Mobile - Katz Marketing Solutions | Radio Advertising | Media Agency

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Location is a big deal. For the history of digital advertising we‘ve basically been targeting on a few things, like content, cookie data and search. Thebig new data set mobile brings to the table is location—a data set that can be as important at inferring intent, demographics, audience segments andother attributes as any we have seen to date.And it brings genuine value to end users—helping them find products and services where and when they want them—a key attribute of the mostvaluable advertising mediums.There is a lot of energy and excitement around location targeting in mobile—from agencies and brands that see the enormous potential and fromtechnology companies that are building the next-generation platforms for harvesting and leveraging this data for marketing and advertising.But there‘s one very significant problem that is holding mobile location targeting back—the market has been flooded with bad location data. And manyare turning a blind eye to this fact because to acknowledge it would be contrary to their business interests.There are many sources for actionable mobile location data. The device can share GPS level data (provided the user has opted in to share locationwith an app or web site). This GPS data is typically represented by latitude and longitude coordinates (lat/long) and is generally very accurate. Thenetwork can share data derived from cell tower triangulation which is also quite accurate. There is also user-supplied location data (e.g. when a userprovides his zip code when registering for a site or service).Another method of deriving location is IP address analysis, which can range from very accurate to completely inaccurate. An IP lookup can resolve toa terrestrial wifi network (like an airport or coffee shop), most of which are well indexed to location. But an IP lookup can also resolve to a carrier IPaddress and carrier IPs vary widely in accuracy. Many carrier IP locations are accurate to the metro or zip level, but many resolve to ―backhaul‖addresses—which are the locations where the carrier aggregates mobile data for transport over fiber trunks in the telecommunication infrastructure—which are generally inaccurate.The crème of the crop in location data targeting is device-level GPS lat/long data. Highly targeted mobile advertising campaigns that are focused ontargeting people in an area the size of a city block or a shopping center or a big box store require this precise lat/long data (and potentially wifi data).The problem is that lat/long data is very scarce. Most industry experts consistently estimate that about 5-10% of mobile ad impressions have lat/longfrom users who have opted in to share location with an app or site. This makes sense. Most apps and many of the largest mobile consumer apps—like internet radio or game apps—aren‘t allowed by Apple to ask for location.One of the rules for app store approval is that, if the developer of an app has built in a feature that asks the user for location, he must have a goodreason for doing so—location-based apps like Foursquare, mapping apps or local media properties sites/apps that are providing geo-aware weather,sports scores or movie times are good examples of apps that can ask for location and with which users tend to share location.Yet, some exchanges and networks claim 70, 80 or even 100 percent lat/long impressions. How can this be? One more time—5 to 10% of all mobileimpressions have lat/long but a given exchange may claim 80% lat/long?The answer is some people are making up lat/longs. This is the dirty little secret of location-based advertising. About 12 months ago, some publishersfigured out that location was the one attribute that really moved the needle in the exchanges and the ―inferred‖ (read ―made up‖) lat/long was born. 1If buyers are paying a premium for lat/long location data and it‘s the only thing that can give a publisher‘s mobile impressions a price boost,manipulators will find a way. And they have. In 12 months‘ time, the number of lat/long impressions in exchanges has grown from the industry average5-10% to the current 70-80%. Even though, generally speaking, lower quality, rather than premium impressions, end up in exchanges, so one wouldexpect that premium lat/long impressions would be used by publishers and their location specialist partners and fewer (not more) lat/long impressionswould be making it into the exchanges.The methods being used to generate ―inferred‖ lat/longs fall into two primary categories (although there are more): ―centroids‖ or ―randomized‖ lat/longs.Centroids are lat/long coordinates that are generated by software programs that automatically pick the center of a geographic region as a substitutefor either no location data —many corrupt lat/longs are dead center in the middle of the country—or for lesser-quality location data—they are in themiddle of a state, DMA, city or zip.Randomized lat/longs are generated by software programs that randomly choose lat/longs within a region. This is a really big problem for the evolutionof the highly granular location targeting that has so much potential and has marketers so excited. If a marketer is targeting a particular store location,mall or office building, a particular neighborhood or city block or an audience segment that is based on inferences drawn from the context of a user‘slocation, then bogus location coordinates are almost certainly targeting the wrong place and the wrong people and driving down performance.Garbage in, garbage out.So what to do about it? At Verve, our roots are in building mobile tools for publishers and we work with many of the largest premium contentpublishers in the US providing them with a mobile publishing, web and app platform that powers their mobile content distribution.So, for about a third of the publishers we work with, we are the first party technology platform —we know with 100% certainty what location the GPSchip in the device is generating. Also, most of these properties are location-aware, giving users good reason to opt in to sharing location.Further, for the publishers we work with who aren‘t on our publishing platform, we work with most of them directly, through first party businessdevelopment relationships. If we see data that our systems detect as suspect we call them up and rectify the situation—either they send us good dataor we don‘t work with them. When we do venture into the mobile exchanges we leverage our unique proprietary technology that allows us to recognizeand parse ad impressions with genuine location data from those with false location data and cherry pick verified impressions.78
We work with publishers with over 108M US unique users and see almost 10 billion impressions monthly and we have more verified lat/longimpressions than anyone in mobile. And when we use DMA, city, zip, user supplied or IP targeted location data—which can be valuable under theright circumstances and can help advertisers achieve scale in this emerging technology arena—we don‘t hide the ball and call it something else.All of these things—cultivating inventory partners with higher than average true lat/long data, working directly with partner publishers so we can haveconfidence in the data being received and developing proprietary technology and models that allow us to identify and reject ―inferred‖ lat/longs—areimportant in making sure we can operate our business on legitimate location data and advance location targeting in mobile. But we are also workingon a broader solution that could become an industry model—a system that scores every impression for the likely accuracy of its location data andestimates the likely original source (e.g. ‗this centroid is likely derived from this zip code‘) so even if the problem of ―inferred‖ lat/longs continues wecan provide a measure of transparency.Location targeting in mobile has enormous promise. With the increasing penetration of smartphones, increasing user migration from online to mobileconsumption, the increasing development of location aware apps and the increasing comfort by consumers with sharing location, we will see steadygrowth in high-quality, location-aware ad impressions sufficient to make this promise a reality. The lack of transparency in location data only sets usbackTablets Win Over Smartphones In Ad Click-ThroughRatesHeather Leonard|Mar. 14, 2013, 2:37 PM|213|inShare12EmailMore<strong>Mobile</strong> Insights is a daily newsletter from BI Intelligence delivered first thing everymorning exclusively to BI Intelligence subscribers. Sign up for a free trial of BI Intelligencetoday.Tablets Outperforming Smartphones In <strong>Advertising</strong> (Adfonic via GoMoNews)Adfonic79
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Summary1
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thus, are struggling to respond to
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mobile.‖And, CMOs must understand
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The earliest mobile advertising too
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The upheaval that the Internet has
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But when we ask respondents whether
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―The most significant issue for a
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Mobile Internet advertising is the
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How? With ads that are native to th
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There's an onus on publishers to im
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Some mobile analysts mistakenly bel
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He may even catch the tail-end of t
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Page 34: Unaided brand recall was 43% for au
Page 38 and 39: The technical hurdles are formidabl
Page 41 and 42: Privacy IssuesApple has now phased
Page 44: Google has the same complaint in th
Page 47 and 48: Mobile‘s usefulness for shopping
Page 49 and 50: 1) CPG is adopting mobile faster th
Page 51 and 52: Performance-based pricing models ar
Page 53 and 54: eMarketer expects mobile video adve
Page 55 and 56: Listen To The Sound Of My VoiceA vo
Page 57 and 58: A new report investigating consumer
Page 59 and 60: The next day, Foursquare announced
Page 61 and 62: Expand context beyond locationLocat
Page 63 and 64: Using this tool, VocalizeMobile was
Page 65 and 66: the brands I see in commercials and
Page 67 and 68: "It's not just about trying to move
Page 69 and 70: ―Mobile is becoming one of the fo
Page 71 and 72: time on a mobile device) could be r
Page 73 and 74: ―travelers,‖ ―parents‖ and
Page 75: Failing to Connect with Users Durin
Page 80 and 81: Adfonic, abuying platform for mobil
Page 82 and 83: media-consuming device. But what th
Page 84 and 85: Whether or not mobile users will be
Page 86 and 87: advertisers are coming to us for cu
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Page 90 and 91: 7. Mobile Puts The “R” in Retai
Page 92 and 93: SoLoMo: Time to Get Social, Think L
Page 94 and 95: Companies and marketers who want to
Page 96 and 97: Making the most of a mobile video p
Page 98 and 99: ―Since mobile rich media ad servi
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Page 102 and 103: mobile-centric ad unit? It seems cl
Page 104 and 105: The study goes on suggesting that t
Page 106 and 107: An overwhelming majority—92%- of
Page 108 and 109: ―I think progress is being made
Page 110 and 111: Google also posted better-than-expe
Page 112 and 113: Mobile has also added another layer
Page 114 and 115: Facebook.Stock has climbed from und
Page 116 and 117: IAB: Almost two-third of mobile vid
Page 118 and 119: Mobile Marketing Analytics Are Diff
Page 120 and 121: There is gold waiting in every mobi
Page 122 and 123: Mobile ticketingParamount is runnin
Page 124 and 125: Digital Dimes to Mobile PenniesNow
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128
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Other research showed that TV ads w
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Lockhorn continued that monetary ch
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Among smartphone owners who havenev
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Display Ads' Dubious In-View Perfor
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We've heard Pandora CEO Joe Kennedy
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Talking Point: At the moment, most
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―Make one Web - ensure content an
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Companies such as Amazon, Starbucks
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4. Mobile advertising performs poor
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Recent developments meant to addres
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demographic reported having made at
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effectiveness, a banner click rate
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Digital Experts Tell Us The 7 Bigge
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The other concern I have with mobil
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This shift has been problematic for
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The 1800-Flowers mobile siteWith th
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Measuring mobile video beyond the c
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entries and then tries to provide r
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“It brings together the best of b
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172
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campaigns conducted between Novembe
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uild big money off of it," said Man
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But an effective way of combating u
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Analog 54% 36%Digitally influenced
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etailers’ recent efforts to scale
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That‘s a lot of consumer data to
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As mobile display advertising matur
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Mobile devices‘ smaller screens a
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The YP study shows that the sweet s
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These limitations depress demand fo
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Like similar studies before it, AdS
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percent. Trademob found that 22 per
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We Took Control Away4-day mobile im
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Statistics for the current year sug
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Key takeaways from the forecast:Spe
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52% of marketers report that they a
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Data from ScanLife’s “Mobile Ba
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vs. 10%); making a purchase on a mo
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Challenge Marketers on MobileAUGUST
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Marketers that push creative bounda
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Implications- If we had used the st
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uying against content or even vast
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action with a brand; however, it‘
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was relevant to them, making this t
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MOBILE INTERNET USE ACCOUNTED FOR 1
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ADVERTISERS, SHE CLAIMS. HOWEVER, A
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Study: More Users Clicking Ads, Ris
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Distrust, Irrelevance Temper Mobile
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About The Data: The 2012 Hipcricket
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topping the list in terms of consum
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Foursquare, about to celebrate its
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Here are the top tasks in terms of
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25.2% Newsstand (12)23.7% Lifestyle
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According to Nielsen the majority o
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