Mobile Audience Targeting 101

(1200x600) Target an Audience on Mobile

Targeting Dimensions

The world has gone mobile. Recent data has shown that, for the first time ever, more people are searching Google through a mobile device, rather than a desktop or a laptop computer. This data was released in October 2015, which in ‘Internet years’ is almost ancient history.

At the same time, the amount of mobile devices in use worldwide is increasing, fast. This usage, also called ‘mobile penetration’, was at 4.43 billion for 2015, according to the statistics portal Statista. Moreover, there are no hints of the penetration slowing down – by 2019 there will be more than 5.07 billion mobile devices in use, worldwide.

# of mobile phone users
Global mobile penetration [Credit: Statista (screenshot)]
The conclusion of this introduction is simple – if your marketing strategy does not revolve around mobile devices, you’re doing it wrong. Everyone’s on their smartphones nowadays, and if you’re not there, you’re missing out.

But usage habits are completely different for desktop/laptop users versus mobile users, especially mobile app users. The interface is completely different, user experience is completely different, ultimately leading us to conclude that your online marketing campaign simply won’t cut it on mobile. You need to adapt.

Having such a diverse audience (4.43 billion users all over the world, from different countries, with different cultures and habits), has led to more targeting options, and in order to properly target your audience, you should research each one and use those that will yield the best results.

There are many targeting options on mobile, including basic ones which should be something all businesses should employ, no matter the type of work they do: targeting by location, device model, platform, geography, usage and activity.

Then there are the more advanced types of targeting, which brands and enterprises with deeper pockets should consider based on the type of work they do: users can be targeted based on installed apps, app genres, cross-app activity, in-app events, in-app revenue, social graph, demographics and salary, credit score and financial data, machine learned, interests and affinity, persona and finally – intent.

Let’s take a look at the basic targeting options you should consider, regardless of the type of work your organization does:

Basic Targeting Dimensions

  • Geography – Different countries, different lifestyles and different habits – in the end even different standard of living, all affect how your app will perform. If it’s popular in North America, that doesn’t mean it will be popular in Latin America. But it does mean you could use that knowledge to your advantage, regionally. A game’s popularity, shown through a high mobile user acquisition, will reflect in the top charts, which are fragmented geographically. However, apps tend to diffuse between close geos. So if an app is turning out to be a success in, say, Argentina, you might want to try and expand that popularity to Chile, Uruguay, Paraguay and Brazil.
  • Device models – One of my usual arguments when discussing mobile marketing is ‘If Facebook’s doing it, then it must be worth it’, and in this particular case, Facebook does allow you to target users by device. If you’re lacking other data, you can use targeting by device model to determine someone’s socioeconomic status and persona. Obviously, someone spending $700+ on a smartphone does not behave in the same way as someone who spends $200, max.
  • Platform – Through targeting by platform, marketers are able to reach out to users based on the mobile platform they use – Android, iOS, BlackBerry, Windows Phone, etc. An obvious example of when this can be useful is if your app is available only on a specific platform.
  • Location – Location is one of the primary drivers for a mobile user’s experience. Many apps base their entire existence on the location of the user (notable examples being Lyft or Foursquare). Knowing where an app user is located, or knowing areas around the world where your app is (or isn’t) popular, can be key to creating a successful advertising strategy. This type of targeting is extremely useful for targeted promotions. For example, if Dunkin’ Donuts is offering nationwide promotions at local shops, you want to show the Central Park creative ad to 5th Avenue dwellers, and the Venice Beach ad to someone in Los Angeles.
  • Activity – Is your targeted audience immersed into mobile apps, or are they mostly casual users? Do they personalize their apps, or are they just looking for a quick update on something before moving on? It’s important to know how many times a user opens a specific app (number of sessions), and how long does that user stay with the app (session duration).  It also helps to target users by session recency, as a proxy to user engagement and “freshness”.
  • Days/Hours – Our SOOMLA Q1 2016 Mobile Insights Report says that users are most active during weekends. An Appsflyer report suggests the same. You can build your ad frequency around such intelligence, making sure the maximum number of people see the message you’re trying to communicate.

These were the basic parameters that marketers usually take into consideration when building a mobile advertising strategy. However, you shouldn’t stick just to these, as they’re too generic. If you’re really interested in penetrating the heart of your audience, you’ll need a more detailed approach. Here are the advanced targeting options you can try:

Advanced Targeting Dimensions

  • Installed apps – Millennials play more games than business people, and young parents are more inclined to track finances or download a parenting app. Every football fan will have a live scores app installed. You can target specific audiences based on the apps they have installed on their mobile device.  Combining this with other targeting dimensions doubles down the odds of hitting the right people.  For example, a major league baseball app owner located in St. Louis is likely to be a Cardinals fan.
  • App genres – Games are, by far, the most popular app genre out there, but business, educational or lifestyle apps also have a large audience. Each app genre has its own users and their specific habits.
games most popular app
Games are the most popular app genre by far [Credit: Statista (screenshot)]
  • In-app events – If you thought simply installing the app is everything a mobile marketer can and should be tracking, you’re in for a big surprise. There are a number of different in-app events you can track and form your marketing strategy around, such as how many times the app was opened, which features users engage with, have they linked it to other apps and services, etc. This is, however, a highly demanding element, in both infrastructure and manpower, which is why it’s mostly used by the biggest players. It is often used as means of re-engagement on existing users, as opposed to targeting new users. So, for example, having a CRM that manages all of your game’s users, can track level progression which would enable you to segment all players who’ve reached level 5 and target only them in your campaigns.
  • In-app revenue – Some would place this parameter under the ‘in-app events’ part, but I’d like to single it out as it is quite an important feature. The SOOMLA report says people who have made a purchase in one app are six times more likely to make a purchase in the next, and the percentage grows as the number of apps in use grow. Knowing who the spenders are, together with a couple of other parameters can prove highly useful for your campaign.  While only 1-2% of your users will ever pay, this small list of users can be expanded with lookalike features such as those provided by Facebook and SOOMLA Audiences.
  • Social graph – Social graph, or the social fingerprint, is the trace people leave online, on their social media channels such as Facebook, Twitter, Pinterest or LinkedIn. Marketers can track people that like, share or comment on certain types of content, serving ads which might be of direct interest to them. Marketers can also expand on the idea, if they move with the assumption that the friends of people with a specific social fingerprint have similar interests, as well as friends of friends, of friends and so on. So, for example, if you’re interested in traveling, your friends might also be, and their friends, quite likely.
  • Demographics – I had my doubts whether to put this in the Basic section or here. Targeting people by demographics means looking for groups with specific denominators, such as age, gender, location, annual income and marital status.
  • User lists – The most up close and personal method of advertising is called ‘User lists’, and that’s basically like a newsletter for your app. Except it’s not a newsletter, it’s an ad. And it’s not in your email, but on your smartphone apps. But seriously, it works in a similar way – the advertiser provides a precise list of devices, based on their IDFAs (Identifier for Advertising – Apple) or Advertising IDs (Android), and tells the ad network to target only those people. This is the most accurate type of advertising as it works by “show these ads ONLY to these people” principle.

Advanced mechanics are a bit more sophisticated and work well when combined with the basic ones we covered earlier in the article. They allow for pinpoint marketing and are a great tool for specific industries targeting specific types of people. There are even more advanced techniques, ones which have just recently started to enter the mainstream, and they require what is now known as Big Data and Machine Learning.

Big data revolves around data sets that are simply too large for data processing tools of today to handle. Facebook would be a good example, as the company gets enormous input about its users, with the emphasis being on – users. So big data revolves more around app users, what they like and dislike, and less about the app itself. Such insights can help marketers tailor strategies with filigree precision, and we can split the parameters in:

AI-Driven Targeting Dimensions

Yes, AI does stand for Artificial Intelligence and yes, it’s exactly what you think it would be, minus the whole sentient-robot-hellbent-on-destroying-humanity thing. By applying machine learning and AI algorithms to large networks of users such as those seen on Google search, Facebook, Twitter and many more ad networks, today’s marketing platforms can infer a higher order of attributes that characterize precise audiences on mobile:

  • Interests/Affinity – Targeting users based on their interests and activity requires extensive knowledge on what those users do on their mobile devices. We can target users based on other apps they use, websites they visit, things they browse and buy.  Once again, Facebook is the master of this domain.  By owning the media upon which 1.6 billion users worldwide dwell on daily, Facebook can tell what each users likes – from gardening to rugby to strategy games.
  • Persona – Persona targeting can be described (although brutally simplified), as in-depth demographic targeting. Instead of knowing the basic demographic information like how old someone is or where that person lives, knowing a more personal side, like interests, hobbies and habits is what goes under persona targeting. For example, smartphone and, more precisely, app usage, can tell you that older businessmen from France, that are also frequent flyers and are not big fans of sports, have a higher conversion rate to premium. Obviously, you’ll want to target such people with ads showing them all the benefits of switching to a premium version of your app.
  • Intent – A lot of people browse online, or over their mobile devices, without really wanting to buy anything. That’s like the digital equivalent of window shopping. However, that becomes a problem for marketers as they’re serving (and paying for) ads to people that don’t really plan on spending any cash. Luckily for all of us, there’s now a way to target people based on their intent. It’s quite a large and thorough approach, which requires a lot of data – including shopping habits, previous purchases, mobile shopping frequency, etc. However, having a machine scour through a lot of that data can give marketers the upper hand and allow for individual targeting. This is also used in unison with deep linking – a technique in which a person that has already installed an app via an ad, is taken to a specific location within the app, instead of the home screen. So for example, if a person was looking to book a hotel in Vienna at a specific time and finds an app to do that, once installed and ran, that app will take him straight to the booking section, with the proper dates and the right hotel already selected.

Platform Overview

Now that you know what to look for when targeting an audience here are a few examples of the leading audience targeting platforms.

  • facebook-logoimage-facebook-logopng-moshi-monsters-wiki-dmua0wep1Facebook Audiences: Easily create audience lists with Facebook, currently the targeting leader in the industry and the most popular choice for brands and performance marketers. You can either upload you own lists, create lookalike audiences or create new audiences. Facebook targeting dimensions include basic (location, age, gender, language) or detailed targeting (demographics, interests, behaviors, Facebook categories). Some unique targeting features to Facebook include targeting by connections via pages, apps or events. For each category you can target people who like your page/app/event, friends of people who like your page/app/event and exclude people who like your page/app/event. Facebook also supports audience retargeting based on a pixel in your website.


  • Twitter Audiences: You can create a Twitter audience from multiple resources such as uploading your own list, making a tag to collect website visitors or collecting your mobile app users. Logo_twitter_wordmark_1000Like Facebook, Twitter also supports audience retargeting based on a unique pixel for your website. Depending on your objective you can define your own audience dimensions by:  
    • Location
    • Gender
    • Language
    • Device/Platform/Carrier
    • Additional Audience Features: keywords, followers, interests, tailored audiences, TV targeting, behaviors, and event targeting (reaches people interested in global or regional events)

Twitter’s additional audience features are very unique because they allow you to target specific followers via their Twitter username. You can also target by interest categories to increase your reach. Or target by keywords that are relevant to your campaign and company.


  • BlueKai: Acquired by Oracle in 2014, BlueKai offers target audiences through its Oracle ID Graph. bluekaiIt reaches more than 90% of US online consumers by connecting: mobile IDs, email, postal addresses, social IDs and cookie IDs.
  • SOOMLA Audiences: With SOOMLA’s audiences dashboard you can now either upload a seed audience and generateSoomla-Logo-Blue a lookalike list or create a custom audience. It is the only platform that can segment audiences by in-app purchase patterns.  The custom audience dimensions include:
      • Country
      • Size
      • Genres
      • Type (Payers, Non-Payers, All)
      • Playing Recency
      • Paying Recency
      • Amount Paid (range)
      • Times Purchased
      • Retention

SOOMLA Audiences

  • PushSpring: Started in 2013, PushSpring offers custom segments, personas and app genre audience targeting. 1356With their Persona Explorer, the targeting dimensions include:
    • Life Stage: capture characteristics, behaviors, and patterns that define key life events for consumers
    • Interest & Activity: provides marketers with a comprehensive view of mobile consumer interests such as green friendly, avid skier, or a TV geek.
    • Intent: derived from observed mobile user behavior patterns across a variety of app and device signals that indicate definitive consumer intent for a product or service category such as cruise shoppers, apartment hunters, or impulse buyers.


  • Adience: A mobile audience management platform, Adience allows for audience tracking to help mobile applications understand their audiences icon2-adience_logomore clearly. With Adience, you can track: gender, age, geography, interests, likelihood of converting to premium, likelihood of installing app and personas.
  • Acxiom: Target users based on their interests with individual campaigns. Acxiom allows you to target by specific industry or event such as non-profit, political, retail, insurance and many other options. acxiom-logo-rAcxiom also has data packages already created that target specific holidays such as Easter, Father’s Day, Halloween and their packages also include Big Game and Tax Time.   

All this time, we’ve been discussing how to target different types of people, but not once have we mentioned what we’re targeting them with, and if not more important, then it’s at least equally important when building a quality ad strategy.

You can do a lion’s share of work with targeting, but if your ad sucks, you’re just doing Sisyphean tasks. And that’s where the two worlds collide – your target audience, no matter how carefully pinpointed it is, can still be fragmented when it comes to its reaction towards your ad.

Let’s say you want to advertise a new restaurant in town. Health and fitness-conscious females might like seeing an ad showing some healthy chicken salad, while those older businessmen from France would react better to an ad showing some nice beef steak and a glass of red wine. Luckily for all of us, we can set up a campaign with countless different adsets, each targeting a different group, based on any and all of the elements we showed above, and that’s something you should be doing.

The bottom line is – targeting is awesome, but works properly only when combined with ad creatives carefully built for the specific audience that’s being targeted.

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