the number of links between device identifiers (intra-device), not the number of links between devices (cross-device). When it comes to your return on ad spend, the difference is important.

A user’s browsing and location history can be very different on a mobile device and a desktop making these links, across channels, among the hardest to establish. In order to identify a cross-channel connection, a robust dataset for each channel is required. As such, the majority of links within a graph are likely between devices in the same channel. Inquire about the percentage of connections that are truly cross-channel as well as their relative precision.

What is the effect on my data and KPIs?

While the counts are important indicators, they do not guarantee scale for your data. First-party data is the ad-buyer’s “holy grail,” so it’s important to know the match rate for identifiers you want to extend using the graph in order to truly optimize your ad spend – and your campaign – across specific consumers’ devices.

But if a cross-device solution cannot improve your KPIs, then other metrics do not matter. Performance KPIs like awareness, engagement and conversion rates work well to measure a cross-device campaign. Solutions that enable sequencing and frequency capping across devices can help bolster these KPIs and reduce a consumer’s urge to activate an ad blocker.

While cross-device technology has been around for a while, we’ve only just begun to activate it. As the number of screens in front of consumers continues to grow, the industry must work quickly to develop standards that empower media buyers to evaluate and leverage this technology to shift to a true audience-based approach. In the meantime , it’s important to be educated on the topic in order to make the best possible buying decisions.

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How Cross-Device Identity Matching Works (part 1)

August 12, 2016 in Blog

Martin Kihn at Gartner provides a great primer and explanation of Adelphic’s patented methodology for cross-device identity matching.

Cross-device identity is the thing that tells marketers and other nosy types that Device A and Device B and Browser C all belong to the same Person X. Devices (and browsers, which we’ll call devices for convenience) are matched to people. These people may be known to us by name or they may remain quite mysterious. But here we are concerned only with the process of matching devices together that all point to someone.

How is this done?

Talking to our friends at Adelphic recently, they clued us in to their U.S. Patent 8,438,184 B1. Adelphic is a mobile demand side platform, in the business of helping advertisers target people mainly on mobile devices, so they’re interested in identity. Why? If they’ve served an ad to Person X on Device A, they’d like to know that fact before they bid good money on yet another ad to the same person on Device B. Or if they happen to know something interesting about Person X (say, they like Bernese mountain dogs), then when that person shows up on a new Device C, Adelphic can put in a high bid for their Bernese mountain dog tea cozy-selling client.

Boom! But only – of course – if they know that Devices A, B and C all belong to the same Bernese mountain dog lover Marty, I mean, Person X.

How? That’s the topic of the patent, which I have read in some detail. (Patent reading is about as fun as going to Coney Island to count the sand, so you’re welcome.) I summarize highlights for the people.

ADELPHIC’S PATENT

It turns out that the “matcher” (e.g., Adelphic) is in the business of building up a large database of individuals. Each individual has a unique identifer (we can call it the Master ID) and a set of known Attributes. These Attributes are things that the database knows about them based on previous interactions. And – importantly – this Master ID and set of Attributes also tries to include other ID’s that are uniquely tied to particular devices.

So at its core, the matcher is a system that is confronted with device identifiers that it bumps up against its Master ID database over and over in an attempt to see if that device belongs with an existing Master ID, i.e., a person they know. If not, a new Master ID is created and becomes part of the matching game.

Some of you may wonder: “Is it using deterministic or probabilistic methods?” The answer is: both.

First, it will try to determine if there is a literal match – that is, if the device identifier is already in the database. If so, there is a direct match that we call deterministic. If not, we need Plan B: probabilistic matching. Plan B uses some fancy math (which I will sketch out below) to figure out if the various Attributes it’s seeing are similar enough to Attributes in the Master ID database to make it PROBABLE we have a match.

If not, rinse and repeat: New Master ID, attached to these Attributes, and associated with the device ID.

Simplified Version of Match Process

Simplified Version of Match Process

This is all somewhat less mystical than it sounds. I will take a moment here to list the specific pieces of information that Adelphic’s patent mentions. It’s interesting because it shows how sparse info can get in ad tech.

Deterministic matches are commonly made by finding one-to-one identity with:

  • Cookie – any unique browser cookie set by the advertiser or its agents, like a DSP
  • Phone number
  • Email address
  • UserID – explicit identifier that is similar to a cookie, known only by advertiser or its agents
  • Device ID – some of the ones listed in the patent don’t exist anymore (like Apple’s beloved UDID and various open standards that didn’t take); practically, this is limited to ADID and IDFA available only to app developers for Android and IoS

These identifiers are often sent with the HTTP request as a query parameter. This means something that looks like a URL is sent to the matcher’s server and it contains a string after the matcher’s address, like:

www.matcher.com/api/identityrequest?cookie=XYX2883838383aasdf;email=person@site.com

The matcher has set up an API that can be pinged with this request. It sends back a match (if it exists) and other relevant info (ditto). Of course, many times a marketer will not have an email, phone number or even known cookie. In practice, this kind of deterministic identity is useful for people who have explicitly given us information – usually because they are a customer or prospect – and this is stored either in their browser (e.g., cookie) or on the web page itself (e.g., email).

Most people will not have a deterministic identifier attached to their API request. So we go to probabilistic matching. Here the matcher will use any and all information it can find. Some of it is simply the kind of information that is always sent back and forth when machines on the internet communicate. This information is contained in the IAB specs and is routinely part of any exchange of data on the wires.

It comes in two flavors: device and system data; and so-called behavioral data.

Device and system data spelled out by the patent include:

  • OS type and version
  • Device brand and model
  • Clock setting
  • Time zone
  • Speed
  • Language default

These seem quite mundane but contain more information than we think. OS versions can get very specific. While default language = english doesn’t say much, I’ve heard that clock settings down to multiple decimal points can be quite revealing.

Then there is so-called behavioral data. (I say “so-called” because it isn’t always about what we humans call behaviors.)

Attribute data of this type are:

  • HTTP header – this is hidden text sent with the HTTP request and includes things like the date and time, characters accepted, various settings
  • User agent – the browser and version
  • App launch time
  • Page load time
  • Referrer – previous page visited is usually stored in the browser
  • Plug-ins used
  • Geography (latititude / longitude)
  • URL – specific page person is on; this can also be visited to determine the type of content being viewed (more on this below)
  • Typing frequency
  • Gesture – these last two apply to apps, if you can capture some patterns in the person’s interaction with the app; I have no idea how often this is used and can’t find any real information about it, other than the obvious fact that people can have different typing frequencies and gestures. (If you know, DM me at @martykihn or comment below.)

This does not seem like a whole lot of information to describe a unique person, and it isn’t. But combined, it can be helpful. For example, if I open a browser and visit a Bernese mountain dog site and my referrer is a Crossfit gym in Bedford Hills, NY – well, that’s pretty unique. If I did the same thing on my iPad last week – which, to be honest, I probably did – there exists a MasterID with those behavioral Attributes and (assuming there are not thousands of people who do exactly the same thing, which there are NOT) the matcher can call us a likely match. Based purely on a URL and a Referrer.

To view the article in its entirety, visit Gartner.

 

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Q&A with Adelphic’s GM of the Americas, Jacqueline Berg

June 27, 2016 in Blog

Adelphic’s new GM of the Americas lends her perspective on a range of important issues facing the advertising industry

What attracted you to Adelphic? How did you view the company?

Jackie Berg: I was looking for a start up company with a strong management team and a good tech foundation where I could have an impact. I initially viewed Adelphic as an innovative mobile-first company but it quickly became jackie-bergclear they were well beyond a mobile DSP. They had great talent across the organization and innovative ways of recognizing audiences across channels which empowers advertisers to achieve better performance.

You’ve watched the mobile industry declare “the year of mobile” for more than a decade. Now mobile is omnipresent in consumers’ lives, so why is mobile ad spend so low?

It’s natural for there to be a lag, so it’s not a question of if, but when marketers will do more than just dip their toes in the mobile waters. Agencies and marketers already know that mobile is indispensable for consumers, and the picture is becoming ever-more clear with regard to mobile campaign execution – they’re becoming more educated on mobile buying practices and attribution methodology and audience-centric targeting is more accessible than ever before. And as brands come to understand that a strong mobile strategy is the foundation for a successful cross-channel strategy, they will increase spend on mobile inventory, on their way to executing campaigns across an increasing number of screens. This is a huge opportunity that Adelphic is extremely well positioned to capitalize on.

You’ve worked with the giants who’ve helped shape digital and mobile. How does your time at these companies shape your perception of the mobile industry?

Throughout my career, I’ve seen many companies execute their ad campaigns across multiple screens and channels from siloed departments with a different sales and product team. But I’ve learned that a holistic approach is what will ultimately prevail. The cross-channel delivery that today’s technology enables is more reflective of how audiences interact with their devices and the media they engage with on them.

Is there an issue that you feel industry has yet to address that will impact its ability to grow?

Viewability measurement is in a mature stage in desktop, but it still needs to progress in mobile in order to build confidence for marketers looking to take advantage of all the channel affords. In addition, marketers and agencies need to continue pursuing attribution beyond the old “last click wins” methodology to ensure they are giving credit to all touchpoints in the consumer journey.

Finally, we all need to be concerned about fraud and invalid traffic across all devices and channels, but vigilance, education and increased transparency will all help to keep these issues at bay.

What are brands looking for that the industry hasn’t delivered?

Brands want premium audiences programmatically and wish to reach them with engaging innovative ad formats, targeted data and across channels.

What are publishers looking for the industry has yet to support?

Since programmatic took the industry by storm, data has surpassed most other aspects of ad buying and selling in terms of importance. But with the proliferation of ad blocking, publishers are looking for other industry stakeholders to go back to their roots to develop thoughtful and creative ad design that enables strong brand performance, reduces consumers’ desire to implement ad blocking technologies and ultimately increases the value of publishers’ sites. To this effect, native has been a boon for publishers, but the innovation must continue. Creative execution continues to be a challenge for most.

Publishers are also looking for seamless PMP opportunities that yield increased control and returns worthy of the high-quality inventory up for grabs in this environment. They’re also eager to find header bidding-like solutions for mobile advertising as well as unique ways to monetize their data.

Cross-channel is the next direction for Adelphic. How do you see this strategy impacting marketers’ current marketing mix?

Marketers are recognizing that a cross-channel approach that is too focused on devices ignores the constituent who is actually making the purchase: the consumer. Adelphic is uniquely equipped to engage audiences due to our behavior-centric approach, which takes into account their movements across a growing number of devices.

As marketers understand the role of new and emerging channels, budgets will shift to match consumer behaviors and marketing mixes will be more balanced with relation to true ROI. Marketers of tomorrow will no longer designate specific budgets to channels–instead, they will allocate a single cross-channel budget and look to a technology platform that can automatically allocate the media mix based on delivery and on performance.

What role will data play in the cross channel movement?

Marketers are increasingly bringing their own first-party data to the table and expect partners to be able to ingest and analyze that data along with second and third party data in order to reach consumers in real-time, when and where it counts most.

Platforms like Adelphic, which are designed to process and make decisions based on multiple data sources and formats, and at large scale, are well positioned to deliver and perform on people-centric cross channel campaigns.

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Real-Time Banter: Adelphic and BrightRoll Discuss Mobile Marketing

May 19, 2016 in Blog

This edition of Real-Time Banter features a conversation about mobile marketing with Dan Mosher, VP & GM of BrightRoll Exchange at Yahoo. Dan was interviewed by Jennifer Lum, Chief Strategy Officer for Adelphic.

dan-mosher

Jennifer: What is BrightRoll Exchange?

Dan: The BrightRoll Exchange seamlessly connects large pools of inventory with all of our top buyers which includes DSPs, brands and agency trading desks. The exchange connects more than 100 DSPs to some of our highest quality inventory sources across video, display and native, where we bring in not only Yahoo owned an operated inventory, but other high quality inventory sources.

Is Yahoo O&O inventory already available in the exchange?

It’s already in the exchange. That was one of the key tenets of the deal when we signed it more than a year ago, and when we closed it, we made the Yahoo video inventory available in the exchange instantaneously. Yahoo display inventory has been available in the exchange for years. We have now rebranded the overall exchange, display, video and native, to the BrightRoll Exchange.

What is your role at BrightRoll?

I run the exchange business, which is all of the programmatic buyers on the exchange.

How has the role of the BrightRoll platform evolved since the Yahoo acquisition in 2014?

Well the biggest thing that we formalized after the acquisition was the separation of the BrightRoll DSP business from the BrightRoll Exchange business.. The way that each platform has evolved has been to add Yahoo’s display capabilities into what was core BrightRoll video capabilities. The BrightRoll DSP now provides multichannel access for all of our self service customers – access to all sorts of inventory across different sources using Yahoo data. That was the big evolution of the platform: Yahoo’s data is available for our DSP customers, and that they use on a customized basis for their campaigns. The BrightRoll Exchange has evolved to include display inventory, and now includes native inventory as well. We were able to bring on those high quality sources of inventory that were the Yahoo owned and operated inventory and we continued to upgrade our inventory sources post acquisition as well. The platform has really evolved around those facets, and now we have, on the Exchange side, one team that interacts with our top customers, no matter what type of format they want to buy, via display, native or video..

You mentioned that Yahoo audience data is now available through the BrightRoll DSP. Will Yahoo audience data become available through the BrightRoll Exchange?

Yes, it is available today, however, it’s not available in the same way that its available for our DSP customers, where they can pick, choose and customize the data segments that they want to use. Instead, we expose specific segments through the exchange to our top brand partners buying through a third party DSP via Deal ID. For example, we’ve recently provisioned an “LDA” deal (legal drinking age), where we use Yahoo data to create a segment of customers that is over 21. We know that the Yahoo data is extremely effective and precise, so we’ve had a couple of customers set up deal IDs on the BrightRoll Exchange where they were able to access only legal drinking age customers using the data. So there will be segments like that, specific deal IDs that might be behavioral or intent segments where we may pull in different elements, but its not going to be the broad-based way that it’s available on the DSP.

How has Flurry inventory data been integrated into the BrightRoll Exchange?

Flurry had three parts to its business when it was acquired by Yahoo. One was a display and video mobile inventory piece, a nascent native segment and the rich data that it receives based on having its analytics SDK installed on thousands of apps. We’ve integrated the Flurry mobile video inventory into the BrightRoll Exchange, so Flurry inventory is now available to any of our mobile video customers who are buying on the BrightRoll Exchange. The next step will be to include some of the native inventory that was previously available via Flurry, in the BrightRoll Exchange as well. Those are the pieces we’re most focused on. Flurry has its powerful SDK on thousands and thousands of apps, which gives our DSP buyers some interesting data insights but this is not available on the exchange today. These publishers are seeing the native advertisements perform better, and have better monetization capabilities. We are going to be able to leverage that native inventory in the BrightRoll Exchange in 2016.

Will the Flurry SDK become the unified mobile SDK for the supply side?

The Flurry SDK is where a lot of the development effort is going right now and we will continue to evolve and build it out. Because the third-party inventory and SDK footprint that we have today is quite extensive, the question now is, “How do we build more robust publisher tools that leverage some of the things we have in place?” Because Flurry has a set of publisher tools, BrightRoll on the video side has a set of publisher tools, and Yahoo has its own set of publishers, how do we bring all of those together as a seamless publisher offering? On the mobile side, Flurry and its SDK is clearly the most compelling piece that we have right now and we will double down on that for our supply side business.

How has publishers’ use of programmatic changed since you launched the BrightRoll Exchange?

We launched the BrightRoll Exchange in 2010, and that was really early days in exchanges. I’d say, and I remember this because I was making all of the calls to publishers back then trying to convince them to expose their inventory on our exchange, that they were worried about exchanges in general and thought they might commoditize their inventory. Early on, publishers were reluctant to make their inventory available on the exchange. The views have evolved quite a bit in the last five years. I think most publishers now look at offering their inventory programmatically, through an exchange, as a key facet of how they go to market, and how they monetize. It’s been a method for publishers to lessen the reliance on a direct sales force in some cases, because they can monetize through exchanges. Exchange technology has evolved in a way where a publisher can expose its inventory via private marketplace and have the same level of control that they’ve always had when they were just selling it in-house and didn’t have to adapt or expose it to any exchanges. It’s now a key part of every publisher’s go to market. Some will expose 10 percent of their inventory, whereas some will expose 90 percent of their inventory. It really depends on the publishers themselves, but the views have changed quite a bit, and I think it’s because there is a lot more control and tools they can use to make sure that their inventory is exposed only to the buyers that they deem to be acceptable upfront.

How does BrightRoll address fraudulent traffic?

We have recently launched a partnership with White Ops, which is one of the top anti-fraud companies in the video space. We now have White Ops technology running on every request that we see from any publisher. We’ve deployed that across all of our video impressions and to make sure that no impressions or very few impressions are delivered against invalid traffic. We also have our own internal tools that we’ve been developing for years to assess invalid traffic. We have our internal tools because no one tool is a panacea, but White Ops is one of the top vendors we could’ve worked with. That augments the tools that we already had in-house, but we feel like that puts us in a good position to really assess and make sure we’re limiting and reducing dramatically the amount of invalid traffic that buyers are seeing.

Have you found that different tactics are required to address fraud in mobile versus desktop?

Yes, definitely. The technology is very different in mobile. The way that fraud manifests itself in mobile is different in terms of the type of things that fraudsters do. Third-party vendors aren’t necessarily up to speed on mobile yet, so I think it’s like any technology we’ve looked at. We looked at viewability early on. If we looked at Nielsen and comScore assessments of different traffic, mobile was always a follower on a lot of those things, and I think in the fraud side it seems to be as well, where the third-party vendors aren’t as strong. Our internal publisher team has a lot of really good tools at its disposal to evaluate mobile traffic and look for any inconsistencies that we might deem to be evidence of fraud. We are using all of our internal tools to evaluate mobile traffic. We are evaluating third-party vendors to see when there will be one where we can layer on mobile like we’ve done with desktop.

What is the split in demand that you’re seeing between open exchange, private marketplace and programmatic direct, specifically with mobile demand?

We’ve seen quite an evolution over the last couple of years. We’ve just launched a private marketplace, in earnest, on the video side of our exchange over the last couple of months, and that’s for both mobile and desktop. We’ve seen already that programmatic direct and private marketplaces are 20-30 percent of exchange revenue so it’s gone from zero to 20-30 percent over the last couple of months, which is a large increase. Some of the buyers that we work with who have been doing private marketplaces for a while say they took it up to 40 percent, in some cases. So, we think right now we’re at 25 percent private marketplace. I think that can continue to take up at least up to a third of the business as buyers are more and more interested accessing specific pools of inventory where they know more up front about the inventory than when just buying it in the open exchange. In some cases they’ve done a specific deal with the publisher and we are just instrumenting that deal through our exchange, or more likely, they are accessing curated packages of inventory that provides a specific type of function and/or a specific purpose within a campaign.

PMPs and programmatic direct represent a different control mechanism, not only to control but to lock in inventory during a period of high demand and also influence consistency around pricing.

Right. One of the big promises of PMP and programmatic direct is the ability to negotiate the price up front, within a certain range. We still have programmatic direct relationships where there could be multiple bidders and there’s some type of bidding happening, but within a specific range and they have a sense up front of what the pricing is that they’re going to try to achieve. In some cases to get that privilege they have to pay up higher than what they would have otherwise in the open exchange but they trade that for visibility and comfort that their campaigns will deliver.

Two more questions, they’re both personal and fun. First question, do you use an iPhone or an Android?

I use an iPhone. I used to be an Android user. Tod Sacerdoti, the CEO and founder of BrightRoll, is an avid Apple fan boy and gave me a lot of crap about my Android phone. I think I finally succumbed sometime in 2012, when the iPhone 5 rolled out and I had to try it.

 Does the entire BrightRoll management team use iPhones?

Most of the BrightRoll management team uses an iPhone, I would postulate. I think a couple of the holdouts were told to get on the bus! But Yahoo as a company really encourages iPhones as well because of the prevalence of our apps. iOS is still a better monetization platform from what we understand on a per-user basis, and so I think most of the people around here, from my assessment, seem to have iPhone versus Androids.

What is the first app you open everyday?

Well it has to be the Yahoo! Mail app yahoo-mailbecause that’s certainly the app that I check most frequently, not only first thing in the morning, but also during the day. It has gone through a lot of evolutions over even the last 16 months that we’ve been here, it’s been upgraded significantly. But really I’m just checking to see what my numbers were the day before, and I get a good email every morning bright and early so that’s the first thing I check when I wake up. “How did we do revenue-wise yesterday?”

 Thank you very much Dan, it was really great speaking with you.

 

 

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