Monthly Archives: December 2016

Ad Tech Vet Eric Picard Joins Pandora As VP Of Ad Product Management

Originally Published on AdExchanger.com – Wednesday, December 21st, 2016

Pandora is increasing its bet on ad tech.

The streaming music platform will bring on Eric Picard as VP of ad product management to continue building out display and video products and lead its dive into programmatic audio.

Picard is a longtime ad tech executive. In 1997, he launched Bluestreak, one of the first companies to create the rich media formats that are standard in digital today. Since then, he’s launched numerous ad tech startups, led ad product strategy for Microsoft and, most recently, was VP of omnichannel media for MediaMath. Picard joined MediaMath via its acquisition of Rare Crowds, a programmatic platform he founded in 2012.

“I’ve been in ad tech my entire career,” he said. “I have played roles in teams across pretty much every aspect of the space.”

In audio, and at Pandora specifically, Picard sees an opportunity to “participate in such a large marketplace for an ad media type that hasn’t been fully explored yet.”

“There aren’t too many places in the market to go that are nearly as exciting as the marketplace that Pandora has built for audio, display and video ads,” he said.

In his role, Picard will lead a team of 15 to 20 product managers focused on building and optimizing ad products. He plans to grow that team during his tenure.

Pandora has been bullish on programmatic display but hasn’t yet begun selling its in-stream audio ads programmatically. Picard will likely have a big part in pioneering that in 2017.

“I’ve been deeply involved in the next generation of platforms and methodologies, what we loosely call programmatic,” he said. “You can imagine that we’re thinking a lot about a lot of those things.”

Pandora offers an opportunity to innovate in an area of ad tech that’s still nascent.

“Figuring out the future of audio is obviously the enticement,” he said.

 

Get creative with hyperlocal targeting

By Eric Picard & Max Dowaliby (Originally Published on Imedia – December 16, 2015)

Hyperlocal targeting is the shiniest method of delivering advertising to consumers based on their exact location.  This is geo-targeting taken to the logical conclusion of every person carrying a GPS locator on their person wherever they go, even though GPS is only one method of determining location. The introduction of location data into mobile advertising has allowed advertisers to leverage the always-on, always-connected mobile device as an indicator of location. This has driven hyperlocal targeting to become one of the fastest growing mechanisms to capture dollars allocated to local advertising.

According to Borrell Associates, 42 percent of all local advertising is expected to be digital in 2015, totaling over $47 billion. Sixty-one percent of smartphone users say that they are more likely to buy from mobile sites and applications if they customize content or information to the current location of the user.

There are many complexities to local advertising that have not been sorted out, even with these advances.  For years, analysts have been talking about the coming transition of local dollars to digital, but it is possible that hyperlocal targeting could change this. The main issues in the transition of local to digital has been the so-called “local independents” — the “mom-and-pop” shops — which are the standalone companies that make up the vast majority of local businesses.  For these companies, local for years has meant Yellow Pages and newspapers, and, for the larger ones, radio and potentially local television. Mainly this has been held back due to creative production, as these small businesses don’t have the means to create advertising to fit the needs of the digital space.

The “national-local” advertisers — the brands with local presence — ranging from quick-service restaurants to retailers are the main drivers of adoption of digital. Until mobile location data really became actionable, there was still little reason for the local dollars of the national brands to transition to digital — as geo-targeting was seen as too vague, and the creative value propositions were not quite strong enough. Things are changing.

Hyperlocal targeting is not a simple mechanism for identifying or targeting users. It’s more of an overall set of services for leveraging highly accurate, fresh, and relevant data about a user in order to make the best decision matching the ad opportunity to the consumer, based on their exact location. Let’s explore hyperlocal location targeting (what most people are referring to when they say hyperlocal targeting):

Advertisers have been able to do some sort of location targeting for years now. Targeting based on city, DMA, or zip code have been well-used and well-performing tactics. However, the real challenge here is getting more granular than a zip code. Since mobile phones provide signals that allow us to achieve incredibly granular information, the mass adoption and nonstop usage of these devices has — in many ways — solved the problem for us.

Hyperlocal location targeting refers to the ability to be able to target small areas or “geo-fences,” including radius (general distance from a target location) and polygonal geo-fences (a shape drawn on a map). Both of these mechanisms have uses for targeting users; for instance, a message could be sent to users when inside a certain radius of a specifically targeted destination. An example: A retailer might want to send “message A” when a user is within 2 miles, “message B” when a user is within 1 mile, and “message C” when a user is within 100 meters. This can be an extremely powerful tool to drive foot traffic or engagement. This location information also allows advertisers to provide relevant, and contextually aware content to users. In the case of a polygon, a quick-service restaurant that delivers food might have very specific streets that become a boundary for where they deliver from one location versus another — and radius simply won’t solve for this.

We now have incredibly accurate signals by which we should be able to target users, but there are still some key challenges when trying to leverage this data. Arguably the most important is the accuracy of this information. Depending on where the location information is coming from (browser, in-app, carrier, etc.), the precision varies greatly. Location information is conveyed via latitude-longitude coordinate pairs, and, as such, can vary in degrees of precision. Carrier-provided location data is often only accurate to the area that an individual cell tower provides service to, whereas in-app provided location data can be extremely accurate and place a user inside a retail store, or even in a certain part of a retail store. There is also a large amount of (usually) unintentional location fraud. This refers to revered latitude-longitude pairs, missing coordinates, or centroids (a central point in a city, state, country, etc.). There are numerous location targeting partners who cleanse and validate location data to help this problem, but it remains an issue that cannot be ignored.

Freshness of the location information is important in hyperlocal location targeting. It is critical that a user be messaged when they are physically at a certain location, not when they were there five minutes ago. One of the challenges of dealing with location information is that this data cannot be cached the same way most information about a user can be. Location is fluid, and users are constantly moving. This makes location data at scale an incredible amount of information to process.

However, when these challenges are overcome, there results are worth it. A quality hyperlocal campaign can provide incredible utility and relevance to a user. Messaging a user at the right place and right time works, we know that. It’s all about the execution. Users are clamoring for this kind of utility. Eighty percent of Google searches that included the term “near me” were from mobile devices in Q4 2014. Even more importantly, the prevalence of the term “near me” is up 34 times since 2011. Users now want — if not demand — relevant information and experiences based on where they are. Hyperlocal is a buzz word, and for good reason. Let’s just make sure we use it to its fullest capabilities. Get creative!