LITE mobile ad targeting



Imagine a scene: you’re at the beach swimming in the waves, when out of nowhere your favorite sunglasses are knocked off your head; you blindly fish through the cloudy water where you last saw them. Many feel the same hopeless searching sensation when choosing targeting parameters for optimal mobile ad placement. While volumes of user data points exist, we can’t help but feel that finding the best combination to drive conversions is comparable to such a blind and hopeless search for your favorite beach accessory. While we might be tempted to launch large-scale campaigns with broad targeting parameters to optimize impressions, there are better means to maximize conversion rate; adding users with higher overall LTV.  In our experience, basic user data such as age range and mobile device can be complemented with new mobile-enabled granular user information to reach a user at the most applicable time. Apply the LITE model, using high level user data coupled with targeted ads based on:

Location, Incentives, Timing, and Effectiveness

Smartphone users spend hours of their life on their devices, and are never far from their phones, providing an optimal tool to target based on real-time location. Location targeting, however, is not simply applied to a country or even entire cities. Effective localized practices places locally-optimized ads to users at the most granular level possible, think of it as zip-code level targeting. Have a user searching for pizza delivery tonight in San Francisco? Don’t simply target them with a San Francisco dinner option, but rather a local establishment directly in their neighborhood.

And this brings us to incentives. Great, you have effectively targeted the user at their street-level location, but why should they click on your ad? Let’s take this same example, and this time we are offering a special promo code for a food delivery app in partnership with this local pizzeria. BINGO, the user attention is drawn by the local nature of the ad, and is incentivized to click based on a special offer.

Timing is everything, we’ve all heard that before. Taking a new example of a taxi hailing service, based on app usage data, we know that User A is most apt to use their device to plan their rides home in the evenings, particularly weekends. Such coveted information gives key insight showing precisely when User A is most susceptible to an ad for said mobile taxi ordering service. An incentivized local ad during this time period for such a service is essential to driving successful campaigns acquiring quality customers ready to use your app.

With this culmination of targeting metrics, mobile ads are applicable to each user’s specific situation, thus driving an effective ad campaign.