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2016 Edition: A Marketer’s Guide to Cross-Device Identification

February 29, 2016 in News

Cross-Device IdentificationIt’s been a busy 10 months since AdExchanger published its inaugural Marketer’s Guide to Cross-Device Identification. Since then the market has seen significant developments, including technology evolution, merger activity and shots across the bow from government regulators.

Below, we pick up where we left off with an important update to our overview of the cross-device landscape.

As device fragmentation increases, so has the industry’s adoption of cross-device technology.

“We were talking about the cookie – now we’re talking about cross-device identification,” said Brian Anderson, a partner at LUMA Partners, speaking at AdExchanger’s Industry Preview event in January. “[Cross-device] is a critical component in the marketplace in order to provide mass personalization.”

It might be folly to call 2016 the “year of cross-device.” As Mike Juhas, senior director of sales at CPXi-owned AdReady, noted, “The bottom line is that cross-device strategy should be an integral part of any scalable campaign and not be considered this year’s hot new thing.”

Regardless, as time spent on mobile continues going up and to the right, cross-device technology is in the spotlight as marketers start to ramp up their spend in a material way.

But significant challenges remain, including privacy issues, reach vs. accuracy and the thorny little matter of the Internet of Things.

A Quick Recap Before Diving In

There are two primary methods used to establish user identity across devices – deterministic and probabilistic.

Deterministic matching taps into known user data to make a match, generally an email address used to log into multiple devices. (Think Facebook, Google, Amazon, Twitter, AOL.)

The probabilistic approach draws on a variety of anonymized data signals like IP address, device type, browser type, location and operating system to create likely statistical connections between devices. (Think Drawbridge, the recently acquired Tapad, Crosswise, Adelphic, Adbrain.)

Probabilistic ID vendors will often use what is called a truth set – a core of licensed deterministic data – to train their algorithm over time.

That makes it sound pretty black and white – but it isn’t.

There is also a growing trend around data companies like Oracle and LiveRamp adopting a blended approach, using a combination of probabilistic to complement their deterministic matching capabilities in an attempt to reach the scale of players like Facebook and Google.

akindergarden_2As LiveRamp product VP Anneka Gupta told AdExchanger in November when LiveRamp revealed its partnership with Drawbridge, “[This is] becoming really important in channels like mobile where it takes more time to aggregate enough deterministic data to have significant reach.”

Walled Gardens

The deterministic players – mainly Facebook with Atlas and Google, which finally came out with its own cross-device solution in June after months of speculation – are often referred to as walled gardens, aka enticing and effective Shangri-La playgrounds of near-perfect cross-device identity matches where marketers can achieve both scale and accuracy with one noteworthy catch: Marketers can’t take their insights with them. What happens in a walled garden stays in a walled garden and can’t be used to inform campaigns elsewhere.

Although marketers generally find this state of affairs frustrating, it hasn’t stopped them from spending with the big guys, as clearly evidenced by Facebook’s and Google’s respective blockbuster Q4s.

Facebook has demurred that it’s all in the name of privacy. Patrick Harris, Facebook’s director of global agency development, has said that if he had his druthers he would replace the term “walled garden” with “privacy garden.” (It hasn’t caught on.)

The Privacy Question (With No Clear Answer)

The proliferation of devices has made it harder – in fact, near impossible – for consumers to opt out across devices.

Cookie-based opt-outs are half a headache. As Adobe privacy product manager Vinay Goel acknowledged on a June conference call with brand clients and partners about its then forthcoming cross-device data co-op product, “If you clear your cookies and then the consumer comes back to the site, they are being targeted and profiled again. This is one of the limitations and challenges with cookie-based opt-outs.”

Although self-regulatory programs like AdChoices and AppChoices, created by the Digital Advertising Alliance (DAA), aim to help consumers get a handle on where their data is being used, there are obvious limitations.

For one, the opt-out process requires an heroic amount of effort and industriousness on the user’s part. Users who want to opt out have to do so on a per-browser, per-device basis – and then diligently maintain their preferences. It’s asking a lot.

The industry is just “not there yet” when it comes to universal opt-out, admitted Genie Barton, VP and director of the Council of Better Business Bureaus’ Online Interest-Based Advertising Accountability Program. Barton was speaking during a panel discussion at the Federal Trade Commission’s (FTC) November workshop on cross-device tracking in Washington, DC, attended by policymakers, academics, privacy researchers, technologists and ad industry reps.

“When folks in the advertising space talk about scaling up cross-device tracking in an exchange, they tend to be talking about a probabilistic solution and that introduces some challenges,” said Jonathan Mayer, privacy advocate and newly minted Federal Communications Commission chief technologist, in a previous interview with AdExchanger. “If they offer an opt-out, they can only do so with a likelihood, but no guarantee, that the opt-out will transfer to other devices.”

The FTC Digs In

The FTC’s cross-device workshop was a watershed moment, making it clear that the commission, although not motivated to regulate, has its eye on the industry.

As is its wont, the FTC attacked the issue from the consumer protection perspective.

“I think it’s fair to say this area is evolving rapidly and may be … challenging traditional consumer expectations about their privacy,” said Justin Brookman, policy director of the FTC’s Office of Technology Research and Investigation, at the workshop.

optoutsFor research purposes, Brookman and his team ran a mini analysis of the top 20 sites for news, sports, shopping, games and reference (100 sites in all) to see if they could tell when cross-device tracking is happening.
“We spent days trying to get a sense of what’s going on,” Brookman said. “It’s really hard to determine objectively, from the end user point of view, when cross-device tracking is going on … [And] that raises the question: How much transparency should there be? What do consumers expect? Do they want to be overloaded with information? If cross-device tracking is going on, what should consumers be told and how?”

The industry is still hashing all of that out, but some consumers aren’t waiting to sharpen their pitchforks.

The FTC accepted public comments on cross-device in the months leading up to and the month following the workshop.

A number of respondents had choice words for the ad industry, including James from New York, who said: “Please make an effort to inhibit the intrusion of almost anyone into the lives of almost everyone.” Paula from Georgia was even more to the point: “‘Relevant’ advertising is a negative for me – not a positive. Please make sure my privacy is more important than the almighty dollar!”

The Thing Is…

There’s another question to add to the end of Brookman’s list: What are the privacy implications of cross-device tracking when the Internet of Things enters the scene? Arguably, anything that gives off a signal is fair game for the device graph, whether it’s an Apple Watch or a connected toothbrush.

But before the proverbial smart toaster becomes a fixture in the kitchen, smart TVs are getting comfy in the living room. By 2019, smart TVs are slated to make their way into more than 50% of TV viewing households across the US, UK and Japan, according to recent research from IHS.

In November, right before the FTC’s cross-device workshop, an article in ProPublica called attention to the fact that smart TV maker Vizio had updated its privacy policy to say it had begun collecting and sharing cross-device user data with advertisers. Users who weren’t interested had to proactively opt out.

A few days after that, a piece in Ars Technica decried a practice known as audio beaconing, which takes advantage of inaudible, high-frequency sounds embedded in ads to track user behavior across devices, including TVs, phones and tablets.

Both scenarios call attention to the thorny issue of what notice and choice, aka privacy policies, should look like in a world where anything that can be connected to the Internet will be connected to the Internet.

The cross-device landscape is still either the privacy Wild West or a hotbed of innovation, depending on your perspective. And, privacy policies, rather than the privacy safeguards most consumers believe them to be, are really just legal documents for companies to protect their derrieres in the case of a breach.

(According to research from University of Pennsylvania professor and privacy pundit Joseph Turow, between 55% and 65% of US consumers believe that when a website has a privacy policy it means that site won’t share user data with other companies, which is patently untrue.)

“We fully understand the important part that innovation plays … [but] if you’re looking at your TV kind of side-eyed and worry about what’s going on there, that could turn into a dangerous spiral,” the FTC’s Brookman observed at an International Association of Privacy Professionals event in November. “For consumers, everything they own is a little black box and we’re trying to make sure that their interests are provided for.”

Reach vs. Accuracy

Privacy issues aside, the industry is dealing with its own issues, namely how to strike the right balance between reach and accuracy.

A device graph – the mapped connections between devices – is only as effective as its ability to find a lot of matches (reach) with a level of statistically relevant precision (accuracy).

For companies that aren’t deterministic titans like Facebook or Google with both scale and accuracy, one usually has to suffer in favor of the other. If a marketer wants reach, match accuracy usually goes down. If a marketer wants exactitude, scale goes out the window.

There’s an extra nuance there, though. As Tim Abraham, director of data platforms at Adbrain, explained:

“Accuracy is a metric that doesn’t necessarily mean what people think it does. In the context of cross-device identification, accuracy is calculated as the number of matches correctly identified, as well as the number of non-matches correctly identified. In other words, it’s the number of times a probabilistic prediction was correct, but also includes ‘non-match’ predictions from the total pool of predictions it made. Marketers don’t care very much about the non-match predictions because they want the predictions of correct device matches. But there will actually be many more non-matches than correct matches, so this massively skews the accuracy score, making it look much better than it really is.”

In other words, device graphs are getting credit for being accurate about inaccuracies. It’s a head-scratcher.

So is the fact that the two primarily probabilistic device graphs on the market have been verified by Nielsen as being insanely accurate. According to Nielsen, Tapad’s cross-device connections are 91.2% accurate, while Drawbridge received a 97.3% accuracy score.

To put that into perspective, when AOL worked with comScore on a verification project in 2014, the results came in at 93% accurate – and that’s for a deterministic data set.

How, then, were the Tapad and Drawbridge numbers so high? The answer could lie in the subtle difference between accuracy rate and match rate. While the match rate is defined as how many times one is able to correctly connect two or more devices, the accuracy rate includes correctly identified non-matches.

Nielsen compared samples from both the Tapad graph and the Drawbridge graph to data from its own third-party panel as the truth set.

In the test with Nielsen, Drawbridge’s accuracy rate was 97.3%, but its match rate was 10.3%. (Tapad didn’t publicly release its match rate.)

Tyler Pietz, a VP and programmatic strategist at IPG trading desk Cadreon, explained it like this: “For the purposes of a study, it’s pretty easy to focus on the stats that position you in the best possible light – but you can’t provide a 10% match rate for an advertiser. … To put this in context, if an advertiser has a pool of 100 desktop cookies and wishes to find a corresponding mobile device for each, then a 10% match rate would equate to identifying a match device for 10 out of the initial pool of 100 desktop cookies.”

There is a fair amount of skepticism in the industry around probabilistic methods and whether cross-device recognition and targeting is as advanced as the vendors who sell it claim.

firstdance1As evidenced with AOL’s comScore number, even deterministic matching isn’t 100% accurate 100% of the time.

Cross-Device Consolidation

But that hasn’t dampened M&A in the cross-device space.

The biggest move by far was Verizon’s $4.4 billion acquisition of AOL in May. Verizon is no noob to the cross-device game. In 2012, Verizon Wireless rolled out an addressable advertising division in the form of Precision Market Insights, whose stated goal is to solve for consumer identity using mobile.

Verizon’s move to snap up AOL looks like a clear sign that the telecom wants to go toe to toe with Facebook and Google.

Telecoms feel like they’ve been “missing out on the marketing action that Facebook and Google have dominated for a long time,” said Kamakshi Sivaramakrishnan, CEO of Drawbridge. “They’re awakening to the fact that data has been transacting on their networks, but they have had no real piece of it. This is the first step in creating a strong digital presence, and the next step is connecting the devices, either using technology or in a more explicit manner. … The carriers will be very active acquirers in the near future.”

Prescient words. In January, Drawbridge’s top competitor, Tapad, was acquired by Norwegian mobile carrier Telenor for $360 million.

Telcos see lucrative potential in cross-device recognition and targeting, wrote Matt Keiser, CEO of programmatic email platform LiveIntent.

Keiser elucidated his point with a ”Wheel of Fortune” reference in a recent column for AdExchanger:

“Verizon and Telenor have the consonants of deterministic data, in terms of the actual devices and their respective anonymized IDs. They recognize the biggest opportunity is having the option to dial up accuracy or scale to best serve marketers across devices and channels. So they went shopping for vowels, which took the form of AOL and Tapad, respectively. For me, buying letters to get closer to solving the puzzle in ‘Wheel of Fortune’ is the most obvious parallel to cross-device. It’s just the ‘Tip _f th_ ic_b_rg.’”

Also in January, Verizon Ventures, the investment arm of Verizon Communications, sunk $5.5 million into intent-targeting platform Qualia, which recently merged with cross-device vendor BlueCava in an effort to capitalize on the combination of their respective data signals.

It’s a sign of the times, Verizon Ventures executive director Mark Smith told AdExchanger.

“Being able to take intent data and on a real-time basis look at where those consumers are going across screens is vital, because no action today is done in isolation,” Smith said. “Combined, they’re addressing how you can begin to piece together a story around ad decisioning and provide attribution about how a [mobile] exposure contributed to a sale or other action.”

To read the article in its entirety, visit AdExchanger.

The post 2016 Edition: A Marketer’s Guide to Cross-Device Identification appeared first on Adelphic.

What Marketers Need to Understand About Cross-Device Advertising Reach and Accuracy

January 22, 2016 in News

cross-device advertisingAdvertisers are understandably looking for scale with their cross-device advertising campaigns – but when they ask for it at the expense of accuracy, that’s a problem.

“The marketer has erred on the side of reach, but reach and frequency are a tradeoff,” said Omar Tawakol, SVP and GM of Oracle Data Cloud, speaking at a panel during AdExchanger’s Industry Preview conference Wednesday in New York City.

In other words, pretty much any cross-device identity graph – other than, perhaps, Facebook’s – is a compromise between getting it right and getting it right at scale. And for cross-device advertising recognition or targeting to be successful, you need both of those cylinders firing.

But advertisers often evaluate vendors based on reach because it’s an easier metric to grasp.

“Just give me a number, tell me how many devices you can give me when I give you a set of cookies – it’s really easy,” Tawakol said. “But when you talk about accuracy, people don’t even really understand how to prioritize [it] or what truth sets they’re going to use.”

While Facebook can use deterministic data to link multiple devices to individual users, other cross-device vendors in the space generally rely on probabilistic techniques to create their connections.

Of course, advertisers can also bring their own first-party data to the party – LendingTree, for example, recently created a login experience to collect registration data and get insight into the customer journey, said Nitin Bhutani, VP of marketing at LendingTree – but scale is an issue.

In a probabilistic setting, where matches are being made using statistical algorithms, expanding reach can mean sacrificing accuracy.

In general, though, marketers have “to get smarter [and] ask questions about accuracy,” or they’re going to “force the wrong behavior with vendors,” Tawakol said. “Think about what your vendor is going to do in the cross-device space if the next time you meet with them you say, ‘Well, this other vendor has slightly higher reach.”

If marketers demand reach, that’s what the vendors are going to provide them with.

“Well, I’m going to start a device ID graph company tomorrow and say everyone on the planet is connected – maximum reach,” Tawakol joked. “It’s ridiculous.”

That said, reach and accuracy don’t necessarily have to sit on opposite ends of the seesaw if vendors use a combination of deterministic and probabilistic methods, Tawakol said.

‘We all want to use deterministic, but there is nowhere near enough matches to do that,” he said. “We need to do more of a data science approach that takes what you know and scores it probabilistically.”

But what about Facebook and Google? They’ve got serious deterministic mojo, obviously, but the rest of the industry isn’t licked.

“Their scale and reach at this point is unbeatable and the amount of verified registration data they have is top notch, but they don’t have full coverage for cross-device yet,” said Jennifer Lum, co-founder and chief strategy officer at Adelphic. “[And] they have work to do in TV and on the mobile web.”

None of the debate around consumer identity matters, though, if brands don’t consider what they’re going to do once they’ve created the cross-device match.

“All of the companies we work with have varying levels of fantastic first-party data and access to third-party data and, increasingly, we’re helping brands work together to generate significant second-party data,” said Matt Asay, VP of mobile at Adobe. “But, stepping back from that, the most important thing for any brand is not, I’m sorry, which ad you show the person – it’s the overall experience that consumer has with that brand.”

To read the article in its entirety, visit AdExchanger.

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The Cross-Device Advertising Conundrum of 2016

January 21, 2016 in News

cross-device advertisingWith people using something like four to six devices through the course of one day, it’s hard for marketers to track the user experience for cross-device advertising.

Omar Tawakol, GVP and GM, Oracle Data Cloud, Oracle, said fragmentation is getting worse, not better. “There’s no way for you to accurately attribute anything,” he said. “You’ve got to tie this stuff together. it’s essential to what we do.”

Tawakol was part of “Cross-Device Advertising 2016,” at AdExchanger’s Industry Preview Wednesday. The panel, moderated by Martin Kihn, Gartner’s research director, set out to determine the challenges and opportunities as marketers try to reach customers on their many different devices.

Of course, attribution is a key issue — and it’s not all bad news.

Jennifer Lum, co-founder and CSO, Adelphic, explained why this future is bright: “Cross-device is so exciting because we’re approaching a point when we’re starting to paint a full picture of consumers’ waking day,” Lum said. “You can leverage that data to decide how and when you want to engage with consumers.” To get to that future, Tawakol said, the market has to get smarter about accuracy without forcing the wrong behavior on vendors, embracing an integrated data science approach.

Nitin Bhutani, VP-marketing, LendingTree, is hopeful about cross-device, too. He said that maybe two years down the line, we could be using one main device (in lieu of a separate phone and laptop), and all our data might be stored in the cloud. In an ideal world, Facebook and Google would share their data with marketers looking to track customers’ digital and physical purchase journeys.

Lum added by emailed comment that if Facebook and Google (two players with scale, reach and verified registration data) were to be cross-device enablers instead of keeping their data walled in, they could possibly make more targeting data available to third-party platforms, with the ultimate benefit an increase in programmatic media sales.

And there’s always the option of asking for user data, which certainly helps connect the dots. Matt Asay, VP-mobile, Adobe, said asking for data should be looked at through the prism of “What is the customer going to experience with that brand?”

“The only reason [customers] are going to give you their data is if they trust you, and you’re giving them something in return,” he added.

Read the article in its entirety at AdExchanger.

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Cross-Device Advertising Offers Political Advertisers Great Promise & Significant Challenges

January 13, 2016 in News

cross-device advertisingThe 2016 election promises to be exciting not only in politics, but also in the world of cross-device advertising. For the first time, political mobile and cross-device advertising will play a significant part in the advertiser media mix.

Historically, political campaigns were challenging because of lack of ability to precisely target registered, prospective and on-the-fence voters. But in the 2016 election, candidates will be able to reach voters with more relevant and engaging campaigns, due to advancements in advertising technology and user identification.

While significant developments have been made in deterministic and probabilistic user identification, however, the industry still needs to conquer measurement, privacy and other challenges before it can realize the full potential of cross-device for political advertising.

Historical Challenges Of Election Campaigns

Political views are deeply ingrained. In recent years, scientific thinking has emerged that a person’s political views are in direct correlation to a person’s personality or genetics. Therefore, targeting users on-message in a political campaign is more important than ever. Failing to deliver political ads with pinpoint precision can create wasted ad spend and campaigns that are at best irrelevant, and at worst laughable.

In the 2004 and 2008 elections, advertising was entirely contextual, with media buyers placing deals on sites or ad networks as a proxy for audiences. Although innovative at the time, this type of contextual-only buying was highly wasteful, especially for political campaigns. The 2012 election year signaled the emergence of demand-side platforms (DSPs) and the promise of audience buying at scale, but early DSPs were slow to adopt the technical and policy changes necessary to incorporate political audience segments into their platforms. In addition, early DSPs used cookies for targeting and measurement, making them unreliable in mobile and across multiple devices.

Another historical challenge for political campaigns: location targeting. In a presidential campaign, the focus is on high-value swing states, such as Ohio, Florida, Colorado, Nevada, Virginia, North Carolina and Iowa. Ad targeting must go a level deeper, down to the congressional districts that act as the fulcrum point for the entire state. While early DSPs included capabilities to target users based on state, city, ZIP code and DMA, they lacked the precision to target congressional districts, which are irregularly shaped and can include an overlap of multiple ZIP codes.

Mobile Location: Getting Better

Going into the 2016 election year, the ecosystem has matured to improve the precision and relevance of political advertising. New technical capabilities allow marketers to go beyond the cookie and IP address. Advertisers can now target prospective voters based on their mobile location, as well as probabilistic and deterministic user identification, all of which can fuel high-performing mobile and cross-device campaigns.

Mobile location signals, consisting of latitude and longitude data points, increase the precision of targeting prospective voters. By using latitude and longitude signals, custom polygons may be created for targeting users at the time the ad is served, as well as based on past location history. Latitude and longitude targeting allows media buyers to reach users with precision inside congressional districts.

Yet, these signals are fraught with problems, leading the marketing industry to demand greater transparency around latitude and longitude data integrity and validation. The majority of latitude and longitude signals are dubious, forcing some mobile data partners, such as Factual, to go to great lengths to clean and validate latitude and longitude data. Marketers thirst not only for better measurement and verification of mobile signals, but for supply-side certification of inventory as well.

ID, Please

New advances in ad tech can also solve the challenge of precisely identifying voter audiences. Third-party data providers today feature robust political data segments. For example, Neustar and BlueKai offer targeting of political audiences, including segments of registered Republicans, Democrats, independents, voters in specific elections and on-the-fence prospective voters. Voter data files are matched to household IP address info and translated into registered, voted and undecided audience segments, which can be targeted on the open exchange and on specific sites and apps.

CRM data targeting can also prove instrumental in reaching prospective voters, with several large publishers now supporting the uploading of CRM data for targeting within their ecosystems. For example, voter and donor records containing email addresses can be hashed and uploaded into Facebook Custom Audiences for targeting prospective voters within Facebook. While precise, this type of deterministic targeting raises questions around user privacy; while matching is done on hashed “depersonalized” data, initial inputs like user email addresses are decidedly personally identifiable information. In addition, CRM targeting in Facebook, Twitter, Amazon and other publisher ecosystems are confined to the publisher’s own walled gardens.

A similar flavor of addressable targeting may also be done at scale via a third-party data provider or data management platform. For example, voter CRM data may be uploaded into Neustar or LiveRamp for activation everywhere a DSP has reach. While a compelling tactic, this type of targeting creates for open questions around data fidelity as data gets translated from CRM to digital identity to person.

Measurement Gaps

Lastly, advancements in attribution usher in the most exciting developments for political campaigns and the advertising landscape as a whole. By leveraging their expansive login data and device graphs, Google’s DoubleClick Campaign Manager and Facebook’s Atlas ad servers allow for seamless measurement of user path and conversion, even across multiple devices.

The key is accessing a turnkey integration with these leading ad server partners that allows for measurement of the efficacy of cross-device and mobile advertising efforts. A political advertiser will be able to measure voter engagement and conversion across multiple devices for the first time.

Still, some measurement gaps remain within these publishers’ walled gardens. For example, only Facebook’s Atlas ad server is allowed to fully serve and track ads inside the Facebook ecosystem. DoubleClick view tags are not allowed for Facebook Custom Audiences or in the Facebook mobile app. Twitter allows DoubleClick click tracking for promoted tweet products, but does not pass device IDs from its app into the ad server tags that enable cross-environment tracking.

So while publisher walled gardens promise a unified view of the customer journey, that view can also be difficult to assemble. Hopefully, this is just a temporary setback as the market naturally moves toward efficiency and consolidation.

The next election year will be exciting to marketers and voters alike. Marketers will have unprecedented ability to target users consistently across devices with unparalleled audience and location precision. In turn, prospective voters will see ads that are not only relevant, but also informational, engaging and influential for their future voting decisions.

Read the article in its entirety at AdExchanger.

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The Real Ad Tech Unicorns: Firms Run by Women in Technology

December 4, 2015 in News

Ad TechGo to any ad tech conference and you’ll find no line at the ladies’ room. The industry, like much of tech, is dominated in its executive ranks by men.

That’s what makes mobile DSP Adelphic unusual: Half of the company’s eight-person management team is female. Emily Del Greco, its head of sales, spent eight years at Google, where she helped build the company’s DSP business. Vp of product Yael Avidan is a Yahoo veteran, and Gina Kim, Adelphic’s vp of business development, led DMP sales at BlueKai and Oracle.

Getting there wasn’t the result of a specific tactic or quota, said Adelphic co-founder and chief strategy officer Jennifer Lum. “The goal was always to find and hire the best possible candidates. We’ve just done a better job of casting a broader net,” she said.

Attracting female talent gets easier the more women you hire. When Del Greco joined from Google in 2011 as Adelphic’s second senior executive, the perspective she brought to the hiring process made it easier to attract other female executives. “As a woman, you tend to perceive female candidates differently from how a male would,” Lum said. Female leaders are more likely to be seen by men as bossy or aggressive than as strong leaders, for example.

Ad tech’s challenge in attracting women is part of a bigger one facing tech companies generally. Digiday found in 2013 that out of the 35 executives at publicly traded ad tech companies, only three were female. The picture hasn’t changed much. Women represent just 2.9 percent of ad tech CEOs today, according to ad tech company Maxifier. That’s lower than the 4.8 percent of female CEOs at Fortune 500 companies overall.

 

But ad tech companies can no longer afford to not search for a wider base of talent, said Lum. As the ad tech space has evolved and gotten more competitive, it’s put a premium on talent, particularly on the sales side, that can do more than take potential clients out to dinner. Today’s ad tech companies are looking for “relationship builders,” who have deep knowledge of a company’s brand and product.

“Ad tech now is way more tech- and partnership-driven than it was before, so it’s attracting more people with different kinds of backgrounds in general,” Lum said. “Having a team that is uniform and looks and talks the same isn’t going to make you competitive against a team that’s diverse and able to connect and relate to partners on multiple levels.”

Lum couldn’t cite specific examples of how its gender-balanced management has helped Adelphic’s business. But she believes that having executives with diverse experiences gives the company more perspectives on which to base its decisions.

Despite Adelphic’s success on this front, Lum acknowledged that the company still has work to do. While 26 percent of the company’s staff is female, women represent just 13 percent of its engineering talent. She chalked this up to young women having fewer role models in technical careers and Adelphic being headquartered in Boston, where the overall talent pool is limited.

“We’re seeing a lot of positive conversation around changing the diversity balance, but the one thing that’s really needed is time,” she said. “This isn’t something that can be changed overnight.”

To read the article in its entirety, visit Digiday.

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xAd and Adelphic Enable Turnkey Mobile Programmatic Advertising Offering for Precise Location-Based Targeting at Scale

October 22, 2015 in News

Adelphic Extends Location Suite with New Seamless Integration with xAd

mobile programmatic advertising

Adelphic, the leading mobile and cross-channel demand-side platform (DSP), today announced it has partnered with xAd, the leading location platform that enables marketers to reach the right people based on the real places they visit every day. This new partnership enables seamless access to xAd’s location-based targeting, providing the first turnkey way of activating precise location with mobile programmatic advertising at scale through Adelphic’s platform.

This integration provides clients direct access to xAd’s new proprietary proximity targeting parameters – Nearby and Wider Reach – that automatically customize geofences based on the campaign category and insights from previous campaign performance. xAd’s location platform listens to 300 billion mobile ad impressions each month globally, filters and ranks data signals by geo-precision, then verifies the physical location and its geo-boundaries through a patent-pending technology called Blueprints™.

“As marketers gear up for the greatest commerce season of the year, xAd now offers the most automated and precise way to reach the right mobile audiences based on the campaign and category type, enabling marketers to take the guesswork out of location-based marketing,” said Dorothee Bergin, Director of Platform and Programmatic Partnerships at xAd. “Together, xAd and Adelphic are advancing the industry beyond ‘guess-and-check’ location targeting, which often takes days to optimize, by offering clients a better way to access and automate the most sophisticated location-based mobile targeting in real-time.”

Adelphic continues to be a leader in programmatic audience buying by providing marketers with access to sophisticated data products for targeting, optimization and measurement. “This partnership with xAd grants our clients access to a leader in the mobile location space with a truly seamless integration into the Adelphic platform,” said Emily Del Greco, VP of Sales for Adelphic. “Our enterprise buyers are excited about the frictionless workflow and we are committed to first-of-its-kind integrations of this type.”

To view the press release in its entirety, visit PRWeb.

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The 30 Most Powerful Women in Mobile Advertising, Featuring Adelphic’s Jennifer Lum

October 20, 2015 in News

mobile advertisingMen tend to dominate the mobile advertising world.

So each year we ask readers and companies to nominate who they think are the most influential women in the business. We also asked that they nominate at least one other competitor to ensure the list wasn’t self-serving. In addition, we also consulted with Erin “Mack” McKelvey, CEO of SalientMG, whose knowledge of the mobile ad business far exceeds our own.

This is, by no means, a complete list of all the influential women in the mobile advertising business. It is, however, a representation of some of the most powerful women out there, who are running big businesses, with large client bases, and sizeable revenues to report.

23. Jennifer Lum, co-founder of Adelphic

As well as serving as chief strategy officer of Adelphic, Lum is also an angel investor and startup advisor to companies such as Burstly, which was acquired by Apple (Lum’s former employer.)

Adelphic’s main point of difference is user identification, no matter which device they are using.

The company has yet to reveal its revenues, but it raised $11 million in Series B funding late last year. Adelphic says Q2 revenues rose 282% year-on-year, but we don’t know from what base.

To view the list in its entirety, visit Business Insider.

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