Category: Data-Labor-Technology Stories

In today’s world of social media speed, fake news and announcing deaths before they happen, how does a brand not just gain the trust of their consumers, but keep it, as well? I attended the Family Online Safety Institute’s annual conference in Washington, D.C., last November, where a great deal of the research centered around…

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The advertising industry has been plagued by a lack of trust, with vendors, agencies and marketers looking at each other askance. Ad fraud, bad traffic and hidden fees have taken their toll, and while industry players have taken measures to reinstitute their good standing, their work isn’t nearly complete. During a panel Thursday at AdExchanger’s… Continue reading »

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The most ideological members of Congress shared news stories on their Facebook pages more than twice as often as moderate legislators between Jan. 2, 2015, and July 20, 2017, according to a new Pew Research Center study that examined all official Facebook posts created by members of Congress in this period. The analysis included links […]

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“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ed Camargo, vice president of paid media at PMX Agency. As marketers, we are constantly prompted to consider the question, “How do people intuitively engage with media?” We are, after… Continue reading »

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“The Sell Sider” is a column written by the sell side of the digital media community. Today’s column is written by James Curran, founder and chief product officer at STAQ. Publishers need to change the way they approach their programmatic ad sales business. Many publishers have not yet put in place the right planning, operations… Continue reading »

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A weekly comic strip from AdExchanger that highlights the digital advertising ecosystem…

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Here’s today’s AdExchanger.com news round-up… Want it by email? Sign up here. See To Believe It’s been two years since the ANA and K2 released a damning report on programmatic buying practices, and media agencies are still suffering a trust fallout. Assembly, owned by MDC Partners, has agreed to pay for clients to use a tool… Continue reading »

The post Assembly To Show Inventory Costs; Snap Updates App Install Units appeared first on AdExchanger.

By Jay Wardle – president, Dstillery

It’s 5 p.m. on a Saturday. A shopper enters a Nike store in Philadelphia. At 5:35 p.m., she leaves carrying a new pair of running shoes. All along, her smartphone had been beaming her location data to a performance-data specialist, which then relayed the information to Nike’s marketing team.

But what did Nike really learn about that shopper’s path to purchase? Sure, they know roughly where she was, and when. But isn’t anyone who enters a shoe store likely to buy shoes? If brick-and-mortar retailers want to compete with Amazon, they’ll need to turn their stores into a competitive advantage. First, they have to harvest location data from their hundreds of outlets to collect a data set Amazon doesn’t have. Then, they’ll have to walk in the giant’s footsteps by using that data to make predictions that drive sales.

That’s where geospatial data comes in. Location data, collected in isolation and in real-time, merely offers measurement. Geospatial data offers location, plus the context retailers need to make decisions.

According to the Mobile Marketing Association, 40 percent of client-side marketers are deeply concerned about data quality and lack of transparency in data sources and methodologies. In another recent study, 94 percent of senior brand marketers said they found it challenging to work with location data, in part because it can be inaccurate, and in part due to their own limited understanding of which third-party providers can help them.

It doesn’t have to be this way. While raw location data helps a brand measure and answer questions such as place visit rates or where their previous customers live, a geospatial approach can be used to clarify that data and better understand where shoppers are in their path to purchase. Then, using that data, retailers can predict a shopper’s next move. Kimberly Yarnell, vp of digital media at Macy’s, commented that “location is not just about where a person is at a moment in time, it’s about where he or she has been and understanding where he or she may go.”

 

AI-driven geospatial data gives retailers a clearer picture

Accurate predictions must start with accurate data. Consider a high-end home furnishings retailer in Highland Park, Illinois. The retailer was using location data — simple latitude and longitude — to determine the number of customers visiting its store. But estimates didn’t line up with foot traffic. According to their numbers, the store should have looked like Black Friday every day.

In reviewing their data, Dstillery’s data science team discovered a common error. Because the retailer was looking for consumer data within an area rounded to one decimal point (i.e., 89.8 instead of the more precise 89.87654), the brand was seeing an abnormally high number of shoppers. In fact, consumers with mobile devices were walking the aisles at different stores dozens of miles away. Therein lies the risk of basing marketing decisions on surface level location-based data.

Geospatial data, on the other hand, takes into account a broader depth of dimensions beyond pure location. In this case, we noticed far too many devices at this location relative to other, nearby stores. Then, we used machine learning technology to filter out suspect location-based data, leaving us with a clean, accurate view of the store’s real visitors.

The retailer was finally set up for predictive success, using the precise data AI delivered.

Geospatial data improves channel strategy

One national sportswear apparel company asked Dstillery for deeper insights into its specific audience niches.

The company understood that its audience was made up of soccer fans. But what did that really tell them? If an amateur soccer player walks into a retail outlet, she’s likely to buy sports equipment. But a couch potato who happens to be a diehard Real Madrid fan is far likelier to buy apparel. By diving into various online and offline indicators, we were able to identify subpopulations with highly specific interests. And — crucially — we knew where those people lived.

It was the geospatial data that made those insights invaluable. For instance, if we isolated a geographic area with a high concentration of one or two specific subpopulations — say, fans or soccer moms — we could help the company deploy highly focused direct messaging campaigns. In areas with a general mix of subpopulations, a general messaging approach won out.

It didn’t stop at marketing. Geospatial data helped determine which retail partnerships to pursue. After all, if a company knows where its various audience segments shop — and what they’re likely to buy — it’s easy for that company to determine which stores its products should be in. And in areas where shoppers can’t properly be served by their local retail outlets, a company can favor e-commerce partnerships. Armed with geospatial data, companies can tailor marketing and retail partnership strategies to highly specific populations.

Predictive is the holy grail

Early on, WPP chief executive officer Martin Sorrell proclaimed location-based marketing the “holy grail” for advertisers. Seven years later, its promise still feels elusive, particularly for retailers. But there’s still plenty of  hope. Technologies have advanced marketers’ ability to tap into mobile devices as another channel to engage consumers, and the industry as a whole continues to tirelessly shed itself of endemic data quality and transparency issues.

By embracing geospatial data as a strategic discipline, committing to using it creatively to predict consumer behavior, and pushing partners to live up to higher standards with respect to data integrity and transparency, brands put themselves in a significantly better position to win — even in an Amazonian climate.

 

The post How retailers can use geospatial data to predict consumer behavior appeared first on Digiday.

With the General Data Protection Regulation being enforced in May, demand-side platforms need to figure out how to target users without relying on personal data. DSPs that are unable to adapt to the new rules are likely to lose market share and suffer a similar fate as the programmatic platforms that were late to adopt header bidding.

The GDPR demands that personal data only be used with explicit permission from individuals. This could become problematic for DSPs because they rely on audience data to target ads, and 50 percent of European internet users said that if given the option, they would opt out of seeing retargeted ads, according to a December survey by HubSpot.

Johnny Ryan, head of ecosystem at anti-ad blocking firm PageFair, said that when users opt out of having their data used for ad-targeting purposes, DSPs will have to scrupulously avoid using any information that ties back to an individual user. Data like IP addresses and cookies, which are the backbone of real-time bidding, will be off the table in these scenarios. These data restrictions will burden many vendors, and the GDPR will revolutionize ad tech akin to how the auto industry is being pushed to switch to electric vehicles, he said.

To obtain consent from users, DSPs have to rely on other companies along the ad supply chain since DSPs don’t have direct relationships with the end human being receiving an ad. It is the consumer-facing websites of publishers that ad tech companies will rely on to obtain consent, said Ratko Vidakovic, founder of ad tech consultancy AdProfs.

Obtaining permission from people to use their data for advertising purposes isn’t as simple as serving a one-time pop-up message that opts them in. Lawyers, sales execs, editorial people and web developers all get dragged into GDPR-related meetings, said Jeremy Hlavacek, head of global automated monetization at IBM Watson Advertising, which encompasses IBM’s media properties like The Weather Co.

Lawyers inform the rest of the company on what the policy permits, sales aims to make sure the new rules don’t hurt vendor and advertiser relationships, editorial’s focus is on embedding the consent forms in a way that doesn’t provide a bad user experience, and web developers build the features. Hlavacek speculated that small publishers will struggle to devote enough resources to GDPR compliance to make a smooth transition once the regulations take effect.

Since publishers’ opinions of ad tech vary widely, not all publishers are going to trip over themselves to get user consent for ad targeting. Those that rely heavily on targeted programmatic ads will be as desperate as their vendors to get user consent. But other publishers less beholden to ad rates may use the GDPR as an opportunity to re-examine the vendors they want to keep, and it is possible that some publishers fed up with data leakage won’t bother to bug their readers to opt into data tracking.

Publishers’ varied responses to the GDPR could create a patchwork environment where the readers of certain sites are more likely to give advertisers permission to use their personal data than readers of other sites. This will make contextual targeting more important for DSPs as they use content as a proxy to reach audiences, said Ari Levenfeld, chief privacy officer at ad tech firm Sizmek, which acquired DSP Rocket Fuel last year.

“This would necessarily whittle down the universe of targeting options in the EU,” said Eric Berry, CEO of native ad platform TripleLift.

Building features into dashboards for granular content targeting isn’t easy. The contextual targeting would have to be done at scale and across many languages, and these types of products can take months to perfect, Levenfeld said.

To prepare for the GDPR, the DSP Dataxu integrated Grapeshot into its platform about a year ago to beef up its contextual targeting capabilities, said Andy Dale, vp of legal and data protection officer at Dataxu, noting that Dataxu is working on building its own contextual targeting products. Dataxu also plans to hire a data privacy consultant in March to help it comply with the upcoming regulations.

DSPs are far from being the only sector of the Lumascape to feel pressure from the GDPR. Retargeting firms are scrambling to get consumer consent, and data management platforms are bracing for a tough battle to obtain the data that powers their businesses.

“We support ad tech companies and like working with them and want to see them succeed,” Hlavacek said. “But it is a dangerous time to be not fully compliant with all of these rules.”

The post With GDPR looming, DSPs are under pressure to adapt appeared first on Digiday.

Even the most fervent believers in programmatic advertising believe it needs to undergo a cleanup, as marketers lose faith in ad tech due to issues like hidden fees, ad fraud and murky auction models.

The mood among marketers, agencies and vendors at AdExchanger’s Industry Preview event Jan. 17-18 in New York was a candid admission that automated ad buying is undeniably the future but has many problems that cannot be put off.

“There’s an element of trust missing right now,” said Belinda Smith, global director of media activation for video game company Electronic Arts, at the event on Jan. 18. “Frankly speaking, it’s not in my interest to understand every detail of the buy-side fee because as a marketer, my biggest focus is getting in front of my audience. But [building trust] means that my partners should be able to answer everything that I ask.”

Smith said on stage that her team has run programmatic on its own for a while, and it started owning vendor contracts last year to keep track of tech providers’ fee structure. Contract ownership will continue to be a big focus for Electronic Arts this year, she added. “As we pick up things, we learn tricks and tips [in programmatic],” Smith said. “We put how fees are charged in detail in our contracts, we look at [campaign] win rates, and we constantly talk to our publishers — if what we see and what they see don’t match and we can’t reconcile what’s going on, we will take money out of the system.”

Another presenter, Louis Paskalis, svp of customer engagement and investment for Bank of America, described programmatic as “the single worst thing that happened to advertising and only salvation for the future of marketing” because it promises to generate the highest yield at the lowest cost. “As a marketer, I need to know the context of my ads. If we have the same shoe ad following us for three months, that’s bad consumer experience,” said Paskalis on Jan. 17. “Programmatic could work if it optimizes the customer relationship instead of the transaction.”

Michael Roth, chairman and CEO for Interpublic, also said at the conference on Jan. 17 that IPG is in talks with many programmatic tech providers to make sure they optimize for media effectively.

Ad tech vendors are acting. For instance, Adobe and AppNexus announced a partnership to bring transparency to hidden fees. Meanwhile, video exchange Telaria introduced a program called The Fraud Fighter on Jan. 17 to ensure its video inventory meets or exceeds brand-safety standards. Rubicon Project also reduced its take rate from 24 percent to 11 percent and eliminated buy-side fees last year, according to the company’s CEO Michael Barrett. “Ad quality will also continue to be a big focus for us in 2018,” he said.

Yet most executives at the event agreed that more must be done. Speaking on a joint panel with Smith, Brian O’Kelley, co-founder and CEO of AppNexus, said mobile ad fraud is still rampant, and there’s no good technology to catch it, while Keith Eadie, vp and gm of Adobe Advertising Cloud, said marketers need more clarity on the auction dynamic that each exchange employs.

Smith, on the other hand, thinks that if marketers want more transparency, they must be willing to pay more for better inventory. “When you negotiate [the price] down and put pressure on fees, there’s only one way for that story to play out,” she said. “In that case, you shouldn’t be shocked that fees pop out in other places because people need to make money. Being cheap in everything doesn’t make [programmatic] a sustainable model.”

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