Debunking The Top 6 Myths About Location-Based Mobile Advertising

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In today’s digital world, our smartphones know more about us than our friends and family. They know the numbers in our bank account, our ongoing health concerns, and the people we talk to. Our smartphones also track the places we go, which opens up tremendous possibilities for advertisers. Location data can not only provide businesses with key insights into customer preferences and behaviors, but also enables them to deliver ads in the most impactful (i.e. relevant) moment.

However, despite its exciting promise, location-based mobile advertising has struggled to reach its full potential. A yawning gap persists between the possibilities of this ad format and its execution — a gap buttressed by a slew of common misconceptions that prevent the sector from moving forward.

Let’s take a look at the 6 top myths about location-based mobile advertising, and the realities behind them.

Myth: When Ad Vendors say: “Our location data is 4 (or 5 or 6) decimal points of accuracy”

REALITY: To be truly valuable, location data needs to be accurate. Accuracy reflects the degree to which you can target the right person with the right message, and in an effort to sell their product, ad vendors like to boast that their location data offers 4 or more decimal points of accuracy.

However, the reality is that all the players in the space are working with the exact same data (albeit with widely varying degrees of precision). Moreover, 3 decimal places or greater is generally considered PII(Personally Identifiable Information) by the IAB. The challenge, and thus the differentiator, comes in when a vendor a) cleans and normalizes the data and b) makes accurate use of different data sets to strengthen it.


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Myth: POI Data is straightforward

REALITY: POI data is essentially a data representation of the physical world. Since buildings rarely move, POI data is often viewed as “easier” or “simpler” than user data (since humans tend to move around). This is a mistake, given that 20-50% of POI data in conventional datasets is wrong. Since businesses are always evolving (locations open, close, move or change identifiers, such as phone numbers or owners), unlocking the full potential of POI data can be a challenge to building an effective mobile campaign.

The fact is, deriving accurate POI data is actually a harder problem than clean user location data, and arguably more important. Bad POI data could mean delivering an ad for a business that is not where the ad says it is or building inaccurate audience segments. Unlocking the full potential of POI data requires technology that can first ingest, clean and normalize big data sets, then build context for the data depending on the particularities of a local market.

 

Myth: True polygons around a store are hard to do

REALITY: Polygons are a way of organizing places and place data. While a “location” can be reduced down to a point, polygons are one-way location technology companies demarcate where a place (like a store) begins and another ends. This is critical when waging an effective location-based mobile advertising campaign, but many businesses believe that drawing true polygons around a store is prohibitively difficult.

Today, polygons are table stakes, and any vendor not drawing them is at a disadvantage. Tight geofences need to be balanced with the need for reach and scale–otherwise, you will only see a tiny segment of users.

 

Myth: Tiles are better than exact places polygons (and vice-versa)

REALITY: Tiles are another method of identifying/demarcating a place. There are those in the industry who promote tiles over polygons or vice versa, but neither is better than the other. There is a time and a place for both. Exact places (i.e. polygons) work better for creating user segments and geofencing, while  tiles work well when aggregating data about a place.


Myth: When ad vendors say: “Our cross-device ID matching achieves 90%+ accuracy

REALITY: Along with location data, ad vendors love to tout the high accuracy of their cross-device ID matching. Today’s consumer fluidly and regularly switches between devices. The ability to track and engage users across devices remains a steep obstacle, but overcoming it reaps great rewards.

As a result, it’s not uncommon for ad vendors to say their cross-device ID matching achieves an accuracy of 90% or more. In truth, probabilistic match rates vary widely depending on datasets, usually from 20-50%. Deterministic matching (i.e. actual verified data) can yield high rates, but those data sets are usually smaller.


Myth: Fraudulent user location data injected by publishers is a big problem

REALITY: Fraud is understandably a significant concern for advertisers, who don’t want to invest significant resources into location-based mobile advertising campaigns, only to find that the user location data from publishers is subpar at best, or totally false at worst.

Fortunately, fraudulent user location data is easy to detect with the right technology that automates and manages it in real-time. When detection is utilized by whitelists, it can be managed with less granularity.

The location-based mobile advertising market is set to explode. Research firm BIA/Kelsey estimates that it will grow to $18.2 billion by 2019. This ad format needs to be part of every advertiser’s portfolio, but it’s important to embark on these efforts armed with facts, rather than fiction. Don’t let commonplace myths prevent you from unlocking the full potential of location-based mobile advertising.

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