Le 3 Les plus grandes idées fausses sur mobile Ciblage géographique
xAd | 10 / 02 / 2012
Since the dawn of mobile, advertisers have salivated at the idea of targeting users based on their current location — but despite the clear promise of the medium, many have struggled to capitalize on it. A number of misconceptions threaten to confine the industry to the progress made in these early years of mobile, so in an effort to continue our momentum – it’s time a few these myths were officially debunked.
1. “Everyone Can Do Location Targeting”
Mobile publishers have access to the location information they ask of their users. This location data could be as general as a city, or as specific as a request to capture their exact location at any given time. The more exact the location, the more valuable it is both to an ad network and to a mobile advertiser. Latitude/Longitude (lat/long) is the most accurate location data currently available, yet it’s estimated that only 10-15% of smartphone traffic has true lat/long. While many users are still feeling out their comfort level in providing personal and real-time location information to the apps occupying their smartphone, publishers are doing what they can with the location data they have been allowed and passing that information on to networks. Therefore not all these signals reflect real-time location, and if we were to map the user location signals passed on to most ad networks, we would start to see clusters of location signals within the centroid of cities or zip codes, and far less spread out across each target area. This means that in many cases, real-time user location data is not actually being utilized and user locations are being assumed by the generalized data being passed.
As a result, advertising you thought would be served to a specific area may actually be served in the general vicinity of your target area as well as some of the surrounding areas. Although this lack of location accuracy is concerning, the true crime here is the fact that the campaign performance will be judged on a less-than-perfect campaign model. As the industry becomes more educated on the power of location data, the expectations of advertisers and their consumers are also expanding. Therefore an ad network’s ability to harness the most exact location data available and use it in a relevant and meaningful way will win in these early stages of mobile.
2. “Geo-Fencing Covers All My Bases”
Targeting consumers based on a set radius around any given point – be it an exact address, zip code centroid, etc. – is often called “geo-fencing.” This well-known targeting method is used to better reach the most relevant audience base related to an advertiser’s goals and needs. Ads are targeted within a neat little circumference and any consumers that happen to fall outside that virtual fence are excluded from ad placement.
Does anyone else see a problem with that?
The truth is that mobile users are constantly moving and so are their needs. Therefore confining a mobile ad campaign to an exact geometric shape (sometimes as small as a few hundred meters) may actually be causing you to miss your true target audience. Our recommendation is to test the concept of geo-fencing by testing and optimizing several target distances (i.e. one mile vs. five miles vs. 10 miles, etc.). When doing this – keep in mind that different areas may call for different size fences (i.e. metro areas should have tighter fences where more rural areas may call for larger coverage). In addition to geo-fencing, test typical location targeting parameters such as zip code targeting or city if your serving area supports this. Who knows – you may be pleasantly surprised at what you find out.
So think outside the traditional geo-fence and go after your audience wherever they may roam, instead of assuming their behaviors and location will remain within the confines of a certain “assumed” radius.
3. “My Click-Through Rate Is High, So My Mobile Ad Must Be Performing”
Mobile ad measurement has come a long way. No longer are we constricted to the simple first-click analysis of traditional online advertising. So why are advertisers still gauging the success of a campaign on the Click-Through Rate?
Mobile ad users are looking for quick and relevant information on the go, and innovation in mobile ad strategy has given them just that. Secondary actions in the form of click-to-call, download map and driving directions, etc., allow users to access the information they need in response to a mobile advertisement. But the benefit for advertisers is two-fold. Of course they benefit from mobile user interest in their advertising, and the more clicks the better. But secondary actions also allow advertisers to get a better feel for the needs of their audience and their engagement level with the ad – a metric far more powerful than the average CTR. If a user downloads map and driving directions, we can make a fair assumption that they are on their way to that location. But if we concentrate on just the initial CTR, we are missing this valuable measurement.
A common concern with mobile advertising is butt-dialing, fat finger syndrome, or fraudulent clicks. In fact, according to a recent TradeMob report, 40% of all mobile clicks are useless. So developing and measuring your mobile ad campaign based on secondary actions is a great way to get past these instances of accidental engagement, and find the real value of any mobile ad campaign.
Therefore, a mobile device’s location of use is a key factor in determining the search behavior of mobile users. When search behavior related to location is taken into account, the relevancy of any mobile ad campaign can significantly increase, which in-turn increases the campaign’s overall performance.
Education is the key to the mobile industry’s continued progress. As soon as these three common location-targeting misconceptions are officially debunked by the community, there will be many more to take its place. But as technology advances, so will user adoption, and in the next few years, we should see mobile users who are fully on-board with the value provided by relevant location targeting.