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Writer's pictureFahad H

10 Key Mobile/Location-Based Stats That Marketers Need


It should surprise exactly no one that mobile usage and location-based technologies are taking over the world. With more iPhones being shipped every day than humans being born, it’s not hard to see that it won’t be long before there are more smartphones in the world than people.

And while smartphones and tablets have been around for several years now, we are starting to reach a tipping point on many fronts where these devices are becoming an integral part of our lives — so much so that they are often the last thing we look at before we go to bed and the first thing we check when we wake in the morning.

So, what does this all mean for marketers? As I’ve written in other posts, the mobile phenomenon is a game-changer for marketers.

Mobile proliferation is allowing for a ton more of data to access and analyze. It is creating new ways to reach target audiences now that we know where they are (and when they are). Smart devices are allowing for radical new payment systems. And most importantly, they are dramatically impacting how people search, research and shop — both online and in person.

To help frame the opportunity, here are some key mobile and location-based statistics that all marketers should be aware of.

  1. Three Mobile Usage Models. There are three main modes of usage: urgent, bored and repetitive. When creating mobile apps or mobile-optimized sites, it’s important to understand these meta use cases. Many times, only those instances meeting the “repetitive” or “bored” use cases merit developing an app. For the “urgent,” often a mobile site is all that’s needed unless it’s for stock prices or information that a user is making daily decisions on. Source: Mobify

  2. Mobile Device Adoption Rate. Mobile web adoption is growing 8x faster than web adoption did in the late 1990s and early 2000s. The biggest takeaway from this statistic is the fact that as ubiquitous as desktops and laptops are, mobile devices will outstrip this by a lot. This will also have a profound impact on what is called the Internet of Things as access to data and services moves from a mobile screen to objects in our cars, homes and work, including things we wear on our bodies.  Source: Mobify

  3. Rise of Unstructured Data. Unstructured data is growing at a rate of 100:1 vs. structured data. For anyone that understands data, this is both a blessing and a curse. The lay persons’ explanation for this is that unstructured data is harder to parse and interpret because it is largely text-, photo- and video-based so writing queries against it is not as easy as it is for structured data (think of things like name, address, zip, phone as structured data or data that easily fits into columns and rows of a database). Source: Venuelabs and The LBMA

  4. Location-Based Data. Twelve percent of adult smartphone owners say they use a geo-social service to “check in” to certain locations or share their location with friends. When my co-author, Mike Schneider, and I originally wrote the book, Location-based Marketing for Dummies, we were bullish on the concept of active check-ins. Since 2011, behavior has trended much more toward passive location-based activity. In particular, apps that are geo-aware are becoming more and more prevalent. This number is down from 18% in early 2012 by the way.” Source: Pew Internet

  5. Mobile Internet Usage. More time spent on internet via  smartphones than laptops/desktops. Web designers and architects: take notice. This is no longer your father’s internet. Responsive design rules the day. The key is lighter, faster and cleaner. Source: MarketingLand

  6. Mobile Ad Engagement. Brands are seeing as much as a 20% increase in conversion when adding location data to their ad data. We’ve all heard about the death of advertising. And while we know that’s not actually true, it is apparent that the paid media space is becoming more fragmented and thus more expensive and less effective. Enter location data as a way to drive greater effectiveness in mobile ads. Content is still king, but context is quickly becoming queen. Source: Skyhook Wireless

  7. Location-Based Opportunity. Today, about 67% of photos posted to the internet have an associated location. Locked within these photos are insights into merchandising, operations, and other valuable information that can be mined. Refer back to point three for additional context. Source: Venuelabs and The LBMA

  8. Demographic Targeting. Fifty-eight percent (58%) of U.S. adults have smart phonesFile this under “duh,” but the reason I am including it is not what you think. It’s actually to reinforce the fact that this means that 42% of mobile phone owners don’t have a smart phone. This means that SMS is still important. Also of note is that for the 58% that do own smart phones, 81% of those have a household income of $75,000+. Source: Pew Internet

  9. Location-Based Advertising. Sixty-nine percent (69%) of Google searches include a specific locationRelated to the inclusion of location data to the effectiveness of advertising, it’s also driving a lot of search queries these days. Customers don’t want to know what but where. This also reinforces the importance of keeping your business’s address and information current on sites like Google Places, Yelp and foursquare. Source: eMarketingBlogger

  10. Omni-Channel Advertising. Forty percent (40%) of shoppers consult three or more channels (often while shopping) before making a purchase. This same stat was less than 10% in 2002. And 4 out of 5 consumers use smartphones to shop. I covered this concept of “omni-channel” in a recent post; but clearly, it’s more important than ever to consider the shopper journey. Those that ignore will cede sales to upstarts and smart brands that understand and execute against this concept. Source: Convince and Convert

While there are thousands of more statistics you can use to inform your mobile strategy and thinking, these are a few that should help. I strongly suggest visiting the sites of the sources I’ve referenced next to each statistic as there are lots of other useful data available at each.

Thank you to Mike Langford, Mike Schneider, Eric Miltsch and Jeremiah Owyang for providing data recommendations.

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